diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 6c25d3fb..0276b500 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -58,6 +58,9 @@ jobs: run: | python -m pytest -m coremdf tests/ + - name: Pre-install PsyNeuLink (from development branch on github) + run: python -m pip install git+https://github.com/ModECI/PsyNeuLink@devel + - name: Install optional dependencies run: python -m pip install .[all] diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index afa98653..1a23c72a 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -9,7 +9,7 @@ repos: rev: v3.4.0 hooks: - id: check-added-large-files - args: ['--maxkb=800'] + args: ['--maxkb=3000'] - id: check-case-conflict - id: check-merge-conflict - id: check-symlinks diff --git a/examples/PyTorch/PyTorch_MDF/convolution.json b/examples/PyTorch/PyTorch_MDF/convolution.json new file mode 100644 index 00000000..2f8d5f66 --- /dev/null +++ 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b/examples/PyTorch/PyTorch_MDF/convolution.py new file mode 100644 index 00000000..f5903e13 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/convolution.py @@ -0,0 +1,74 @@ +import numpy as np +import torch +import torch.nn.functional as F +from torch import nn +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +# Simple CNN +class CNN(nn.Module): + def __init__(self, in_channels=1, num_classes=10): + super().__init__() + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=8, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + ) + self.pool = nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2)) + self.conv2 = nn.Conv2d( + in_channels=8, + out_channels=16, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + ) + self.fc1 = nn.Linear(16 * 7 * 7, num_classes) + + def forward(self, x): + x = F.relu(self.conv1(x)) + x = self.pool(x) + x = F.relu(self.conv2(x)) + x = self.pool(x) + x = x.reshape(x.shape[0], -1) + x = self.fc1(x) + return x + + +# Hyperparameters +in_channels = 1 +num_classes = 10 + +model = CNN(in_channels=in_channels, num_classes=num_classes) + +# print(model) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 1, 28, 28)) + ebv_output = torch.zeros((10,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + model.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = model(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=model, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("convolution.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/example.onnx.png b/examples/PyTorch/PyTorch_MDF/example.onnx.png new file mode 100644 index 00000000..dc2f1b24 Binary files /dev/null and b/examples/PyTorch/PyTorch_MDF/example.onnx.png differ diff --git a/examples/PyTorch/PyTorch_MDF/example.png b/examples/PyTorch/PyTorch_MDF/example.png new file mode 100644 index 00000000..0f202f61 Binary files /dev/null and b/examples/PyTorch/PyTorch_MDF/example.png differ diff --git a/examples/PyTorch/PyTorch_MDF/imagenet_labels.txt b/examples/PyTorch/PyTorch_MDF/imagenet_labels.txt new file mode 100644 index 00000000..df234963 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/imagenet_labels.txt @@ -0,0 +1,1000 @@ +{0: 'tench, Tinca tinca', + 1: 'goldfish, Carassius auratus', + 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', + 3: 'tiger shark, Galeocerdo cuvieri', + 4: 'hammerhead, hammerhead shark', + 5: 'electric ray, crampfish, numbfish, torpedo', + 6: 'stingray', + 7: 'cock', + 8: 'hen', + 9: 'ostrich, Struthio camelus', + 10: 'brambling, Fringilla montifringilla', + 11: 'goldfinch, Carduelis carduelis', + 12: 'house finch, linnet, Carpodacus mexicanus', + 13: 'junco, snowbird', + 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea', + 15: 'robin, American robin, Turdus migratorius', + 16: 'bulbul', + 17: 'jay', + 18: 'magpie', + 19: 'chickadee', + 20: 'water ouzel, dipper', + 21: 'kite', + 22: 'bald eagle, American eagle, Haliaeetus leucocephalus', + 23: 'vulture', + 24: 'great grey owl, great gray owl, Strix nebulosa', + 25: 'European fire salamander, Salamandra salamandra', + 26: 'common newt, Triturus vulgaris', + 27: 'eft', + 28: 'spotted salamander, Ambystoma maculatum', + 29: 'axolotl, mud puppy, Ambystoma mexicanum', + 30: 'bullfrog, Rana catesbeiana', + 31: 'tree frog, tree-frog', + 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui', + 33: 'loggerhead, loggerhead turtle, Caretta caretta', + 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea', + 35: 'mud turtle', + 36: 'terrapin', + 37: 'box turtle, box tortoise', + 38: 'banded gecko', + 39: 'common iguana, iguana, Iguana iguana', + 40: 'American chameleon, anole, Anolis carolinensis', + 41: 'whiptail, whiptail lizard', + 42: 'agama', + 43: 'frilled lizard, Chlamydosaurus kingi', + 44: 'alligator lizard', + 45: 'Gila monster, Heloderma suspectum', + 46: 'green lizard, Lacerta viridis', + 47: 'African chameleon, Chamaeleo chamaeleon', + 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis', + 49: 'African crocodile, Nile crocodile, Crocodylus niloticus', + 50: 'American alligator, Alligator mississipiensis', + 51: 'triceratops', + 52: 'thunder snake, worm snake, Carphophis amoenus', + 53: 'ringneck snake, ring-necked snake, ring snake', + 54: 'hognose snake, puff adder, sand viper', + 55: 'green snake, grass snake', + 56: 'king snake, kingsnake', + 57: 'garter snake, grass snake', + 58: 'water snake', + 59: 'vine snake', + 60: 'night snake, Hypsiglena torquata', + 61: 'boa constrictor, Constrictor constrictor', + 62: 'rock python, rock snake, Python sebae', + 63: 'Indian cobra, Naja naja', + 64: 'green mamba', + 65: 'sea snake', + 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus', + 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus', + 68: 'sidewinder, horned rattlesnake, Crotalus cerastes', + 69: 'trilobite', + 70: 'harvestman, daddy longlegs, Phalangium opilio', + 71: 'scorpion', + 72: 'black and gold garden spider, Argiope aurantia', + 73: 'barn spider, Araneus cavaticus', + 74: 'garden spider, Aranea diademata', + 75: 'black widow, Latrodectus mactans', + 76: 'tarantula', + 77: 'wolf spider, hunting spider', + 78: 'tick', + 79: 'centipede', + 80: 'black grouse', + 81: 'ptarmigan', + 82: 'ruffed grouse, partridge, Bonasa umbellus', + 83: 'prairie chicken, prairie grouse, prairie fowl', + 84: 'peacock', + 85: 'quail', + 86: 'partridge', + 87: 'African grey, African gray, Psittacus erithacus', + 88: 'macaw', + 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita', + 90: 'lorikeet', + 91: 'coucal', + 92: 'bee eater', + 93: 'hornbill', + 94: 'hummingbird', + 95: 'jacamar', + 96: 'toucan', + 97: 'drake', + 98: 'red-breasted merganser, Mergus serrator', + 99: 'goose', + 100: 'black swan, Cygnus atratus', + 101: 'tusker', + 102: 'echidna, spiny anteater, anteater', + 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus', + 104: 'wallaby, brush kangaroo', + 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus', + 106: 'wombat', + 107: 'jellyfish', + 108: 'sea anemone, anemone', + 109: 'brain coral', + 110: 'flatworm, platyhelminth', + 111: 'nematode, nematode worm, roundworm', + 112: 'conch', + 113: 'snail', + 114: 'slug', + 115: 'sea slug, nudibranch', + 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore', + 117: 'chambered nautilus, pearly nautilus, nautilus', + 118: 'Dungeness crab, Cancer magister', + 119: 'rock crab, Cancer irroratus', + 120: 'fiddler crab', + 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica', + 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus', + 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish', + 124: 'crayfish, crawfish, crawdad, crawdaddy', + 125: 'hermit crab', + 126: 'isopod', + 127: 'white stork, Ciconia ciconia', + 128: 'black stork, Ciconia nigra', + 129: 'spoonbill', + 130: 'flamingo', + 131: 'little blue heron, Egretta caerulea', + 132: 'American egret, great white heron, Egretta albus', + 133: 'bittern', + 134: 'crane', + 135: 'limpkin, Aramus pictus', + 136: 'European gallinule, Porphyrio porphyrio', + 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana', + 138: 'bustard', + 139: 'ruddy turnstone, Arenaria interpres', + 140: 'red-backed sandpiper, dunlin, Erolia alpina', + 141: 'redshank, Tringa totanus', + 142: 'dowitcher', + 143: 'oystercatcher, oyster catcher', + 144: 'pelican', + 145: 'king penguin, Aptenodytes patagonica', + 146: 'albatross, mollymawk', + 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus', + 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca', + 149: 'dugong, Dugong dugon', + 150: 'sea lion', + 151: 'Chihuahua', + 152: 'Japanese spaniel', + 153: 'Maltese dog, Maltese terrier, Maltese', + 154: 'Pekinese, Pekingese, Peke', + 155: 'Shih-Tzu', + 156: 'Blenheim spaniel', + 157: 'papillon', + 158: 'toy terrier', + 159: 'Rhodesian ridgeback', + 160: 'Afghan hound, Afghan', + 161: 'basset, basset hound', + 162: 'beagle', + 163: 'bloodhound, sleuthhound', + 164: 'bluetick', + 165: 'black-and-tan coonhound', + 166: 'Walker hound, Walker foxhound', + 167: 'English foxhound', + 168: 'redbone', + 169: 'borzoi, Russian wolfhound', + 170: 'Irish wolfhound', + 171: 'Italian greyhound', + 172: 'whippet', + 173: 'Ibizan hound, Ibizan Podenco', + 174: 'Norwegian elkhound, elkhound', + 175: 'otterhound, otter hound', + 176: 'Saluki, gazelle hound', + 177: 'Scottish deerhound, deerhound', + 178: 'Weimaraner', + 179: 'Staffordshire bullterrier, Staffordshire bull terrier', + 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier', + 181: 'Bedlington terrier', + 182: 'Border terrier', + 183: 'Kerry blue terrier', + 184: 'Irish terrier', + 185: 'Norfolk terrier', + 186: 'Norwich terrier', + 187: 'Yorkshire terrier', + 188: 'wire-haired fox terrier', + 189: 'Lakeland terrier', + 190: 'Sealyham terrier, Sealyham', + 191: 'Airedale, Airedale terrier', + 192: 'cairn, cairn terrier', + 193: 'Australian terrier', + 194: 'Dandie Dinmont, Dandie Dinmont terrier', + 195: 'Boston bull, Boston terrier', + 196: 'miniature schnauzer', + 197: 'giant schnauzer', + 198: 'standard schnauzer', + 199: 'Scotch terrier, Scottish terrier, Scottie', + 200: 'Tibetan terrier, chrysanthemum dog', + 201: 'silky terrier, Sydney silky', + 202: 'soft-coated wheaten terrier', + 203: 'West Highland white terrier', + 204: 'Lhasa, Lhasa apso', + 205: 'flat-coated retriever', + 206: 'curly-coated retriever', + 207: 'golden retriever', + 208: 'Labrador retriever', + 209: 'Chesapeake Bay retriever', + 210: 'German short-haired pointer', + 211: 'vizsla, Hungarian pointer', + 212: 'English setter', + 213: 'Irish setter, red setter', + 214: 'Gordon setter', + 215: 'Brittany spaniel', + 216: 'clumber, clumber spaniel', + 217: 'English springer, English springer spaniel', + 218: 'Welsh springer spaniel', + 219: 'cocker spaniel, English cocker spaniel, cocker', + 220: 'Sussex spaniel', + 221: 'Irish water spaniel', + 222: 'kuvasz', + 223: 'schipperke', + 224: 'groenendael', + 225: 'malinois', + 226: 'briard', + 227: 'kelpie', + 228: 'komondor', + 229: 'Old English sheepdog, bobtail', + 230: 'Shetland sheepdog, Shetland sheep dog, Shetland', + 231: 'collie', + 232: 'Border collie', + 233: 'Bouvier des Flandres, Bouviers des Flandres', + 234: 'Rottweiler', + 235: 'German shepherd, German shepherd dog, German police dog, alsatian', + 236: 'Doberman, Doberman pinscher', + 237: 'miniature pinscher', + 238: 'Greater Swiss Mountain dog', + 239: 'Bernese mountain dog', + 240: 'Appenzeller', + 241: 'EntleBucher', + 242: 'boxer', + 243: 'bull mastiff', + 244: 'Tibetan mastiff', + 245: 'French bulldog', + 246: 'Great Dane', + 247: 'Saint Bernard, St Bernard', + 248: 'Eskimo dog, husky', + 249: 'malamute, malemute, Alaskan malamute', + 250: 'Siberian husky', + 251: 'dalmatian, coach dog, carriage dog', + 252: 'affenpinscher, monkey pinscher, monkey dog', + 253: 'basenji', + 254: 'pug, pug-dog', + 255: 'Leonberg', + 256: 'Newfoundland, Newfoundland dog', + 257: 'Great Pyrenees', + 258: 'Samoyed, Samoyede', + 259: 'Pomeranian', + 260: 'chow, chow chow', + 261: 'keeshond', + 262: 'Brabancon griffon', + 263: 'Pembroke, Pembroke Welsh corgi', + 264: 'Cardigan, Cardigan Welsh corgi', + 265: 'toy poodle', + 266: 'miniature poodle', + 267: 'standard poodle', + 268: 'Mexican hairless', + 269: 'timber wolf, grey wolf, gray wolf, Canis lupus', + 270: 'white wolf, Arctic wolf, Canis lupus tundrarum', + 271: 'red wolf, maned wolf, Canis rufus, Canis niger', + 272: 'coyote, prairie wolf, brush wolf, Canis latrans', + 273: 'dingo, warrigal, warragal, Canis dingo', + 274: 'dhole, Cuon alpinus', + 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus', + 276: 'hyena, hyaena', + 277: 'red fox, Vulpes vulpes', + 278: 'kit fox, Vulpes macrotis', + 279: 'Arctic fox, white fox, Alopex lagopus', + 280: 'grey fox, gray fox, Urocyon cinereoargenteus', + 281: 'tabby, tabby cat', + 282: 'tiger cat', + 283: 'Persian cat', + 284: 'Siamese cat, Siamese', + 285: 'Egyptian cat', + 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor', + 287: 'lynx, catamount', + 288: 'leopard, Panthera pardus', + 289: 'snow leopard, ounce, Panthera uncia', + 290: 'jaguar, panther, Panthera onca, Felis onca', + 291: 'lion, king of beasts, Panthera leo', + 292: 'tiger, Panthera tigris', + 293: 'cheetah, chetah, Acinonyx jubatus', + 294: 'brown bear, bruin, Ursus arctos', + 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus', + 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus', + 297: 'sloth bear, Melursus ursinus, Ursus ursinus', + 298: 'mongoose', + 299: 'meerkat, mierkat', + 300: 'tiger beetle', + 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle', + 302: 'ground beetle, carabid beetle', + 303: 'long-horned beetle, longicorn, longicorn beetle', + 304: 'leaf beetle, chrysomelid', + 305: 'dung beetle', + 306: 'rhinoceros beetle', + 307: 'weevil', + 308: 'fly', + 309: 'bee', + 310: 'ant, emmet, pismire', + 311: 'grasshopper, hopper', + 312: 'cricket', + 313: 'walking stick, walkingstick, stick insect', + 314: 'cockroach, roach', + 315: 'mantis, mantid', + 316: 'cicada, cicala', + 317: 'leafhopper', + 318: 'lacewing, lacewing fly', + 319: "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk", + 320: 'damselfly', + 321: 'admiral', + 322: 'ringlet, ringlet butterfly', + 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus', + 324: 'cabbage butterfly', + 325: 'sulphur butterfly, sulfur butterfly', + 326: 'lycaenid, lycaenid butterfly', + 327: 'starfish, sea star', + 328: 'sea urchin', + 329: 'sea cucumber, holothurian', + 330: 'wood rabbit, cottontail, cottontail rabbit', + 331: 'hare', + 332: 'Angora, Angora rabbit', + 333: 'hamster', + 334: 'porcupine, hedgehog', + 335: 'fox squirrel, eastern fox squirrel, Sciurus niger', + 336: 'marmot', + 337: 'beaver', + 338: 'guinea pig, Cavia cobaya', + 339: 'sorrel', + 340: 'zebra', + 341: 'hog, pig, grunter, squealer, Sus scrofa', + 342: 'wild boar, boar, Sus scrofa', + 343: 'warthog', + 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius', + 345: 'ox', + 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis', + 347: 'bison', + 348: 'ram, tup', + 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis', + 350: 'ibex, Capra ibex', + 351: 'hartebeest', + 352: 'impala, Aepyceros melampus', + 353: 'gazelle', + 354: 'Arabian camel, dromedary, Camelus dromedarius', + 355: 'llama', + 356: 'weasel', + 357: 'mink', + 358: 'polecat, fitch, foulmart, foumart, Mustela putorius', + 359: 'black-footed ferret, ferret, Mustela nigripes', + 360: 'otter', + 361: 'skunk, polecat, wood pussy', + 362: 'badger', + 363: 'armadillo', + 364: 'three-toed sloth, ai, Bradypus tridactylus', + 365: 'orangutan, orang, orangutang, Pongo pygmaeus', + 366: 'gorilla, Gorilla gorilla', + 367: 'chimpanzee, chimp, Pan troglodytes', + 368: 'gibbon, Hylobates lar', + 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus', + 370: 'guenon, guenon monkey', + 371: 'patas, hussar monkey, Erythrocebus patas', + 372: 'baboon', + 373: 'macaque', + 374: 'langur', + 375: 'colobus, colobus monkey', + 376: 'proboscis monkey, Nasalis larvatus', + 377: 'marmoset', + 378: 'capuchin, ringtail, Cebus capucinus', + 379: 'howler monkey, howler', + 380: 'titi, titi monkey', + 381: 'spider monkey, Ateles geoffroyi', + 382: 'squirrel monkey, Saimiri sciureus', + 383: 'Madagascar cat, ring-tailed lemur, Lemur catta', + 384: 'indri, indris, Indri indri, Indri brevicaudatus', + 385: 'Indian elephant, Elephas maximus', + 386: 'African elephant, Loxodonta africana', + 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens', + 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca', + 389: 'barracouta, snoek', + 390: 'eel', + 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch', + 392: 'rock beauty, Holocanthus tricolor', + 393: 'anemone fish', + 394: 'sturgeon', + 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus', + 396: 'lionfish', + 397: 'puffer, pufferfish, blowfish, globefish', + 398: 'abacus', + 399: 'abaya', + 400: "academic gown, academic robe, judge's robe", + 401: 'accordion, piano accordion, squeeze box', + 402: 'acoustic guitar', + 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier', + 404: 'airliner', + 405: 'airship, dirigible', + 406: 'altar', + 407: 'ambulance', + 408: 'amphibian, amphibious vehicle', + 409: 'analog clock', + 410: 'apiary, bee house', + 411: 'apron', + 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin', + 413: 'assault rifle, assault gun', + 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack', + 415: 'bakery, bakeshop, bakehouse', + 416: 'balance beam, beam', + 417: 'balloon', + 418: 'ballpoint, ballpoint pen, ballpen, Biro', + 419: 'Band Aid', + 420: 'banjo', + 421: 'bannister, banister, balustrade, balusters, handrail', + 422: 'barbell', + 423: 'barber chair', + 424: 'barbershop', + 425: 'barn', + 426: 'barometer', + 427: 'barrel, cask', + 428: 'barrow, garden cart, lawn cart, wheelbarrow', + 429: 'baseball', + 430: 'basketball', + 431: 'bassinet', + 432: 'bassoon', + 433: 'bathing cap, swimming cap', + 434: 'bath towel', + 435: 'bathtub, bathing tub, bath, tub', + 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon', + 437: 'beacon, lighthouse, beacon light, pharos', + 438: 'beaker', + 439: 'bearskin, busby, shako', + 440: 'beer bottle', + 441: 'beer glass', + 442: 'bell cote, bell cot', + 443: 'bib', + 444: 'bicycle-built-for-two, tandem bicycle, tandem', + 445: 'bikini, two-piece', + 446: 'binder, ring-binder', + 447: 'binoculars, field glasses, opera glasses', + 448: 'birdhouse', + 449: 'boathouse', + 450: 'bobsled, bobsleigh, bob', + 451: 'bolo tie, bolo, bola tie, bola', + 452: 'bonnet, poke bonnet', + 453: 'bookcase', + 454: 'bookshop, bookstore, bookstall', + 455: 'bottlecap', + 456: 'bow', + 457: 'bow tie, bow-tie, bowtie', + 458: 'brass, memorial tablet, plaque', + 459: 'brassiere, bra, bandeau', + 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty', + 461: 'breastplate, aegis, egis', + 462: 'broom', + 463: 'bucket, pail', + 464: 'buckle', + 465: 'bulletproof vest', + 466: 'bullet train, bullet', + 467: 'butcher shop, meat market', + 468: 'cab, hack, taxi, taxicab', + 469: 'caldron, cauldron', + 470: 'candle, taper, wax light', + 471: 'cannon', + 472: 'canoe', + 473: 'can opener, tin opener', + 474: 'cardigan', + 475: 'car mirror', + 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig', + 477: "carpenter's kit, tool kit", + 478: 'carton', + 479: 'car wheel', + 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM', + 481: 'cassette', + 482: 'cassette player', + 483: 'castle', + 484: 'catamaran', + 485: 'CD player', + 486: 'cello, violoncello', + 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone', + 488: 'chain', + 489: 'chainlink fence', + 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour', + 491: 'chain saw, chainsaw', + 492: 'chest', + 493: 'chiffonier, commode', + 494: 'chime, bell, gong', + 495: 'china cabinet, china closet', + 496: 'Christmas stocking', + 497: 'church, church building', + 498: 'cinema, movie theater, movie theatre, movie house, picture palace', + 499: 'cleaver, meat cleaver, chopper', + 500: 'cliff dwelling', + 501: 'cloak', + 502: 'clog, geta, patten, sabot', + 503: 'cocktail shaker', + 504: 'coffee mug', + 505: 'coffeepot', + 506: 'coil, spiral, volute, whorl, helix', + 507: 'combination lock', + 508: 'computer keyboard, keypad', + 509: 'confectionery, confectionary, candy store', + 510: 'container ship, containership, container vessel', + 511: 'convertible', + 512: 'corkscrew, bottle screw', + 513: 'cornet, horn, trumpet, trump', + 514: 'cowboy boot', + 515: 'cowboy hat, ten-gallon hat', + 516: 'cradle', + 517: 'crane', + 518: 'crash helmet', + 519: 'crate', + 520: 'crib, cot', + 521: 'Crock Pot', + 522: 'croquet ball', + 523: 'crutch', + 524: 'cuirass', + 525: 'dam, dike, dyke', + 526: 'desk', + 527: 'desktop computer', + 528: 'dial telephone, dial phone', + 529: 'diaper, nappy, napkin', + 530: 'digital clock', + 531: 'digital watch', + 532: 'dining table, board', + 533: 'dishrag, dishcloth', + 534: 'dishwasher, dish washer, dishwashing machine', + 535: 'disk brake, disc brake', + 536: 'dock, dockage, docking facility', + 537: 'dogsled, dog sled, dog sleigh', + 538: 'dome', + 539: 'doormat, welcome mat', + 540: 'drilling platform, offshore rig', + 541: 'drum, membranophone, tympan', + 542: 'drumstick', + 543: 'dumbbell', + 544: 'Dutch oven', + 545: 'electric fan, blower', + 546: 'electric guitar', + 547: 'electric locomotive', + 548: 'entertainment center', + 549: 'envelope', + 550: 'espresso maker', + 551: 'face powder', + 552: 'feather boa, boa', + 553: 'file, file cabinet, filing cabinet', + 554: 'fireboat', + 555: 'fire engine, fire truck', + 556: 'fire screen, fireguard', + 557: 'flagpole, flagstaff', + 558: 'flute, transverse flute', + 559: 'folding chair', + 560: 'football helmet', + 561: 'forklift', + 562: 'fountain', + 563: 'fountain pen', + 564: 'four-poster', + 565: 'freight car', + 566: 'French horn, horn', + 567: 'frying pan, frypan, skillet', + 568: 'fur coat', + 569: 'garbage truck, dustcart', + 570: 'gasmask, respirator, gas helmet', + 571: 'gas pump, gasoline pump, petrol pump, island dispenser', + 572: 'goblet', + 573: 'go-kart', + 574: 'golf ball', + 575: 'golfcart, golf cart', + 576: 'gondola', + 577: 'gong, tam-tam', + 578: 'gown', + 579: 'grand piano, grand', + 580: 'greenhouse, nursery, glasshouse', + 581: 'grille, radiator grille', + 582: 'grocery store, grocery, food market, market', + 583: 'guillotine', + 584: 'hair slide', + 585: 'hair spray', + 586: 'half track', + 587: 'hammer', + 588: 'hamper', + 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier', + 590: 'hand-held computer, hand-held microcomputer', + 591: 'handkerchief, hankie, hanky, hankey', + 592: 'hard disc, hard disk, fixed disk', + 593: 'harmonica, mouth organ, harp, mouth harp', + 594: 'harp', + 595: 'harvester, reaper', + 596: 'hatchet', + 597: 'holster', + 598: 'home theater, home theatre', + 599: 'honeycomb', + 600: 'hook, claw', + 601: 'hoopskirt, crinoline', + 602: 'horizontal bar, high bar', + 603: 'horse cart, horse-cart', + 604: 'hourglass', + 605: 'iPod', + 606: 'iron, smoothing iron', + 607: "jack-o'-lantern", + 608: 'jean, blue jean, denim', + 609: 'jeep, landrover', + 610: 'jersey, T-shirt, tee shirt', + 611: 'jigsaw puzzle', + 612: 'jinrikisha, ricksha, rickshaw', + 613: 'joystick', + 614: 'kimono', + 615: 'knee pad', + 616: 'knot', + 617: 'lab coat, laboratory coat', + 618: 'ladle', + 619: 'lampshade, lamp shade', + 620: 'laptop, laptop computer', + 621: 'lawn mower, mower', + 622: 'lens cap, lens cover', + 623: 'letter opener, paper knife, paperknife', + 624: 'library', + 625: 'lifeboat', + 626: 'lighter, light, igniter, ignitor', + 627: 'limousine, limo', + 628: 'liner, ocean liner', + 629: 'lipstick, lip rouge', + 630: 'Loafer', + 631: 'lotion', + 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system', + 633: "loupe, jeweler's loupe", + 634: 'lumbermill, sawmill', + 635: 'magnetic compass', + 636: 'mailbag, postbag', + 637: 'mailbox, letter box', + 638: 'maillot', + 639: 'maillot, tank suit', + 640: 'manhole cover', + 641: 'maraca', + 642: 'marimba, xylophone', + 643: 'mask', + 644: 'matchstick', + 645: 'maypole', + 646: 'maze, labyrinth', + 647: 'measuring cup', + 648: 'medicine chest, medicine cabinet', + 649: 'megalith, megalithic structure', + 650: 'microphone, mike', + 651: 'microwave, microwave oven', + 652: 'military uniform', + 653: 'milk can', + 654: 'minibus', + 655: 'miniskirt, mini', + 656: 'minivan', + 657: 'missile', + 658: 'mitten', + 659: 'mixing bowl', + 660: 'mobile home, manufactured home', + 661: 'Model T', + 662: 'modem', + 663: 'monastery', + 664: 'monitor', + 665: 'moped', + 666: 'mortar', + 667: 'mortarboard', + 668: 'mosque', + 669: 'mosquito net', + 670: 'motor scooter, scooter', + 671: 'mountain bike, all-terrain bike, off-roader', + 672: 'mountain tent', + 673: 'mouse, computer mouse', + 674: 'mousetrap', + 675: 'moving van', + 676: 'muzzle', + 677: 'nail', + 678: 'neck brace', + 679: 'necklace', + 680: 'nipple', + 681: 'notebook, notebook computer', + 682: 'obelisk', + 683: 'oboe, hautboy, hautbois', + 684: 'ocarina, sweet potato', + 685: 'odometer, hodometer, mileometer, milometer', + 686: 'oil filter', + 687: 'organ, pipe organ', + 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO', + 689: 'overskirt', + 690: 'oxcart', + 691: 'oxygen mask', + 692: 'packet', + 693: 'paddle, boat paddle', + 694: 'paddlewheel, paddle wheel', + 695: 'padlock', + 696: 'paintbrush', + 697: "pajama, pyjama, pj's, jammies", + 698: 'palace', + 699: 'panpipe, pandean pipe, syrinx', + 700: 'paper towel', + 701: 'parachute, chute', + 702: 'parallel bars, bars', + 703: 'park bench', + 704: 'parking meter', + 705: 'passenger car, coach, carriage', + 706: 'patio, terrace', + 707: 'pay-phone, pay-station', + 708: 'pedestal, plinth, footstall', + 709: 'pencil box, pencil case', + 710: 'pencil sharpener', + 711: 'perfume, essence', + 712: 'Petri dish', + 713: 'photocopier', + 714: 'pick, plectrum, plectron', + 715: 'pickelhaube', + 716: 'picket fence, paling', + 717: 'pickup, pickup truck', + 718: 'pier', + 719: 'piggy bank, penny bank', + 720: 'pill bottle', + 721: 'pillow', + 722: 'ping-pong ball', + 723: 'pinwheel', + 724: 'pirate, pirate ship', + 725: 'pitcher, ewer', + 726: "plane, carpenter's plane, woodworking plane", + 727: 'planetarium', + 728: 'plastic bag', + 729: 'plate rack', + 730: 'plow, plough', + 731: "plunger, plumber's helper", + 732: 'Polaroid camera, Polaroid Land camera', + 733: 'pole', + 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria', + 735: 'poncho', + 736: 'pool table, billiard table, snooker table', + 737: 'pop bottle, soda bottle', + 738: 'pot, flowerpot', + 739: "potter's wheel", + 740: 'power drill', + 741: 'prayer rug, prayer mat', + 742: 'printer', + 743: 'prison, prison house', + 744: 'projectile, missile', + 745: 'projector', + 746: 'puck, hockey puck', + 747: 'punching bag, punch bag, punching ball, punchball', + 748: 'purse', + 749: 'quill, quill pen', + 750: 'quilt, comforter, comfort, puff', + 751: 'racer, race car, racing car', + 752: 'racket, racquet', + 753: 'radiator', + 754: 'radio, wireless', + 755: 'radio telescope, radio reflector', + 756: 'rain barrel', + 757: 'recreational vehicle, RV, R.V.', + 758: 'reel', + 759: 'reflex camera', + 760: 'refrigerator, icebox', + 761: 'remote control, remote', + 762: 'restaurant, eating house, eating place, eatery', + 763: 'revolver, six-gun, six-shooter', + 764: 'rifle', + 765: 'rocking chair, rocker', + 766: 'rotisserie', + 767: 'rubber eraser, rubber, pencil eraser', + 768: 'rugby ball', + 769: 'rule, ruler', + 770: 'running shoe', + 771: 'safe', + 772: 'safety pin', + 773: 'saltshaker, salt shaker', + 774: 'sandal', + 775: 'sarong', + 776: 'sax, saxophone', + 777: 'scabbard', + 778: 'scale, weighing machine', + 779: 'school bus', + 780: 'schooner', + 781: 'scoreboard', + 782: 'screen, CRT screen', + 783: 'screw', + 784: 'screwdriver', + 785: 'seat belt, seatbelt', + 786: 'sewing machine', + 787: 'shield, buckler', + 788: 'shoe shop, shoe-shop, shoe store', + 789: 'shoji', + 790: 'shopping basket', + 791: 'shopping cart', + 792: 'shovel', + 793: 'shower cap', + 794: 'shower curtain', + 795: 'ski', + 796: 'ski mask', + 797: 'sleeping bag', + 798: 'slide rule, slipstick', + 799: 'sliding door', + 800: 'slot, one-armed bandit', + 801: 'snorkel', + 802: 'snowmobile', + 803: 'snowplow, snowplough', + 804: 'soap dispenser', + 805: 'soccer ball', + 806: 'sock', + 807: 'solar dish, solar collector, solar furnace', + 808: 'sombrero', + 809: 'soup bowl', + 810: 'space bar', + 811: 'space heater', + 812: 'space shuttle', + 813: 'spatula', + 814: 'speedboat', + 815: "spider web, spider's web", + 816: 'spindle', + 817: 'sports car, sport car', + 818: 'spotlight, spot', + 819: 'stage', + 820: 'steam locomotive', + 821: 'steel arch bridge', + 822: 'steel drum', + 823: 'stethoscope', + 824: 'stole', + 825: 'stone wall', + 826: 'stopwatch, stop watch', + 827: 'stove', + 828: 'strainer', + 829: 'streetcar, tram, tramcar, trolley, trolley car', + 830: 'stretcher', + 831: 'studio couch, day bed', + 832: 'stupa, tope', + 833: 'submarine, pigboat, sub, U-boat', + 834: 'suit, suit of clothes', + 835: 'sundial', + 836: 'sunglass', + 837: 'sunglasses, dark glasses, shades', + 838: 'sunscreen, sunblock, sun blocker', + 839: 'suspension bridge', + 840: 'swab, swob, mop', + 841: 'sweatshirt', + 842: 'swimming trunks, bathing trunks', + 843: 'swing', + 844: 'switch, electric switch, electrical switch', + 845: 'syringe', + 846: 'table lamp', + 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle', + 848: 'tape player', + 849: 'teapot', + 850: 'teddy, teddy bear', + 851: 'television, television system', + 852: 'tennis ball', + 853: 'thatch, thatched roof', + 854: 'theater curtain, theatre curtain', + 855: 'thimble', + 856: 'thresher, thrasher, threshing machine', + 857: 'throne', + 858: 'tile roof', + 859: 'toaster', + 860: 'tobacco shop, tobacconist shop, tobacconist', + 861: 'toilet seat', + 862: 'torch', + 863: 'totem pole', + 864: 'tow truck, tow car, wrecker', + 865: 'toyshop', + 866: 'tractor', + 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi', + 868: 'tray', + 869: 'trench coat', + 870: 'tricycle, trike, velocipede', + 871: 'trimaran', + 872: 'tripod', + 873: 'triumphal arch', + 874: 'trolleybus, trolley coach, trackless trolley', + 875: 'trombone', + 876: 'tub, vat', + 877: 'turnstile', + 878: 'typewriter keyboard', + 879: 'umbrella', + 880: 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modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + mnasnet1_3.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = mnasnet1_3(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=mnasnet1_3, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("mnasNet1_3.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/mobilenetv2.json b/examples/PyTorch/PyTorch_MDF/mobilenetv2.json new file mode 100644 index 00000000..47c31f7d --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/mobilenetv2.json @@ -0,0 +1,7606 @@ +{ + "MobileNetV2": { + "format": "ModECI MDF v0.4", + 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"sender_port": "_385", + "receiver_port": "_385" + }, + "Clip_386_Conv_588": { + "sender": "Clip_386", + "receiver": "Conv_588", + "sender_port": "_386", + "receiver_port": "_386" + }, + "Conv_588_Add_389": { + "sender": "Conv_588", + "receiver": "Add_389", + "sender_port": "_588", + "receiver_port": "_588" + }, + "Add_389_Conv_591": { + "sender": "Add_389", + "receiver": "Conv_591", + "sender_port": "_389", + "receiver_port": "_389" + }, + "Conv_591_Clip_394": { + "sender": "Conv_591", + "receiver": "Clip_394", + "sender_port": "_591", + "receiver_port": "_591" + }, + "Constant_392_Clip_394": { + "sender": "Constant_392", + "receiver": "Clip_394", + "sender_port": "_392", + "receiver_port": "_392" + }, + "Constant_393_Clip_394": { + "sender": "Constant_393", + "receiver": "Clip_394", + "sender_port": "_393", + "receiver_port": "_393" + }, + "Clip_394_Conv_594": { + "sender": "Clip_394", + "receiver": "Conv_594", + "sender_port": "_394", + "receiver_port": "_394" + }, + "Conv_594_Clip_399": { + "sender": "Conv_594", + "receiver": "Clip_399", + "sender_port": "_594", + "receiver_port": "_594" + }, + "Constant_397_Clip_399": { + "sender": "Constant_397", + "receiver": "Clip_399", + "sender_port": "_397", + "receiver_port": "_397" + }, + "Constant_398_Clip_399": { + "sender": "Constant_398", + "receiver": "Clip_399", + "sender_port": "_398", + "receiver_port": "_398" + }, + "Clip_399_Conv_597": { + "sender": "Clip_399", + "receiver": "Conv_597", + "sender_port": "_399", + "receiver_port": "_399" + }, + "Conv_597_Conv_600": { + "sender": "Conv_597", + "receiver": "Conv_600", + "sender_port": "_597", + "receiver_port": "_597" + }, + "Conv_597_Add_414": { + "sender": "Conv_597", + "receiver": "Add_414", + "sender_port": "_597", + "receiver_port": "_597" + }, + "Conv_600_Clip_406": { + "sender": "Conv_600", + "receiver": "Clip_406", + "sender_port": "_600", + "receiver_port": "_600" + }, + "Constant_404_Clip_406": { + "sender": "Constant_404", + "receiver": "Clip_406", + "sender_port": "_404", + "receiver_port": "_404" + }, + "Constant_405_Clip_406": { + "sender": "Constant_405", + "receiver": "Clip_406", + "sender_port": "_405", + "receiver_port": "_405" + }, + "Clip_406_Conv_603": { + "sender": "Clip_406", + "receiver": "Conv_603", + "sender_port": "_406", + "receiver_port": "_406" + }, + "Conv_603_Clip_411": { + "sender": "Conv_603", + "receiver": "Clip_411", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Constant_409_Clip_411": { + "sender": "Constant_409", + "receiver": "Clip_411", + "sender_port": "_409", + "receiver_port": "_409" + }, + "Constant_410_Clip_411": { + "sender": "Constant_410", + "receiver": "Clip_411", + "sender_port": "_410", + "receiver_port": "_410" + }, + "Clip_411_Conv_606": { + "sender": "Clip_411", + "receiver": "Conv_606", + "sender_port": "_411", + "receiver_port": "_411" + }, + "Conv_606_Add_414": { + "sender": "Conv_606", + "receiver": "Add_414", + "sender_port": "_606", + "receiver_port": "_606" + }, + "Add_414_Conv_609": { + "sender": "Add_414", + "receiver": "Conv_609", + "sender_port": "_414", + "receiver_port": "_414" + }, + "Add_414_Add_427": { + "sender": "Add_414", + "receiver": "Add_427", + "sender_port": "_414", + "receiver_port": "_414" + }, + "Conv_609_Clip_419": { + "sender": "Conv_609", + "receiver": "Clip_419", + "sender_port": "_609", + "receiver_port": "_609" + }, + "Constant_417_Clip_419": { + "sender": "Constant_417", + "receiver": "Clip_419", + "sender_port": "_417", + "receiver_port": "_417" + }, + "Constant_418_Clip_419": { + "sender": "Constant_418", + "receiver": "Clip_419", + "sender_port": "_418", + "receiver_port": "_418" + }, + "Clip_419_Conv_612": { + "sender": "Clip_419", + "receiver": "Conv_612", + "sender_port": "_419", + "receiver_port": "_419" + }, + "Conv_612_Clip_424": { + "sender": "Conv_612", + "receiver": "Clip_424", + "sender_port": "_612", + "receiver_port": "_612" + }, + "Constant_422_Clip_424": { + "sender": "Constant_422", + "receiver": "Clip_424", + "sender_port": "_422", + "receiver_port": "_422" + }, + "Constant_423_Clip_424": { + "sender": "Constant_423", + "receiver": "Clip_424", + "sender_port": "_423", + "receiver_port": "_423" + }, + "Clip_424_Conv_615": { + "sender": "Clip_424", + "receiver": "Conv_615", + "sender_port": "_424", + "receiver_port": "_424" + }, + "Conv_615_Add_427": { + "sender": "Conv_615", + "receiver": "Add_427", + "sender_port": "_615", + "receiver_port": "_615" + }, + "Add_427_Conv_618": { + "sender": "Add_427", + "receiver": "Conv_618", + "sender_port": "_427", + "receiver_port": "_427" + }, + "Add_427_Add_440": { + "sender": "Add_427", + "receiver": "Add_440", + "sender_port": "_427", + "receiver_port": "_427" + }, + "Conv_618_Clip_432": { + "sender": "Conv_618", + "receiver": "Clip_432", + "sender_port": "_618", + "receiver_port": "_618" + }, + "Constant_430_Clip_432": { + "sender": "Constant_430", + "receiver": "Clip_432", + "sender_port": "_430", + "receiver_port": "_430" + }, + "Constant_431_Clip_432": { + "sender": "Constant_431", + "receiver": "Clip_432", + "sender_port": "_431", + "receiver_port": "_431" + }, + "Clip_432_Conv_621": { + "sender": "Clip_432", + "receiver": "Conv_621", + "sender_port": "_432", + "receiver_port": "_432" + }, + "Conv_621_Clip_437": { + "sender": "Conv_621", + "receiver": "Clip_437", + "sender_port": "_621", + "receiver_port": "_621" + }, + "Constant_435_Clip_437": { + "sender": "Constant_435", + "receiver": "Clip_437", + "sender_port": "_435", + "receiver_port": "_435" + }, + "Constant_436_Clip_437": { + "sender": "Constant_436", + "receiver": "Clip_437", + "sender_port": "_436", + "receiver_port": "_436" + }, + "Clip_437_Conv_624": { + "sender": "Clip_437", + "receiver": "Conv_624", + "sender_port": "_437", + "receiver_port": "_437" + }, + "Conv_624_Add_440": { + "sender": "Conv_624", + "receiver": "Add_440", + "sender_port": "_624", + "receiver_port": "_624" + }, + "Add_440_Conv_627": { + "sender": "Add_440", + "receiver": "Conv_627", + "sender_port": "_440", + "receiver_port": "_440" + }, + "Conv_627_Clip_445": { + "sender": "Conv_627", + "receiver": "Clip_445", + "sender_port": "_627", + "receiver_port": "_627" + }, + "Constant_443_Clip_445": { + "sender": "Constant_443", + "receiver": "Clip_445", + "sender_port": "_443", + "receiver_port": "_443" + }, + "Constant_444_Clip_445": { + "sender": "Constant_444", + "receiver": "Clip_445", + "sender_port": "_444", + "receiver_port": "_444" + }, + "Clip_445_Conv_630": { + "sender": "Clip_445", + "receiver": "Conv_630", + "sender_port": "_445", + "receiver_port": "_445" + }, + "Conv_630_Clip_450": { + "sender": "Conv_630", + "receiver": "Clip_450", + "sender_port": "_630", + "receiver_port": "_630" + }, + "Constant_448_Clip_450": { + "sender": "Constant_448", + "receiver": "Clip_450", + "sender_port": "_448", + "receiver_port": "_448" + }, + "Constant_449_Clip_450": { + "sender": "Constant_449", + "receiver": "Clip_450", + "sender_port": "_449", + "receiver_port": "_449" + }, + "Clip_450_Conv_633": { + "sender": "Clip_450", + "receiver": "Conv_633", + "sender_port": "_450", + "receiver_port": "_450" + }, + "Conv_633_Conv_636": { + "sender": "Conv_633", + "receiver": "Conv_636", + "sender_port": "_633", + "receiver_port": "_633" + }, + "Conv_633_Add_465": { + "sender": "Conv_633", + "receiver": "Add_465", + "sender_port": "_633", + "receiver_port": "_633" + }, + "Conv_636_Clip_457": { + "sender": "Conv_636", + "receiver": "Clip_457", + "sender_port": "_636", + "receiver_port": "_636" + }, + "Constant_455_Clip_457": { + "sender": "Constant_455", + "receiver": "Clip_457", + "sender_port": "_455", + "receiver_port": "_455" + }, + "Constant_456_Clip_457": { + "sender": "Constant_456", + "receiver": "Clip_457", + "sender_port": "_456", + "receiver_port": "_456" + }, + "Clip_457_Conv_639": { + "sender": "Clip_457", + "receiver": "Conv_639", + "sender_port": "_457", + "receiver_port": "_457" + }, + "Conv_639_Clip_462": { + "sender": "Conv_639", + "receiver": "Clip_462", + "sender_port": "_639", + "receiver_port": "_639" + }, + "Constant_460_Clip_462": { + "sender": "Constant_460", + "receiver": "Clip_462", + "sender_port": "_460", + "receiver_port": "_460" + }, + "Constant_461_Clip_462": { + "sender": "Constant_461", + "receiver": "Clip_462", + "sender_port": "_461", + "receiver_port": "_461" + }, + "Clip_462_Conv_642": { + "sender": "Clip_462", + "receiver": "Conv_642", + "sender_port": "_462", + "receiver_port": "_462" + }, + "Conv_642_Add_465": { + "sender": "Conv_642", + "receiver": "Add_465", + "sender_port": "_642", + "receiver_port": "_642" + }, + "Add_465_Conv_645": { + "sender": "Add_465", + "receiver": "Conv_645", + "sender_port": "_465", + "receiver_port": "_465" + }, + "Add_465_Add_478": { + "sender": "Add_465", + "receiver": "Add_478", + "sender_port": "_465", + "receiver_port": "_465" + }, + "Conv_645_Clip_470": { + "sender": "Conv_645", + "receiver": "Clip_470", + "sender_port": "_645", + "receiver_port": "_645" + }, + "Constant_468_Clip_470": { + "sender": "Constant_468", + "receiver": "Clip_470", + "sender_port": "_468", + "receiver_port": "_468" + }, + "Constant_469_Clip_470": { + "sender": "Constant_469", + "receiver": "Clip_470", + "sender_port": "_469", + "receiver_port": "_469" + }, + "Clip_470_Conv_648": { + "sender": "Clip_470", + "receiver": "Conv_648", + "sender_port": "_470", + "receiver_port": "_470" + }, + "Conv_648_Clip_475": { + "sender": "Conv_648", + "receiver": "Clip_475", + "sender_port": "_648", + "receiver_port": "_648" + }, + "Constant_473_Clip_475": { + "sender": "Constant_473", + "receiver": "Clip_475", + "sender_port": "_473", + "receiver_port": "_473" + }, + "Constant_474_Clip_475": { + "sender": "Constant_474", + "receiver": "Clip_475", + "sender_port": "_474", + "receiver_port": "_474" + }, + "Clip_475_Conv_651": { + "sender": "Clip_475", + "receiver": "Conv_651", + "sender_port": "_475", + "receiver_port": "_475" + }, + "Conv_651_Add_478": { + "sender": "Conv_651", + "receiver": "Add_478", + "sender_port": "_651", + "receiver_port": "_651" + }, + "Add_478_Conv_654": { + "sender": "Add_478", + "receiver": "Conv_654", + "sender_port": "_478", + "receiver_port": "_478" + }, + "Conv_654_Clip_483": { + "sender": "Conv_654", + "receiver": "Clip_483", + "sender_port": "_654", + "receiver_port": "_654" + }, + "Constant_481_Clip_483": { + "sender": "Constant_481", + "receiver": "Clip_483", + "sender_port": "_481", + "receiver_port": "_481" + }, + "Constant_482_Clip_483": { + "sender": "Constant_482", + "receiver": "Clip_483", + "sender_port": "_482", + "receiver_port": "_482" + }, + "Clip_483_Conv_657": { + "sender": "Clip_483", + "receiver": "Conv_657", + "sender_port": "_483", + "receiver_port": "_483" + }, + "Conv_657_Clip_488": { + "sender": "Conv_657", + "receiver": "Clip_488", + "sender_port": "_657", + "receiver_port": "_657" + }, + "Constant_486_Clip_488": { + "sender": "Constant_486", + "receiver": "Clip_488", + "sender_port": "_486", + "receiver_port": "_486" + }, + "Constant_487_Clip_488": { + "sender": "Constant_487", + "receiver": "Clip_488", + "sender_port": "_487", + "receiver_port": "_487" + }, + "Clip_488_Conv_660": { + "sender": "Clip_488", + "receiver": "Conv_660", + "sender_port": "_488", + "receiver_port": "_488" + }, + "Conv_660_Conv_663": { + "sender": "Conv_660", + "receiver": "Conv_663", + "sender_port": "_660", + "receiver_port": "_660" + }, + "Conv_660_Add_503": { + "sender": "Conv_660", + "receiver": "Add_503", + "sender_port": "_660", + "receiver_port": "_660" + }, + "Conv_663_Clip_495": { + "sender": "Conv_663", + "receiver": "Clip_495", + "sender_port": "_663", + "receiver_port": "_663" + }, + "Constant_493_Clip_495": { + "sender": "Constant_493", + "receiver": "Clip_495", + "sender_port": "_493", + "receiver_port": "_493" + }, + "Constant_494_Clip_495": { + "sender": "Constant_494", + "receiver": "Clip_495", + "sender_port": "_494", + "receiver_port": "_494" + }, + "Clip_495_Conv_666": { + "sender": "Clip_495", + "receiver": "Conv_666", + "sender_port": "_495", + "receiver_port": "_495" + }, + "Conv_666_Clip_500": { + "sender": "Conv_666", + "receiver": "Clip_500", + "sender_port": "_666", + "receiver_port": "_666" + }, + "Constant_498_Clip_500": { + "sender": "Constant_498", + "receiver": "Clip_500", + "sender_port": "_498", + "receiver_port": "_498" + }, + "Constant_499_Clip_500": { + "sender": "Constant_499", + "receiver": "Clip_500", + "sender_port": "_499", + "receiver_port": "_499" + }, + "Clip_500_Conv_669": { + "sender": "Clip_500", + "receiver": "Conv_669", + "sender_port": "_500", + "receiver_port": "_500" + }, + "Conv_669_Add_503": { + "sender": "Conv_669", + "receiver": "Add_503", + "sender_port": "_669", + "receiver_port": "_669" + }, + "Add_503_Conv_672": { + "sender": "Add_503", + "receiver": "Conv_672", + "sender_port": "_503", + "receiver_port": "_503" + }, + "Add_503_Add_516": { + "sender": "Add_503", + "receiver": "Add_516", + "sender_port": "_503", + "receiver_port": "_503" + }, + "Conv_672_Clip_508": { + "sender": "Conv_672", + "receiver": "Clip_508", + "sender_port": "_672", + "receiver_port": "_672" + }, + "Constant_506_Clip_508": { + "sender": "Constant_506", + "receiver": "Clip_508", + "sender_port": "_506", + "receiver_port": "_506" + }, + "Constant_507_Clip_508": { + "sender": "Constant_507", + "receiver": "Clip_508", + "sender_port": "_507", + "receiver_port": "_507" + }, + "Clip_508_Conv_675": { + "sender": "Clip_508", + "receiver": "Conv_675", + "sender_port": "_508", + "receiver_port": "_508" + }, + "Conv_675_Clip_513": { + "sender": "Conv_675", + "receiver": "Clip_513", + "sender_port": "_675", + "receiver_port": "_675" + }, + "Constant_511_Clip_513": { + "sender": "Constant_511", + "receiver": "Clip_513", + "sender_port": "_511", + "receiver_port": "_511" + }, + "Constant_512_Clip_513": { + "sender": "Constant_512", + "receiver": "Clip_513", + "sender_port": "_512", + "receiver_port": "_512" + }, + "Clip_513_Conv_678": { + "sender": "Clip_513", + "receiver": "Conv_678", + "sender_port": "_513", + "receiver_port": "_513" + }, + "Conv_678_Add_516": { + "sender": "Conv_678", + "receiver": "Add_516", + "sender_port": "_678", + "receiver_port": "_678" + }, + "Add_516_Conv_681": { + "sender": "Add_516", + "receiver": "Conv_681", + "sender_port": "_516", + "receiver_port": "_516" + }, + "Conv_681_Clip_521": { + "sender": "Conv_681", + "receiver": "Clip_521", + "sender_port": "_681", + "receiver_port": "_681" + }, + "Constant_519_Clip_521": { + "sender": "Constant_519", + "receiver": "Clip_521", + "sender_port": "_519", + "receiver_port": "_519" + }, + "Constant_520_Clip_521": { + "sender": "Constant_520", + "receiver": "Clip_521", + "sender_port": "_520", + "receiver_port": "_520" + }, + "Clip_521_Conv_684": { + "sender": "Clip_521", + "receiver": "Conv_684", + "sender_port": "_521", + "receiver_port": "_521" + }, + "Conv_684_Clip_526": { + "sender": "Conv_684", + "receiver": "Clip_526", + "sender_port": "_684", + "receiver_port": "_684" + }, + "Constant_524_Clip_526": { + "sender": "Constant_524", + "receiver": "Clip_526", + "sender_port": "_524", + "receiver_port": "_524" + }, + "Constant_525_Clip_526": { + "sender": "Constant_525", + "receiver": "Clip_526", + "sender_port": "_525", + "receiver_port": "_525" + }, + "Clip_526_Conv_687": { + "sender": "Clip_526", + "receiver": "Conv_687", + "sender_port": "_526", + "receiver_port": "_526" + }, + "Conv_687_Conv_690": { + "sender": "Conv_687", + "receiver": "Conv_690", + "sender_port": "_687", + "receiver_port": "_687" + }, + "Conv_690_Clip_533": { + "sender": "Conv_690", + "receiver": "Clip_533", + "sender_port": "_690", + "receiver_port": "_690" + }, + "Constant_531_Clip_533": { + "sender": "Constant_531", + "receiver": "Clip_533", + "sender_port": "_531", + "receiver_port": "_531" + }, + "Constant_532_Clip_533": { + "sender": "Constant_532", + "receiver": "Clip_533", + "sender_port": "_532", + "receiver_port": "_532" + }, + "Clip_533_GlobalAveragePool_534": { + "sender": "Clip_533", + "receiver": "GlobalAveragePool_534", + "sender_port": "_533", + "receiver_port": "_533" + }, + "GlobalAveragePool_534_Flatten_535": { + "sender": "GlobalAveragePool_534", + "receiver": "Flatten_535", + "sender_port": "_534", + "receiver_port": "_534" + }, + "Flatten_535_Gemm_536": { + "sender": "Flatten_535", + "receiver": "Gemm_536", + "sender_port": "_535", + "receiver_port": "_535" + } + } + } + }, + "onnx_opset_version": 9 + } +} diff --git a/examples/PyTorch/PyTorch_MDF/mobilenetv2.py b/examples/PyTorch/PyTorch_MDF/mobilenetv2.py new file mode 100644 index 00000000..4630958b --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/mobilenetv2.py @@ -0,0 +1,35 @@ +import torchvision.models as models +import torch +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +mobilenet_v2 = models.mobilenet_v2(pretrained=False) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + mobilenet_v2.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = mobilenet_v2(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=mobilenet_v2, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("mobilenetv2.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/pytorch_example_images/a/img1.jpeg b/examples/PyTorch/PyTorch_MDF/pytorch_example_images/a/img1.jpeg new file mode 100644 index 00000000..be222696 Binary files /dev/null and b/examples/PyTorch/PyTorch_MDF/pytorch_example_images/a/img1.jpeg differ diff --git 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new file mode 100644 index 00000000..cba2ae22 Binary files /dev/null and b/examples/PyTorch/PyTorch_MDF/pytorch_example_images/a/img5.jpeg differ diff --git a/examples/PyTorch/PyTorch_MDF/pytorch_mdf_examples.ipynb b/examples/PyTorch/PyTorch_MDF/pytorch_mdf_examples.ipynb new file mode 100644 index 00000000..387c0ec5 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/pytorch_mdf_examples.ipynb @@ -0,0 +1,1080 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "75766acc", + "metadata": {}, + "source": [ + "## Sample Notebook comparing MDF and PyTorch model" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "cd849be5", + "metadata": {}, + "outputs": [], + "source": [ + "from torchvision import transforms\n", + "from torchvision.io import read_image\n", + "import torch\n", + "from PIL import Image\n", + "import torchvision.models as models\n", + "import numpy as np\n", + "\n", + "from modeci_mdf.interfaces.pytorch import pytorch_to_mdf\n", + "from modeci_mdf.execution_engine import EvaluableGraph" + ] + }, + { + "cell_type": "markdown", + "id": "26dd53e2", + "metadata": {}, + "source": [ + "### Preprocess the input image" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d9bb5c36", + "metadata": {}, + "outputs": [], + "source": [ + "def image_loader(loader, image):\n", + " image = loader(image).float()\n", + " image = image.clone().detach().requires_grad_(True)\n", + " image = image.unsqueeze(0)\n", + " return image\n", + "\n", + "data_transforms = transforms.Compose([\n", + " transforms.Resize(256),\n", + " transforms.CenterCrop(224),\n", + " transforms.ToTensor()\n", + "])" + ] + }, + { + "cell_type": "markdown", + "id": "b041e60d", + "metadata": {}, + "source": [ + "### Load pretrained IMAGENET model" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ad389212", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "MobileNetV3(\n", + " (features): Sequential(\n", + " (0): 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(activation): ReLU()\n", + " (scale_activation): Hardsigmoid()\n", + " )\n", + " (3): ConvNormActivation(\n", + " (0): Conv2d(672, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(160, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " )\n", + " (14): InvertedResidual(\n", + " (block): Sequential(\n", + " (0): ConvNormActivation(\n", + " (0): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(960, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " (2): Hardswish()\n", + " )\n", + " (1): ConvNormActivation(\n", + " (0): Conv2d(960, 960, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=960, bias=False)\n", + " (1): BatchNorm2d(960, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " (2): Hardswish()\n", + " )\n", + " (2): SqueezeExcitation(\n", + " (avgpool): AdaptiveAvgPool2d(output_size=1)\n", + " (fc1): Conv2d(960, 240, kernel_size=(1, 1), stride=(1, 1))\n", + " (fc2): Conv2d(240, 960, kernel_size=(1, 1), stride=(1, 1))\n", + " (activation): ReLU()\n", + " (scale_activation): Hardsigmoid()\n", + " )\n", + " (3): ConvNormActivation(\n", + " (0): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(160, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " )\n", + " (15): InvertedResidual(\n", + " (block): Sequential(\n", + " (0): ConvNormActivation(\n", + " (0): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(960, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " (2): Hardswish()\n", + " )\n", + " (1): ConvNormActivation(\n", + " (0): Conv2d(960, 960, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=960, bias=False)\n", + " (1): BatchNorm2d(960, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " (2): Hardswish()\n", + " )\n", + " (2): SqueezeExcitation(\n", + " (avgpool): AdaptiveAvgPool2d(output_size=1)\n", + " (fc1): Conv2d(960, 240, kernel_size=(1, 1), stride=(1, 1))\n", + " (fc2): Conv2d(240, 960, kernel_size=(1, 1), stride=(1, 1))\n", + " (activation): ReLU()\n", + " (scale_activation): Hardsigmoid()\n", + " )\n", + " (3): ConvNormActivation(\n", + " (0): Conv2d(960, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(160, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " )\n", + " (16): ConvNormActivation(\n", + " (0): Conv2d(160, 960, kernel_size=(1, 1), stride=(1, 1), bias=False)\n", + " (1): BatchNorm2d(960, eps=0.001, momentum=0.01, affine=True, track_running_stats=True)\n", + " (2): Hardswish()\n", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=1)\n", + " (classifier): Sequential(\n", + " (0): Linear(in_features=960, out_features=1280, bias=True)\n", + " (1): Hardswish()\n", + " (2): Dropout(p=0.2, inplace=True)\n", + " (3): Linear(in_features=1280, out_features=1000, bias=True)\n", + " )\n", + ")" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#using a pretrained model\n", + "sample_model = models.mobilenet_v3_large(pretrained=True)\n", + "\n", + "#evaluating to get rid of randomization like dropout and batch-normalization\n", + "sample_model.eval()" + ] + }, + { + "cell_type": "markdown", + "id": "4a9a2570", + "metadata": {}, + "source": [ + "### Load Input Image" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "7c737c0e", + "metadata": {}, + "outputs": [], + "source": [ + "image_path = \"pytorch_example_images/a/img2.jpeg\"\n", + "input_image = Image.open(image_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7f19ad41", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(input_image)" + ] + }, + { + "cell_type": "markdown", + "id": "2eecfe55", + "metadata": {}, + "source": [ + "### load output classes for IMAGENET dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2b602704", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data type before reconstruction : \n", + "Data type after reconstruction : \n", + "{0: 'tench, Tinca tinca', 1: 'goldfish, Carassius auratus', 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', 3: 'tiger shark, Galeocerdo cuvieri', 4: 'hammerhead, hammerhead shark', 5: 'electric ray, crampfish, numbfish, torpedo', 6: 'stingray', 7: 'cock', 8: 'hen', 9: 'ostrich, Struthio camelus', 10: 'brambling, Fringilla montifringilla', 11: 'goldfinch, Carduelis carduelis', 12: 'house finch, linnet, Carpodacus mexicanus', 13: 'junco, snowbird', 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea', 15: 'robin, American robin, Turdus migratorius', 16: 'bulbul', 17: 'jay', 18: 'magpie', 19: 'chickadee', 20: 'water ouzel, dipper', 21: 'kite', 22: 'bald eagle, American eagle, Haliaeetus leucocephalus', 23: 'vulture', 24: 'great grey owl, great gray owl, Strix nebulosa', 25: 'European fire salamander, Salamandra salamandra', 26: 'common newt, Triturus vulgaris', 27: 'eft', 28: 'spotted salamander, Ambystoma maculatum', 29: 'axolotl, mud puppy, Ambystoma mexicanum', 30: 'bullfrog, Rana catesbeiana', 31: 'tree frog, tree-frog', 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui', 33: 'loggerhead, loggerhead turtle, Caretta caretta', 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea', 35: 'mud turtle', 36: 'terrapin', 37: 'box turtle, box tortoise', 38: 'banded gecko', 39: 'common iguana, iguana, Iguana iguana', 40: 'American chameleon, anole, Anolis carolinensis', 41: 'whiptail, whiptail lizard', 42: 'agama', 43: 'frilled lizard, Chlamydosaurus kingi', 44: 'alligator lizard', 45: 'Gila monster, Heloderma suspectum', 46: 'green lizard, Lacerta viridis', 47: 'African chameleon, Chamaeleo chamaeleon', 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis', 49: 'African crocodile, Nile crocodile, Crocodylus niloticus', 50: 'American alligator, Alligator mississipiensis', 51: 'triceratops', 52: 'thunder snake, worm snake, Carphophis amoenus', 53: 'ringneck snake, ring-necked snake, ring snake', 54: 'hognose snake, puff adder, sand viper', 55: 'green snake, grass snake', 56: 'king snake, kingsnake', 57: 'garter snake, grass snake', 58: 'water snake', 59: 'vine snake', 60: 'night snake, Hypsiglena torquata', 61: 'boa constrictor, Constrictor constrictor', 62: 'rock python, rock snake, Python sebae', 63: 'Indian cobra, Naja naja', 64: 'green mamba', 65: 'sea snake', 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus', 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus', 68: 'sidewinder, horned rattlesnake, Crotalus cerastes', 69: 'trilobite', 70: 'harvestman, daddy longlegs, Phalangium opilio', 71: 'scorpion', 72: 'black and gold garden spider, Argiope aurantia', 73: 'barn spider, Araneus cavaticus', 74: 'garden spider, Aranea diademata', 75: 'black widow, Latrodectus mactans', 76: 'tarantula', 77: 'wolf spider, hunting spider', 78: 'tick', 79: 'centipede', 80: 'black grouse', 81: 'ptarmigan', 82: 'ruffed grouse, partridge, Bonasa umbellus', 83: 'prairie chicken, prairie grouse, prairie fowl', 84: 'peacock', 85: 'quail', 86: 'partridge', 87: 'African grey, African gray, Psittacus erithacus', 88: 'macaw', 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita', 90: 'lorikeet', 91: 'coucal', 92: 'bee eater', 93: 'hornbill', 94: 'hummingbird', 95: 'jacamar', 96: 'toucan', 97: 'drake', 98: 'red-breasted merganser, Mergus serrator', 99: 'goose', 100: 'black swan, Cygnus atratus', 101: 'tusker', 102: 'echidna, spiny anteater, anteater', 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus', 104: 'wallaby, brush kangaroo', 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus', 106: 'wombat', 107: 'jellyfish', 108: 'sea anemone, anemone', 109: 'brain coral', 110: 'flatworm, platyhelminth', 111: 'nematode, nematode worm, roundworm', 112: 'conch', 113: 'snail', 114: 'slug', 115: 'sea slug, nudibranch', 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore', 117: 'chambered nautilus, pearly nautilus, nautilus', 118: 'Dungeness crab, Cancer magister', 119: 'rock crab, Cancer irroratus', 120: 'fiddler crab', 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica', 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus', 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish', 124: 'crayfish, crawfish, crawdad, crawdaddy', 125: 'hermit crab', 126: 'isopod', 127: 'white stork, Ciconia ciconia', 128: 'black stork, Ciconia nigra', 129: 'spoonbill', 130: 'flamingo', 131: 'little blue heron, Egretta caerulea', 132: 'American egret, great white heron, Egretta albus', 133: 'bittern', 134: 'crane', 135: 'limpkin, Aramus pictus', 136: 'European gallinule, Porphyrio porphyrio', 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana', 138: 'bustard', 139: 'ruddy turnstone, Arenaria interpres', 140: 'red-backed sandpiper, dunlin, Erolia alpina', 141: 'redshank, Tringa totanus', 142: 'dowitcher', 143: 'oystercatcher, oyster catcher', 144: 'pelican', 145: 'king penguin, Aptenodytes patagonica', 146: 'albatross, mollymawk', 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus', 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca', 149: 'dugong, Dugong dugon', 150: 'sea lion', 151: 'Chihuahua', 152: 'Japanese spaniel', 153: 'Maltese dog, Maltese terrier, Maltese', 154: 'Pekinese, Pekingese, Peke', 155: 'Shih-Tzu', 156: 'Blenheim spaniel', 157: 'papillon', 158: 'toy terrier', 159: 'Rhodesian ridgeback', 160: 'Afghan hound, Afghan', 161: 'basset, basset hound', 162: 'beagle', 163: 'bloodhound, sleuthhound', 164: 'bluetick', 165: 'black-and-tan coonhound', 166: 'Walker hound, Walker foxhound', 167: 'English foxhound', 168: 'redbone', 169: 'borzoi, Russian wolfhound', 170: 'Irish wolfhound', 171: 'Italian greyhound', 172: 'whippet', 173: 'Ibizan hound, Ibizan Podenco', 174: 'Norwegian elkhound, elkhound', 175: 'otterhound, otter hound', 176: 'Saluki, gazelle hound', 177: 'Scottish deerhound, deerhound', 178: 'Weimaraner', 179: 'Staffordshire bullterrier, Staffordshire bull terrier', 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier', 181: 'Bedlington terrier', 182: 'Border terrier', 183: 'Kerry blue terrier', 184: 'Irish terrier', 185: 'Norfolk terrier', 186: 'Norwich terrier', 187: 'Yorkshire terrier', 188: 'wire-haired fox terrier', 189: 'Lakeland terrier', 190: 'Sealyham terrier, Sealyham', 191: 'Airedale, Airedale terrier', 192: 'cairn, cairn terrier', 193: 'Australian terrier', 194: 'Dandie Dinmont, Dandie Dinmont terrier', 195: 'Boston bull, Boston terrier', 196: 'miniature schnauzer', 197: 'giant schnauzer', 198: 'standard schnauzer', 199: 'Scotch terrier, Scottish terrier, Scottie', 200: 'Tibetan terrier, chrysanthemum dog', 201: 'silky terrier, Sydney silky', 202: 'soft-coated wheaten terrier', 203: 'West Highland white terrier', 204: 'Lhasa, Lhasa apso', 205: 'flat-coated retriever', 206: 'curly-coated retriever', 207: 'golden retriever', 208: 'Labrador retriever', 209: 'Chesapeake Bay retriever', 210: 'German short-haired pointer', 211: 'vizsla, Hungarian pointer', 212: 'English setter', 213: 'Irish setter, red setter', 214: 'Gordon setter', 215: 'Brittany spaniel', 216: 'clumber, clumber spaniel', 217: 'English springer, English springer spaniel', 218: 'Welsh springer spaniel', 219: 'cocker spaniel, English cocker spaniel, cocker', 220: 'Sussex spaniel', 221: 'Irish water spaniel', 222: 'kuvasz', 223: 'schipperke', 224: 'groenendael', 225: 'malinois', 226: 'briard', 227: 'kelpie', 228: 'komondor', 229: 'Old English sheepdog, bobtail', 230: 'Shetland sheepdog, Shetland sheep dog, Shetland', 231: 'collie', 232: 'Border collie', 233: 'Bouvier des Flandres, Bouviers des Flandres', 234: 'Rottweiler', 235: 'German shepherd, German shepherd dog, German police dog, alsatian', 236: 'Doberman, Doberman pinscher', 237: 'miniature pinscher', 238: 'Greater Swiss Mountain dog', 239: 'Bernese mountain dog', 240: 'Appenzeller', 241: 'EntleBucher', 242: 'boxer', 243: 'bull mastiff', 244: 'Tibetan mastiff', 245: 'French bulldog', 246: 'Great Dane', 247: 'Saint Bernard, St Bernard', 248: 'Eskimo dog, husky', 249: 'malamute, malemute, Alaskan malamute', 250: 'Siberian husky', 251: 'dalmatian, coach dog, carriage dog', 252: 'affenpinscher, monkey pinscher, monkey dog', 253: 'basenji', 254: 'pug, pug-dog', 255: 'Leonberg', 256: 'Newfoundland, Newfoundland dog', 257: 'Great Pyrenees', 258: 'Samoyed, Samoyede', 259: 'Pomeranian', 260: 'chow, chow chow', 261: 'keeshond', 262: 'Brabancon griffon', 263: 'Pembroke, Pembroke Welsh corgi', 264: 'Cardigan, Cardigan Welsh corgi', 265: 'toy poodle', 266: 'miniature poodle', 267: 'standard poodle', 268: 'Mexican hairless', 269: 'timber wolf, grey wolf, gray wolf, Canis lupus', 270: 'white wolf, Arctic wolf, Canis lupus tundrarum', 271: 'red wolf, maned wolf, Canis rufus, Canis niger', 272: 'coyote, prairie wolf, brush wolf, Canis latrans', 273: 'dingo, warrigal, warragal, Canis dingo', 274: 'dhole, Cuon alpinus', 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus', 276: 'hyena, hyaena', 277: 'red fox, Vulpes vulpes', 278: 'kit fox, Vulpes macrotis', 279: 'Arctic fox, white fox, Alopex lagopus', 280: 'grey fox, gray fox, Urocyon cinereoargenteus', 281: 'tabby, tabby cat', 282: 'tiger cat', 283: 'Persian cat', 284: 'Siamese cat, Siamese', 285: 'Egyptian cat', 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor', 287: 'lynx, catamount', 288: 'leopard, Panthera pardus', 289: 'snow leopard, ounce, Panthera uncia', 290: 'jaguar, panther, Panthera onca, Felis onca', 291: 'lion, king of beasts, Panthera leo', 292: 'tiger, Panthera tigris', 293: 'cheetah, chetah, Acinonyx jubatus', 294: 'brown bear, bruin, Ursus arctos', 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus', 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus', 297: 'sloth bear, Melursus ursinus, Ursus ursinus', 298: 'mongoose', 299: 'meerkat, mierkat', 300: 'tiger beetle', 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle', 302: 'ground beetle, carabid beetle', 303: 'long-horned beetle, longicorn, longicorn beetle', 304: 'leaf beetle, chrysomelid', 305: 'dung beetle', 306: 'rhinoceros beetle', 307: 'weevil', 308: 'fly', 309: 'bee', 310: 'ant, emmet, pismire', 311: 'grasshopper, hopper', 312: 'cricket', 313: 'walking stick, walkingstick, stick insect', 314: 'cockroach, roach', 315: 'mantis, mantid', 316: 'cicada, cicala', 317: 'leafhopper', 318: 'lacewing, lacewing fly', 319: \"dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk\", 320: 'damselfly', 321: 'admiral', 322: 'ringlet, ringlet butterfly', 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus', 324: 'cabbage butterfly', 325: 'sulphur butterfly, sulfur butterfly', 326: 'lycaenid, lycaenid butterfly', 327: 'starfish, sea star', 328: 'sea urchin', 329: 'sea cucumber, holothurian', 330: 'wood rabbit, cottontail, cottontail rabbit', 331: 'hare', 332: 'Angora, Angora rabbit', 333: 'hamster', 334: 'porcupine, hedgehog', 335: 'fox squirrel, eastern fox squirrel, Sciurus niger', 336: 'marmot', 337: 'beaver', 338: 'guinea pig, Cavia cobaya', 339: 'sorrel', 340: 'zebra', 341: 'hog, pig, grunter, squealer, Sus scrofa', 342: 'wild boar, boar, Sus scrofa', 343: 'warthog', 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius', 345: 'ox', 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis', 347: 'bison', 348: 'ram, tup', 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis', 350: 'ibex, Capra ibex', 351: 'hartebeest', 352: 'impala, Aepyceros melampus', 353: 'gazelle', 354: 'Arabian camel, dromedary, Camelus dromedarius', 355: 'llama', 356: 'weasel', 357: 'mink', 358: 'polecat, fitch, foulmart, foumart, Mustela putorius', 359: 'black-footed ferret, ferret, Mustela nigripes', 360: 'otter', 361: 'skunk, polecat, wood pussy', 362: 'badger', 363: 'armadillo', 364: 'three-toed sloth, ai, Bradypus tridactylus', 365: 'orangutan, orang, orangutang, Pongo pygmaeus', 366: 'gorilla, Gorilla gorilla', 367: 'chimpanzee, chimp, Pan troglodytes', 368: 'gibbon, Hylobates lar', 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus', 370: 'guenon, guenon monkey', 371: 'patas, hussar monkey, Erythrocebus patas', 372: 'baboon', 373: 'macaque', 374: 'langur', 375: 'colobus, colobus monkey', 376: 'proboscis monkey, Nasalis larvatus', 377: 'marmoset', 378: 'capuchin, ringtail, Cebus capucinus', 379: 'howler monkey, howler', 380: 'titi, titi monkey', 381: 'spider monkey, Ateles geoffroyi', 382: 'squirrel monkey, Saimiri sciureus', 383: 'Madagascar cat, ring-tailed lemur, Lemur catta', 384: 'indri, indris, Indri indri, Indri brevicaudatus', 385: 'Indian elephant, Elephas maximus', 386: 'African elephant, Loxodonta africana', 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens', 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca', 389: 'barracouta, snoek', 390: 'eel', 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch', 392: 'rock beauty, Holocanthus tricolor', 393: 'anemone fish', 394: 'sturgeon', 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus', 396: 'lionfish', 397: 'puffer, pufferfish, blowfish, globefish', 398: 'abacus', 399: 'abaya', 400: \"academic gown, academic robe, judge's robe\", 401: 'accordion, piano accordion, squeeze box', 402: 'acoustic guitar', 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier', 404: 'airliner', 405: 'airship, dirigible', 406: 'altar', 407: 'ambulance', 408: 'amphibian, amphibious vehicle', 409: 'analog clock', 410: 'apiary, bee house', 411: 'apron', 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin', 413: 'assault rifle, assault gun', 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack', 415: 'bakery, bakeshop, bakehouse', 416: 'balance beam, beam', 417: 'balloon', 418: 'ballpoint, ballpoint pen, ballpen, Biro', 419: 'Band Aid', 420: 'banjo', 421: 'bannister, banister, balustrade, balusters, handrail', 422: 'barbell', 423: 'barber chair', 424: 'barbershop', 425: 'barn', 426: 'barometer', 427: 'barrel, cask', 428: 'barrow, garden cart, lawn cart, wheelbarrow', 429: 'baseball', 430: 'basketball', 431: 'bassinet', 432: 'bassoon', 433: 'bathing cap, swimming cap', 434: 'bath towel', 435: 'bathtub, bathing tub, bath, tub', 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon', 437: 'beacon, lighthouse, beacon light, pharos', 438: 'beaker', 439: 'bearskin, busby, shako', 440: 'beer bottle', 441: 'beer glass', 442: 'bell cote, bell cot', 443: 'bib', 444: 'bicycle-built-for-two, tandem bicycle, tandem', 445: 'bikini, two-piece', 446: 'binder, ring-binder', 447: 'binoculars, field glasses, opera glasses', 448: 'birdhouse', 449: 'boathouse', 450: 'bobsled, bobsleigh, bob', 451: 'bolo tie, bolo, bola tie, bola', 452: 'bonnet, poke bonnet', 453: 'bookcase', 454: 'bookshop, bookstore, bookstall', 455: 'bottlecap', 456: 'bow', 457: 'bow tie, bow-tie, bowtie', 458: 'brass, memorial tablet, plaque', 459: 'brassiere, bra, bandeau', 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty', 461: 'breastplate, aegis, egis', 462: 'broom', 463: 'bucket, pail', 464: 'buckle', 465: 'bulletproof vest', 466: 'bullet train, bullet', 467: 'butcher shop, meat market', 468: 'cab, hack, taxi, taxicab', 469: 'caldron, cauldron', 470: 'candle, taper, wax light', 471: 'cannon', 472: 'canoe', 473: 'can opener, tin opener', 474: 'cardigan', 475: 'car mirror', 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig', 477: \"carpenter's kit, tool kit\", 478: 'carton', 479: 'car wheel', 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM', 481: 'cassette', 482: 'cassette player', 483: 'castle', 484: 'catamaran', 485: 'CD player', 486: 'cello, violoncello', 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone', 488: 'chain', 489: 'chainlink fence', 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour', 491: 'chain saw, chainsaw', 492: 'chest', 493: 'chiffonier, commode', 494: 'chime, bell, gong', 495: 'china cabinet, china closet', 496: 'Christmas stocking', 497: 'church, church building', 498: 'cinema, movie theater, movie theatre, movie house, picture palace', 499: 'cleaver, meat cleaver, chopper', 500: 'cliff dwelling', 501: 'cloak', 502: 'clog, geta, patten, sabot', 503: 'cocktail shaker', 504: 'coffee mug', 505: 'coffeepot', 506: 'coil, spiral, volute, whorl, helix', 507: 'combination lock', 508: 'computer keyboard, keypad', 509: 'confectionery, confectionary, candy store', 510: 'container ship, containership, container vessel', 511: 'convertible', 512: 'corkscrew, bottle screw', 513: 'cornet, horn, trumpet, trump', 514: 'cowboy boot', 515: 'cowboy hat, ten-gallon hat', 516: 'cradle', 517: 'crane', 518: 'crash helmet', 519: 'crate', 520: 'crib, cot', 521: 'Crock Pot', 522: 'croquet ball', 523: 'crutch', 524: 'cuirass', 525: 'dam, dike, dyke', 526: 'desk', 527: 'desktop computer', 528: 'dial telephone, dial phone', 529: 'diaper, nappy, napkin', 530: 'digital clock', 531: 'digital watch', 532: 'dining table, board', 533: 'dishrag, dishcloth', 534: 'dishwasher, dish washer, dishwashing machine', 535: 'disk brake, disc brake', 536: 'dock, dockage, docking facility', 537: 'dogsled, dog sled, dog sleigh', 538: 'dome', 539: 'doormat, welcome mat', 540: 'drilling platform, offshore rig', 541: 'drum, membranophone, tympan', 542: 'drumstick', 543: 'dumbbell', 544: 'Dutch oven', 545: 'electric fan, blower', 546: 'electric guitar', 547: 'electric locomotive', 548: 'entertainment center', 549: 'envelope', 550: 'espresso maker', 551: 'face powder', 552: 'feather boa, boa', 553: 'file, file cabinet, filing cabinet', 554: 'fireboat', 555: 'fire engine, fire truck', 556: 'fire screen, fireguard', 557: 'flagpole, flagstaff', 558: 'flute, transverse flute', 559: 'folding chair', 560: 'football helmet', 561: 'forklift', 562: 'fountain', 563: 'fountain pen', 564: 'four-poster', 565: 'freight car', 566: 'French horn, horn', 567: 'frying pan, frypan, skillet', 568: 'fur coat', 569: 'garbage truck, dustcart', 570: 'gasmask, respirator, gas helmet', 571: 'gas pump, gasoline pump, petrol pump, island dispenser', 572: 'goblet', 573: 'go-kart', 574: 'golf ball', 575: 'golfcart, golf cart', 576: 'gondola', 577: 'gong, tam-tam', 578: 'gown', 579: 'grand piano, grand', 580: 'greenhouse, nursery, glasshouse', 581: 'grille, radiator grille', 582: 'grocery store, grocery, food market, market', 583: 'guillotine', 584: 'hair slide', 585: 'hair spray', 586: 'half track', 587: 'hammer', 588: 'hamper', 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier', 590: 'hand-held computer, hand-held microcomputer', 591: 'handkerchief, hankie, hanky, hankey', 592: 'hard disc, hard disk, fixed disk', 593: 'harmonica, mouth organ, harp, mouth harp', 594: 'harp', 595: 'harvester, reaper', 596: 'hatchet', 597: 'holster', 598: 'home theater, home theatre', 599: 'honeycomb', 600: 'hook, claw', 601: 'hoopskirt, crinoline', 602: 'horizontal bar, high bar', 603: 'horse cart, horse-cart', 604: 'hourglass', 605: 'iPod', 606: 'iron, smoothing iron', 607: \"jack-o'-lantern\", 608: 'jean, blue jean, denim', 609: 'jeep, landrover', 610: 'jersey, T-shirt, tee shirt', 611: 'jigsaw puzzle', 612: 'jinrikisha, ricksha, rickshaw', 613: 'joystick', 614: 'kimono', 615: 'knee pad', 616: 'knot', 617: 'lab coat, laboratory coat', 618: 'ladle', 619: 'lampshade, lamp shade', 620: 'laptop, laptop computer', 621: 'lawn mower, mower', 622: 'lens cap, lens cover', 623: 'letter opener, paper knife, paperknife', 624: 'library', 625: 'lifeboat', 626: 'lighter, light, igniter, ignitor', 627: 'limousine, limo', 628: 'liner, ocean liner', 629: 'lipstick, lip rouge', 630: 'Loafer', 631: 'lotion', 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system', 633: \"loupe, jeweler's loupe\", 634: 'lumbermill, sawmill', 635: 'magnetic compass', 636: 'mailbag, postbag', 637: 'mailbox, letter box', 638: 'maillot', 639: 'maillot, tank suit', 640: 'manhole cover', 641: 'maraca', 642: 'marimba, xylophone', 643: 'mask', 644: 'matchstick', 645: 'maypole', 646: 'maze, labyrinth', 647: 'measuring cup', 648: 'medicine chest, medicine cabinet', 649: 'megalith, megalithic structure', 650: 'microphone, mike', 651: 'microwave, microwave oven', 652: 'military uniform', 653: 'milk can', 654: 'minibus', 655: 'miniskirt, mini', 656: 'minivan', 657: 'missile', 658: 'mitten', 659: 'mixing bowl', 660: 'mobile home, manufactured home', 661: 'Model T', 662: 'modem', 663: 'monastery', 664: 'monitor', 665: 'moped', 666: 'mortar', 667: 'mortarboard', 668: 'mosque', 669: 'mosquito net', 670: 'motor scooter, scooter', 671: 'mountain bike, all-terrain bike, off-roader', 672: 'mountain tent', 673: 'mouse, computer mouse', 674: 'mousetrap', 675: 'moving van', 676: 'muzzle', 677: 'nail', 678: 'neck brace', 679: 'necklace', 680: 'nipple', 681: 'notebook, notebook computer', 682: 'obelisk', 683: 'oboe, hautboy, hautbois', 684: 'ocarina, sweet potato', 685: 'odometer, hodometer, mileometer, milometer', 686: 'oil filter', 687: 'organ, pipe organ', 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO', 689: 'overskirt', 690: 'oxcart', 691: 'oxygen mask', 692: 'packet', 693: 'paddle, boat paddle', 694: 'paddlewheel, paddle wheel', 695: 'padlock', 696: 'paintbrush', 697: \"pajama, pyjama, pj's, jammies\", 698: 'palace', 699: 'panpipe, pandean pipe, syrinx', 700: 'paper towel', 701: 'parachute, chute', 702: 'parallel bars, bars', 703: 'park bench', 704: 'parking meter', 705: 'passenger car, coach, carriage', 706: 'patio, terrace', 707: 'pay-phone, pay-station', 708: 'pedestal, plinth, footstall', 709: 'pencil box, pencil case', 710: 'pencil sharpener', 711: 'perfume, essence', 712: 'Petri dish', 713: 'photocopier', 714: 'pick, plectrum, plectron', 715: 'pickelhaube', 716: 'picket fence, paling', 717: 'pickup, pickup truck', 718: 'pier', 719: 'piggy bank, penny bank', 720: 'pill bottle', 721: 'pillow', 722: 'ping-pong ball', 723: 'pinwheel', 724: 'pirate, pirate ship', 725: 'pitcher, ewer', 726: \"plane, carpenter's plane, woodworking plane\", 727: 'planetarium', 728: 'plastic bag', 729: 'plate rack', 730: 'plow, plough', 731: \"plunger, plumber's helper\", 732: 'Polaroid camera, Polaroid Land camera', 733: 'pole', 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria', 735: 'poncho', 736: 'pool table, billiard table, snooker table', 737: 'pop bottle, soda bottle', 738: 'pot, flowerpot', 739: \"potter's wheel\", 740: 'power drill', 741: 'prayer rug, prayer mat', 742: 'printer', 743: 'prison, prison house', 744: 'projectile, missile', 745: 'projector', 746: 'puck, hockey puck', 747: 'punching bag, punch bag, punching ball, punchball', 748: 'purse', 749: 'quill, quill pen', 750: 'quilt, comforter, comfort, puff', 751: 'racer, race car, racing car', 752: 'racket, racquet', 753: 'radiator', 754: 'radio, wireless', 755: 'radio telescope, radio reflector', 756: 'rain barrel', 757: 'recreational vehicle, RV, R.V.', 758: 'reel', 759: 'reflex camera', 760: 'refrigerator, icebox', 761: 'remote control, remote', 762: 'restaurant, eating house, eating place, eatery', 763: 'revolver, six-gun, six-shooter', 764: 'rifle', 765: 'rocking chair, rocker', 766: 'rotisserie', 767: 'rubber eraser, rubber, pencil eraser', 768: 'rugby ball', 769: 'rule, ruler', 770: 'running shoe', 771: 'safe', 772: 'safety pin', 773: 'saltshaker, salt shaker', 774: 'sandal', 775: 'sarong', 776: 'sax, saxophone', 777: 'scabbard', 778: 'scale, weighing machine', 779: 'school bus', 780: 'schooner', 781: 'scoreboard', 782: 'screen, CRT screen', 783: 'screw', 784: 'screwdriver', 785: 'seat belt, seatbelt', 786: 'sewing machine', 787: 'shield, buckler', 788: 'shoe shop, shoe-shop, shoe store', 789: 'shoji', 790: 'shopping basket', 791: 'shopping cart', 792: 'shovel', 793: 'shower cap', 794: 'shower curtain', 795: 'ski', 796: 'ski mask', 797: 'sleeping bag', 798: 'slide rule, slipstick', 799: 'sliding door', 800: 'slot, one-armed bandit', 801: 'snorkel', 802: 'snowmobile', 803: 'snowplow, snowplough', 804: 'soap dispenser', 805: 'soccer ball', 806: 'sock', 807: 'solar dish, solar collector, solar furnace', 808: 'sombrero', 809: 'soup bowl', 810: 'space bar', 811: 'space heater', 812: 'space shuttle', 813: 'spatula', 814: 'speedboat', 815: \"spider web, spider's web\", 816: 'spindle', 817: 'sports car, sport car', 818: 'spotlight, spot', 819: 'stage', 820: 'steam locomotive', 821: 'steel arch bridge', 822: 'steel drum', 823: 'stethoscope', 824: 'stole', 825: 'stone wall', 826: 'stopwatch, stop watch', 827: 'stove', 828: 'strainer', 829: 'streetcar, tram, tramcar, trolley, trolley car', 830: 'stretcher', 831: 'studio couch, day bed', 832: 'stupa, tope', 833: 'submarine, pigboat, sub, U-boat', 834: 'suit, suit of clothes', 835: 'sundial', 836: 'sunglass', 837: 'sunglasses, dark glasses, shades', 838: 'sunscreen, sunblock, sun blocker', 839: 'suspension bridge', 840: 'swab, swob, mop', 841: 'sweatshirt', 842: 'swimming trunks, bathing trunks', 843: 'swing', 844: 'switch, electric switch, electrical switch', 845: 'syringe', 846: 'table lamp', 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle', 848: 'tape player', 849: 'teapot', 850: 'teddy, teddy bear', 851: 'television, television system', 852: 'tennis ball', 853: 'thatch, thatched roof', 854: 'theater curtain, theatre curtain', 855: 'thimble', 856: 'thresher, thrasher, threshing machine', 857: 'throne', 858: 'tile roof', 859: 'toaster', 860: 'tobacco shop, tobacconist shop, tobacconist', 861: 'toilet seat', 862: 'torch', 863: 'totem pole', 864: 'tow truck, tow car, wrecker', 865: 'toyshop', 866: 'tractor', 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi', 868: 'tray', 869: 'trench coat', 870: 'tricycle, trike, velocipede', 871: 'trimaran', 872: 'tripod', 873: 'triumphal arch', 874: 'trolleybus, trolley coach, trackless trolley', 875: 'trombone', 876: 'tub, vat', 877: 'turnstile', 878: 'typewriter keyboard', 879: 'umbrella', 880: 'unicycle, monocycle', 881: 'upright, upright piano', 882: 'vacuum, vacuum cleaner', 883: 'vase', 884: 'vault', 885: 'velvet', 886: 'vending machine', 887: 'vestment', 888: 'viaduct', 889: 'violin, fiddle', 890: 'volleyball', 891: 'waffle iron', 892: 'wall clock', 893: 'wallet, billfold, notecase, pocketbook', 894: 'wardrobe, closet, press', 895: 'warplane, military plane', 896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin', 897: 'washer, automatic washer, washing machine', 898: 'water bottle', 899: 'water jug', 900: 'water tower', 901: 'whiskey jug', 902: 'whistle', 903: 'wig', 904: 'window screen', 905: 'window shade', 906: 'Windsor tie', 907: 'wine bottle', 908: 'wing', 909: 'wok', 910: 'wooden spoon', 911: 'wool, woolen, woollen', 912: 'worm fence, snake fence, snake-rail fence, Virginia fence', 913: 'wreck', 914: 'yawl', 915: 'yurt', 916: 'web site, website, internet site, site', 917: 'comic book', 918: 'crossword puzzle, crossword', 919: 'street sign', 920: 'traffic light, traffic signal, stoplight', 921: 'book jacket, dust cover, dust jacket, dust wrapper', 922: 'menu', 923: 'plate', 924: 'guacamole', 925: 'consomme', 926: 'hot pot, hotpot', 927: 'trifle', 928: 'ice cream, icecream', 929: 'ice lolly, lolly, lollipop, popsicle', 930: 'French loaf', 931: 'bagel, beigel', 932: 'pretzel', 933: 'cheeseburger', 934: 'hotdog, hot dog, red hot', 935: 'mashed potato', 936: 'head cabbage', 937: 'broccoli', 938: 'cauliflower', 939: 'zucchini, courgette', 940: 'spaghetti squash', 941: 'acorn squash', 942: 'butternut squash', 943: 'cucumber, cuke', 944: 'artichoke, globe artichoke', 945: 'bell pepper', 946: 'cardoon', 947: 'mushroom', 948: 'Granny Smith', 949: 'strawberry', 950: 'orange', 951: 'lemon', 952: 'fig', 953: 'pineapple, ananas', 954: 'banana', 955: 'jackfruit, jak, jack', 956: 'custard apple', 957: 'pomegranate', 958: 'hay', 959: 'carbonara', 960: 'chocolate sauce, chocolate syrup', 961: 'dough', 962: 'meat loaf, meatloaf', 963: 'pizza, pizza pie', 964: 'potpie', 965: 'burrito', 966: 'red wine', 967: 'espresso', 968: 'cup', 969: 'eggnog', 970: 'alp', 971: 'bubble', 972: 'cliff, drop, drop-off', 973: 'coral reef', 974: 'geyser', 975: 'lakeside, lakeshore', 976: 'promontory, headland, head, foreland', 977: 'sandbar, sand bar', 978: 'seashore, coast, seacoast, sea-coast', 979: 'valley, vale', 980: 'volcano', 981: 'ballplayer, baseball player', 982: 'groom, bridegroom', 983: 'scuba diver', 984: 'rapeseed', 985: 'daisy', 986: \"yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum\", 987: 'corn', 988: 'acorn', 989: 'hip, rose hip, rosehip', 990: 'buckeye, horse chestnut, conker', 991: 'coral fungus', 992: 'agaric', 993: 'gyromitra', 994: 'stinkhorn, carrion fungus', 995: 'earthstar', 996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa', 997: 'bolete', 998: 'ear, spike, capitulum', 999: 'toilet tissue, toilet paper, bathroom tissue'}\n" + ] + } + ], + "source": [ + "import ast\n", + " \n", + "# reading the data from the file\n", + "with open('imagenet_labels.txt') as f:\n", + " data = f.read()\n", + " \n", + "print(\"Data type before reconstruction : \", type(data))\n", + " \n", + "# reconstructing the data as a dictionary\n", + "d = ast.literal_eval(data)\n", + " \n", + "print(\"Data type after reconstruction : \", type(d))\n", + "print(d)" + ] + }, + { + "cell_type": "markdown", + "id": "01c264ee", + "metadata": {}, + "source": [ + "### Pass the input through PyTorch Model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "6c58a410", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ostrich, Struthio camelus\n" + ] + } + ], + "source": [ + "input = image_loader(data_transforms, input_image)\n", + "output = sample_model(input).detach().numpy()\n", + "op_label = np.argmax(output)\n", + "print(d[op_label])" + ] + }, + { + "cell_type": "markdown", + "id": "f4fce2eb", + "metadata": {}, + "source": [ + "### Convert PyTorch model to MDF " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b3ff558c", + "metadata": {}, + "outputs": [], + "source": [ + "mdf_model, params_dict = pytorch_to_mdf(\n", + " model=sample_model,\n", + " args=input,\n", + " trace=True,\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "ceaf21d1", + "metadata": {}, + "source": [ + "### Passing Input through MDF model" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "9e5a64c6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Init graph: MobileNetV3Graph\n", + "Evaluating graph: MobileNetV3Graph, root nodes: ['Conv_499'], with array format numpy\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-08-25 17:51:44.651614258 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.651802632 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.701413169 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.701671172 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.730354094 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.730523280 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.740933480 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.741094115 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.766339941 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.766513121 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.776602206 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.776768578 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.870742273 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.870906480 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ostrich, Struthio camelus\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-08-25 17:51:44.883193138 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.883402491 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.916159194 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.916344508 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.927277478 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.927451336 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.954815124 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.954988150 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.965684644 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.965842329 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.986696651 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.986865151 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:44.997954628 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:44.998119412 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:45.021505342 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:45.021676578 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:45.032329493 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 6 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:45.032496308 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n", + "2022-08-25 17:51:45.048474447 [W:onnxruntime:, model.cc:180 Model] ONNX Runtime only *guarantees* support for models stamped with opset version 7 or above for opset domain 'ai.onnx'. Please upgrade your model to opset 7 or higher. For now, this opset 1 model may run depending upon legacy support of some older opset version operators.\n", + "2022-08-25 17:51:45.048635883 [W:onnxruntime:, ort_transpose_optimizer.cc:24 ApplyImpl] Transpose optimizer failed: Unsupported ONNX opset\n" + ] + } + ], + "source": [ + "mdf_graph = mdf_model.graphs[0]\n", + "# mdf_graph_nodes = mdf_graph.nodes[id='Conv_499']\n", + "params_dict[\"input1\"] = input.detach().numpy()\n", + "\n", + "eg = EvaluableGraph(graph=mdf_graph, verbose=False)\n", + "\n", + "eg.evaluate(initializer=params_dict)\n", + "\n", + "output_mdf = eg.output_enodes[0].get_output()\n", + "op_label_mdf = np.argmax(output_mdf)\n", + "print(d[op_label_mdf])" + ] + }, + { + "cell_type": "markdown", + "id": "880397fc", + "metadata": {}, + "source": [ + "### MDF Graph" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "c92ab703", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Converting MDF graph: MobileNetV3Graph to graphviz (level: 1, format: png)\n", + " Node: Conv_499\n", + " Node: HardSwish_315\n", + " Node: Conv_502\n", + " Node: Relu_318\n", + " Node: Conv_505\n", + " Node: Add_321\n", + " Node: Conv_508\n", + " Node: Relu_324\n", + " Node: Conv_511\n", + " Node: Relu_327\n", + " Node: Conv_514\n", + " Node: Conv_517\n", + " Node: Relu_332\n", + " Node: Conv_520\n", + " Node: Relu_335\n", + " Node: Conv_523\n", + " Node: Add_338\n", + " Node: Conv_526\n", + " Node: Relu_341\n", + " Node: Conv_529\n", + " Node: Relu_344\n", + " Node: GlobalAveragePool_345\n", + " Node: Conv_346\n", + " Node: Relu_347\n", + " Node: Conv_348\n", + " Node: HardSigmoid_349\n", + " Node: Mul_350\n", + " Node: Conv_532\n", + " Node: Conv_535\n", + " Node: Relu_355\n", + " Node: Conv_538\n", + " Node: Relu_358\n", + " Node: GlobalAveragePool_359\n", + " Node: Conv_360\n", + " Node: Relu_361\n", + " Node: Conv_362\n", + " Node: HardSigmoid_363\n", + " Node: Mul_364\n", + " Node: Conv_541\n", + " Node: Add_367\n", + " Node: Conv_544\n", + " Node: Relu_370\n", + " Node: Conv_547\n", + " Node: Relu_373\n", + " Node: GlobalAveragePool_374\n", + " Node: Conv_375\n", + " Node: Relu_376\n", + " Node: Conv_377\n", + " Node: HardSigmoid_378\n", + " Node: Mul_379\n", + " Node: Conv_550\n", + " Node: Add_382\n", + " Node: Conv_553\n", + " Node: HardSwish_385\n", + " Node: Conv_556\n", + " Node: HardSwish_388\n", + " Node: Conv_559\n", + " Node: Conv_562\n", + " Node: HardSwish_393\n", + " Node: Conv_565\n", + " Node: HardSwish_396\n", + " Node: Conv_568\n", + " Node: Add_399\n", + " Node: Conv_571\n", + " Node: HardSwish_402\n", + " Node: Conv_574\n", + " Node: HardSwish_405\n", + " Node: Conv_577\n", + " Node: Add_408\n", + " Node: Conv_580\n", + " Node: HardSwish_411\n", + " Node: Conv_583\n", + " Node: HardSwish_414\n", + " Node: Conv_586\n", + " Node: Add_417\n", + " Node: Conv_589\n", + " Node: HardSwish_420\n", + " Node: Conv_592\n", + " Node: HardSwish_423\n", + " Node: GlobalAveragePool_424\n", + " Node: Conv_425\n", + " Node: Relu_426\n", + " Node: Conv_427\n", + " Node: HardSigmoid_428\n", + " Node: Mul_429\n", + " Node: Conv_595\n", + " Node: Conv_598\n", + " Node: HardSwish_434\n", + " Node: Conv_601\n", + " Node: HardSwish_437\n", + " Node: GlobalAveragePool_438\n", + " Node: Conv_439\n", + " Node: Relu_440\n", + " Node: Conv_441\n", + " Node: HardSigmoid_442\n", + " Node: Mul_443\n", + " Node: Conv_604\n", + " Node: Add_446\n", + " Node: Conv_607\n", + " Node: HardSwish_449\n", + " Node: Conv_610\n", + " Node: HardSwish_452\n", + " Node: GlobalAveragePool_453\n", + " Node: Conv_454\n", + " Node: Relu_455\n", + " Node: Conv_456\n", + " Node: HardSigmoid_457\n", + " Node: Mul_458\n", + " Node: Conv_613\n", + " Node: Conv_616\n", + " Node: HardSwish_463\n", + " Node: Conv_619\n", + " Node: HardSwish_466\n", + " Node: GlobalAveragePool_467\n", + " Node: Conv_468\n", + " Node: Relu_469\n", + " Node: Conv_470\n", + " Node: HardSigmoid_471\n", + " Node: Mul_472\n", + " Node: Conv_622\n", + " Node: Add_475\n", + " Node: Conv_625\n", + " Node: HardSwish_478\n", + " Node: Conv_628\n", + " Node: HardSwish_481\n", + " Node: GlobalAveragePool_482\n", + " Node: Conv_483\n", + " Node: Relu_484\n", + " Node: Conv_485\n", + " Node: HardSigmoid_486\n", + " Node: Mul_487\n", + " Node: Conv_631\n", + " Node: Add_490\n", + " Node: Conv_634\n", + " Node: HardSwish_493\n", + " Node: GlobalAveragePool_494\n", + " Node: Flatten_495\n", + " Node: Gemm_496\n", + " Node: HardSwish_497\n", + " Node: Gemm_498\n", + " Edge: Conv_499_HardSwish_315 connects Conv_499 to HardSwish_315\n", + " Edge: HardSwish_315_Conv_502 connects HardSwish_315 to Conv_502\n", + " Edge: HardSwish_315_Add_321 connects HardSwish_315 to Add_321\n", + " Edge: Conv_502_Relu_318 connects Conv_502 to Relu_318\n", + " Edge: Relu_318_Conv_505 connects Relu_318 to Conv_505\n", + " Edge: Conv_505_Add_321 connects Conv_505 to Add_321\n", + " Edge: Add_321_Conv_508 connects Add_321 to Conv_508\n", + " Edge: Conv_508_Relu_324 connects Conv_508 to Relu_324\n", + " Edge: Relu_324_Conv_511 connects Relu_324 to Conv_511\n", + " Edge: Conv_511_Relu_327 connects Conv_511 to Relu_327\n", + " Edge: Relu_327_Conv_514 connects Relu_327 to Conv_514\n", + " Edge: Conv_514_Conv_517 connects Conv_514 to Conv_517\n", + " Edge: Conv_514_Add_338 connects Conv_514 to Add_338\n", + " Edge: Conv_517_Relu_332 connects Conv_517 to Relu_332\n", + " Edge: Relu_332_Conv_520 connects Relu_332 to Conv_520\n", + " Edge: Conv_520_Relu_335 connects Conv_520 to Relu_335\n", + " Edge: Relu_335_Conv_523 connects Relu_335 to Conv_523\n", + " Edge: Conv_523_Add_338 connects Conv_523 to Add_338\n", + " Edge: Add_338_Conv_526 connects Add_338 to Conv_526\n", + " Edge: Conv_526_Relu_341 connects Conv_526 to Relu_341\n", + " Edge: Relu_341_Conv_529 connects Relu_341 to Conv_529\n", + " Edge: Conv_529_Relu_344 connects Conv_529 to Relu_344\n", + " Edge: Relu_344_GlobalAveragePool_345 connects Relu_344 to GlobalAveragePool_345\n", + " Edge: Relu_344_Mul_350 connects Relu_344 to Mul_350\n", + " Edge: GlobalAveragePool_345_Conv_346 connects GlobalAveragePool_345 to Conv_346\n", + " Edge: Conv_346_Relu_347 connects Conv_346 to Relu_347\n", + " Edge: Relu_347_Conv_348 connects Relu_347 to Conv_348\n", + " Edge: Conv_348_HardSigmoid_349 connects Conv_348 to HardSigmoid_349\n", + " Edge: HardSigmoid_349_Mul_350 connects HardSigmoid_349 to Mul_350\n", + " Edge: Mul_350_Conv_532 connects Mul_350 to Conv_532\n", + " Edge: Conv_532_Conv_535 connects Conv_532 to Conv_535\n", + " Edge: Conv_532_Add_367 connects Conv_532 to Add_367\n", + " Edge: Conv_535_Relu_355 connects Conv_535 to Relu_355\n", + " Edge: Relu_355_Conv_538 connects Relu_355 to Conv_538\n", + " Edge: Conv_538_Relu_358 connects Conv_538 to Relu_358\n", + " Edge: Relu_358_GlobalAveragePool_359 connects Relu_358 to GlobalAveragePool_359\n", + " Edge: Relu_358_Mul_364 connects Relu_358 to Mul_364\n", + " Edge: GlobalAveragePool_359_Conv_360 connects GlobalAveragePool_359 to Conv_360\n", + " Edge: Conv_360_Relu_361 connects Conv_360 to Relu_361\n", + " Edge: Relu_361_Conv_362 connects Relu_361 to Conv_362\n", + " Edge: Conv_362_HardSigmoid_363 connects Conv_362 to HardSigmoid_363\n", + " Edge: HardSigmoid_363_Mul_364 connects HardSigmoid_363 to Mul_364\n", + " Edge: Mul_364_Conv_541 connects Mul_364 to Conv_541\n", + " Edge: Conv_541_Add_367 connects Conv_541 to Add_367\n", + " Edge: Add_367_Conv_544 connects Add_367 to Conv_544\n", + " Edge: Add_367_Add_382 connects Add_367 to Add_382\n", + " Edge: Conv_544_Relu_370 connects Conv_544 to Relu_370\n", + " Edge: Relu_370_Conv_547 connects Relu_370 to Conv_547\n", + " Edge: Conv_547_Relu_373 connects Conv_547 to Relu_373\n", + " Edge: Relu_373_GlobalAveragePool_374 connects Relu_373 to GlobalAveragePool_374\n", + " Edge: Relu_373_Mul_379 connects Relu_373 to Mul_379\n", + " Edge: GlobalAveragePool_374_Conv_375 connects GlobalAveragePool_374 to Conv_375\n", + " Edge: Conv_375_Relu_376 connects Conv_375 to Relu_376\n", + " Edge: Relu_376_Conv_377 connects Relu_376 to Conv_377\n", + " Edge: Conv_377_HardSigmoid_378 connects Conv_377 to HardSigmoid_378\n", + " Edge: HardSigmoid_378_Mul_379 connects HardSigmoid_378 to Mul_379\n", + " Edge: Mul_379_Conv_550 connects Mul_379 to Conv_550\n", + " Edge: Conv_550_Add_382 connects Conv_550 to Add_382\n", + " Edge: Add_382_Conv_553 connects Add_382 to Conv_553\n", + " Edge: Conv_553_HardSwish_385 connects Conv_553 to HardSwish_385\n", + " Edge: HardSwish_385_Conv_556 connects HardSwish_385 to Conv_556\n", + " Edge: Conv_556_HardSwish_388 connects Conv_556 to HardSwish_388\n", + " Edge: HardSwish_388_Conv_559 connects HardSwish_388 to Conv_559\n", + " Edge: Conv_559_Conv_562 connects Conv_559 to Conv_562\n", + " Edge: Conv_559_Add_399 connects Conv_559 to Add_399\n", + " Edge: Conv_562_HardSwish_393 connects Conv_562 to HardSwish_393\n", + " Edge: HardSwish_393_Conv_565 connects HardSwish_393 to Conv_565\n", + " Edge: Conv_565_HardSwish_396 connects Conv_565 to HardSwish_396\n", + " Edge: HardSwish_396_Conv_568 connects HardSwish_396 to Conv_568\n", + " Edge: Conv_568_Add_399 connects Conv_568 to Add_399\n", + " Edge: Add_399_Conv_571 connects Add_399 to Conv_571\n", + " Edge: Add_399_Add_408 connects Add_399 to Add_408\n", + " Edge: Conv_571_HardSwish_402 connects Conv_571 to HardSwish_402\n", + " Edge: HardSwish_402_Conv_574 connects HardSwish_402 to Conv_574\n", + " Edge: Conv_574_HardSwish_405 connects Conv_574 to HardSwish_405\n", + " Edge: HardSwish_405_Conv_577 connects HardSwish_405 to Conv_577\n", + " Edge: Conv_577_Add_408 connects Conv_577 to Add_408\n", + " Edge: Add_408_Conv_580 connects Add_408 to Conv_580\n", + " Edge: Add_408_Add_417 connects Add_408 to Add_417\n", + " Edge: Conv_580_HardSwish_411 connects Conv_580 to HardSwish_411\n", + " Edge: HardSwish_411_Conv_583 connects HardSwish_411 to Conv_583\n", + " Edge: Conv_583_HardSwish_414 connects Conv_583 to HardSwish_414\n", + " Edge: HardSwish_414_Conv_586 connects HardSwish_414 to Conv_586\n", + " Edge: Conv_586_Add_417 connects Conv_586 to Add_417\n", + " Edge: Add_417_Conv_589 connects Add_417 to Conv_589\n", + " Edge: Conv_589_HardSwish_420 connects Conv_589 to HardSwish_420\n", + " Edge: HardSwish_420_Conv_592 connects HardSwish_420 to Conv_592\n", + " Edge: Conv_592_HardSwish_423 connects Conv_592 to HardSwish_423\n", + " Edge: HardSwish_423_GlobalAveragePool_424 connects HardSwish_423 to GlobalAveragePool_424\n", + " Edge: HardSwish_423_Mul_429 connects HardSwish_423 to Mul_429\n", + " Edge: GlobalAveragePool_424_Conv_425 connects GlobalAveragePool_424 to Conv_425\n", + " Edge: Conv_425_Relu_426 connects Conv_425 to Relu_426\n", + " Edge: Relu_426_Conv_427 connects Relu_426 to Conv_427\n", + " Edge: Conv_427_HardSigmoid_428 connects Conv_427 to HardSigmoid_428\n", + " Edge: HardSigmoid_428_Mul_429 connects HardSigmoid_428 to Mul_429\n", + " Edge: Mul_429_Conv_595 connects Mul_429 to Conv_595\n", + " Edge: Conv_595_Conv_598 connects Conv_595 to Conv_598\n", + " Edge: Conv_595_Add_446 connects Conv_595 to Add_446\n", + " Edge: Conv_598_HardSwish_434 connects Conv_598 to HardSwish_434\n", + " Edge: HardSwish_434_Conv_601 connects HardSwish_434 to Conv_601\n", + " Edge: Conv_601_HardSwish_437 connects Conv_601 to HardSwish_437\n", + " Edge: HardSwish_437_GlobalAveragePool_438 connects HardSwish_437 to GlobalAveragePool_438\n", + " Edge: HardSwish_437_Mul_443 connects HardSwish_437 to Mul_443\n", + " Edge: GlobalAveragePool_438_Conv_439 connects GlobalAveragePool_438 to Conv_439\n", + " Edge: Conv_439_Relu_440 connects Conv_439 to Relu_440\n", + " Edge: Relu_440_Conv_441 connects Relu_440 to Conv_441\n", + " Edge: Conv_441_HardSigmoid_442 connects Conv_441 to HardSigmoid_442\n", + " Edge: HardSigmoid_442_Mul_443 connects HardSigmoid_442 to Mul_443\n", + " Edge: Mul_443_Conv_604 connects Mul_443 to Conv_604\n", + " Edge: Conv_604_Add_446 connects Conv_604 to Add_446\n", + " Edge: Add_446_Conv_607 connects Add_446 to Conv_607\n", + " Edge: Conv_607_HardSwish_449 connects Conv_607 to HardSwish_449\n", + " Edge: HardSwish_449_Conv_610 connects HardSwish_449 to Conv_610\n", + " Edge: Conv_610_HardSwish_452 connects Conv_610 to HardSwish_452\n", + " Edge: HardSwish_452_GlobalAveragePool_453 connects HardSwish_452 to GlobalAveragePool_453\n", + " Edge: HardSwish_452_Mul_458 connects HardSwish_452 to Mul_458\n", + " Edge: GlobalAveragePool_453_Conv_454 connects GlobalAveragePool_453 to Conv_454\n", + " Edge: Conv_454_Relu_455 connects Conv_454 to Relu_455\n", + " Edge: Relu_455_Conv_456 connects Relu_455 to Conv_456\n", + " Edge: Conv_456_HardSigmoid_457 connects Conv_456 to HardSigmoid_457\n", + " Edge: HardSigmoid_457_Mul_458 connects HardSigmoid_457 to Mul_458\n", + " Edge: Mul_458_Conv_613 connects Mul_458 to Conv_613\n", + " Edge: Conv_613_Conv_616 connects Conv_613 to Conv_616\n", + " Edge: Conv_613_Add_475 connects Conv_613 to Add_475\n", + " Edge: Conv_616_HardSwish_463 connects Conv_616 to HardSwish_463\n", + " Edge: HardSwish_463_Conv_619 connects HardSwish_463 to Conv_619\n", + " Edge: Conv_619_HardSwish_466 connects Conv_619 to HardSwish_466\n", + " Edge: HardSwish_466_GlobalAveragePool_467 connects HardSwish_466 to GlobalAveragePool_467\n", + " Edge: HardSwish_466_Mul_472 connects HardSwish_466 to Mul_472\n", + " Edge: GlobalAveragePool_467_Conv_468 connects GlobalAveragePool_467 to Conv_468\n", + " Edge: Conv_468_Relu_469 connects Conv_468 to Relu_469\n", + " Edge: Relu_469_Conv_470 connects Relu_469 to Conv_470\n", + " Edge: Conv_470_HardSigmoid_471 connects Conv_470 to HardSigmoid_471\n", + " Edge: HardSigmoid_471_Mul_472 connects HardSigmoid_471 to Mul_472\n", + " Edge: Mul_472_Conv_622 connects Mul_472 to Conv_622\n", + " Edge: Conv_622_Add_475 connects Conv_622 to Add_475\n", + " Edge: Add_475_Conv_625 connects Add_475 to Conv_625\n", + " Edge: Add_475_Add_490 connects Add_475 to Add_490\n", + " Edge: Conv_625_HardSwish_478 connects Conv_625 to HardSwish_478\n", + " Edge: HardSwish_478_Conv_628 connects HardSwish_478 to Conv_628\n", + " Edge: Conv_628_HardSwish_481 connects Conv_628 to HardSwish_481\n", + " Edge: HardSwish_481_GlobalAveragePool_482 connects HardSwish_481 to GlobalAveragePool_482\n", + " Edge: HardSwish_481_Mul_487 connects HardSwish_481 to Mul_487\n", + " Edge: GlobalAveragePool_482_Conv_483 connects GlobalAveragePool_482 to Conv_483\n", + " Edge: Conv_483_Relu_484 connects Conv_483 to Relu_484\n", + " Edge: Relu_484_Conv_485 connects Relu_484 to Conv_485\n", + " Edge: Conv_485_HardSigmoid_486 connects Conv_485 to HardSigmoid_486\n", + " Edge: HardSigmoid_486_Mul_487 connects HardSigmoid_486 to Mul_487\n", + " Edge: Mul_487_Conv_631 connects Mul_487 to Conv_631\n", + " Edge: Conv_631_Add_490 connects Conv_631 to Add_490\n", + " Edge: Add_490_Conv_634 connects Add_490 to Conv_634\n", + " Edge: Conv_634_HardSwish_493 connects Conv_634 to HardSwish_493\n", + " Edge: HardSwish_493_GlobalAveragePool_494 connects HardSwish_493 to GlobalAveragePool_494\n", + " Edge: GlobalAveragePool_494_Flatten_495 connects GlobalAveragePool_494 to Flatten_495\n", + " Edge: Flatten_495_Gemm_496 connects Flatten_495 to Gemm_496\n", + " Edge: Gemm_496_HardSwish_497 connects Gemm_496 to HardSwish_497\n", + " Edge: HardSwish_497_Gemm_498 connects HardSwish_497 to Gemm_498\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Written graph image to: example.png\n" + ] + }, + { + "data": { + "image/png": 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6WlUGYx2N/psmabH/VlBQYGFh4eTk1POVjo6O27dvFxUVkZO2ioqKiouLu7u7f/rpJxMTk8mTJ2vy8l5Y5H297777ztLS0tfX9+233/bx8fH19R05cqQ6Trdr1y6Fjkc+aBL689AfxhVADbkB/Q3G3AAAAAAAAABFob5WlcFYR6P/pkm4rwd9YL0soIZ9JYB+kHtADbkH9IPcA2r+/v4SiUQoFPr4+Kjp6b4ewcHBir4E/SKNwb4eQEt4Dg0oIPeAlpB7QEGLuVdfX19ZWdl7o67u7u47d+70bNFF3iF68uSJWCwuLy+fOHHikydP1LqJLZD8/f1PnTpVW1vr6+s7b948ctoXg8FQx/3lJUuWKPoS5IPGYFwEtIRxEVBA7gEtIfeAAupB6A/1IJAwLgJawrgIKCD3gJaQe0AB9SD0h+fkgQL2iwRaQu4BBeQe0JK/v/8PP/wgEomMjY2tra3t7e2dnZ0nTpxI/oednZ29vb2jo+PAx94ODg4tLS3e3t5isfidd975888/J0yY8NxXoR4EkAl9S6CA9aNAJuQGUEBuAFBQeX4aGRl5eHh4eHj0/mJnZ+fff/9d1supU6dEIpGBgYGbm1vvI52cnFJTU3k8XmJi4uzZs4ODg7/66is2m43+gCahfwgU/Pz8jh07xufzg4ODnZ2d1Xor093dXdGXYHylMRhfAS2hrgQKyD2gpcGYewAAAAAAAKAQ9AdUaDDW0egfaox2+4e3bt3qPV2RIIiGhgZyq7ueSYvV1dUEQezYscPa2trCwkKTl/fCwrwMoID9cYCWkHtAAbkHtOTn57dr1y4Wi0UQhJWVFTk/kclkhoWF9cxYfPnllweeipaWlmZmZl988cXt27ddXV337t37wQcfGBoaUr8K9SCATHj+B6hhvTLoD7kB1JAbAM+i8vzU09NzcHBwcHB48803e3+9oaGBnKgoEonEYrFQKNy7d29zczNBEC4uLj2HDRs2LC4ubvHixXv27Nm0adPu3bu//PLLzz//HP0BTUL/ECiQ/cPo6OgpU6Z4eXmp9ePJ2Nh43LhxCr0E4ytNwvgK6Ad1JVBD7gH9DMbcAwAAAAAAAEWhP6Aqg7GORv9Qk7TYPywoKLCwsHBycur5SkdHx+3bt4uKishJi0VFRcXFxd3d3T/99JOJicnkyZM1eXkvLPK+6nfffWdpaenr6/v222/7+Pj4+vqOHDlSHafbtWuXQscjHzQJ9xeAfjAuAmrIPaCfwZh7AAAAAAAAoCj0B1RlMNbR6B9qEu6rQh9Y7w6oYX9eoB/kHgCd4HMKNADr/4AKYRwCtIScBBWSmZMGvY+4e/cuQRC9O4wKkUql//73vwsLC2trax89emRlZWVtbe3i4jJu3Dh/f//hw4cP4OLVbsWKFTdu3CD/+5dffjEzM+v5q0ePHp08eTI3N7eysrKzs9PKysrX15fD4TAYjN7vIOdh8iN/EHfv3mUymUp+V6p29+7d4OBghV5SV1c3b968/l8/d+7ckydPpk+f3v+vTpw4YW1treQlPtvNmze//PLLnj8uWrTovffeI/+7u7v73LlzAoGgvLz80aNHw4cPf+mllxgMRlBQUEBAQO9fBrU6ffp072kzCQkJEydOVOJ9urq6bt68eenSpaKiorq6utbWVjMzMycnpzfffHPatGlDhgzpc7xYLN6xY4dUKiUIIigoaNOmTX0OiImJKSsr638imQc/l5OTU35+vqKv0qTQ0FBbW9vExMSPPvro448/Dg8Px0011eru7hYIBPv37+/u7t68ebOXl5e2r0gB5FYrGzZsiI2NnTFjRlRUlMYigvZaW1v5fH5mZqa/v//q1asH1/9Y5Ia6aT03CgoKCIKoqKhISkoib7pLJJLW1laCIOzs7Ly8vAICAj744ANPT08vL6/PP/981qxZ/T9w5dfe3j579uz29vYpU6b0Hr3IRDHCUeKw3uQcUTx8+PDSpUvkGLiurq67u/ull17y9vaeOXOmzG7IcwceCtG1ccWLVk/JP0osLy8/ceLEzZs3Gxsbhw0b5u7uHhER0aeyaG9vP3369KVLlyorK9va2oyNjUeNGhUUFDRr1izlqgN611MEQQwdOtTOzm7ChAmRkZEKfW5euHBh48aNPX9Uuu6QSU3RQaIo2+WH3NAuhapLOT8yVPjJgtx4lkGUG3w+//Dhw8861+TJk+Pj4xW9QuSGdqkjN0iq+ljR19f39/fX2RuB6GNogFQq3b17d2Fh4YIFC+bMmaPty1GAgYHBipfkGb8AACAASURBVBUrxowZs3fv3pycnCVLlih9LwP60HofYyCQGxqA3ID+kBtATeu5UVBQMGbMmD179pDtcbFYfP/+fYIgzMzMyK54aGgo+R/nzp0rLi4eNWrUQE43uDrk8t+aR//zuWhZsSrUCO3u7v7999+zs7OLi4tbWlqsra2dnZ1DQ0Nff/11Y2Njha5NT0/P0dHx77//Vu5bU4e7d+86OjoqeguVrp2uPp7bo1BVCxS5oXWqzQ3VPqmI3KAwGHNDocMo9MmNzs7Ourq66urqsv919+7drq4ugiCMjIwcHBycnZ3t7OyYTCaXy3V2dnZ2dnZ0dKR+gsLR0bGxsbGpqam+vj4pKenAgQMODg47duxYsGCBgYEBxQtRjwD0ofX6UWnoO2kAns8EmZAbQAG5AUBBk/lpZWUVGBgYGBjI4XB6vrh3714ej+fo6NjnYHNz87i4uAULFiQnJ69du3b37t0sFmvMmDEK/RMoLi5esmRJ768EBAQkJyf3PzI2NlYikfT+yqFDh+Rfa0+Jilv+Olq1TzjLCf03rZPn567W55wpkP03a2vroKAgpb9BtcL4SgMwvgKZUJcBBeQGyDR4cwMAAAAAAAAUhfp64AZvHY3+mwZovf9WUFAwatSoI0eOkNO1RCJReXl5V1eXgYGBs7Mzk8lks9lMJtPT0/Pp06erVq16//33B3K6wTVdi/TcWTbqWF2EvK83derURYsWKfpazUA+aIDW82EgMH5QH4wrgAJyA2QavLkBAAAAAAAAikJ9PXCDt45G/00DtN5/w329ga+vqPLJegSN1svqQcvpnHIeptwaXNRosK8Edn2Vn+Z3fZVzaVnV7vqK3NM6FeYeSYXLzxLIPZVC7imde6pdeRu5p3WqzT3VLp9L/F/uTZ48WbmXawD6ReqGfT2AlrTeBxsI5J66IfeAlpB7QEHruVdQUEAQREVFRVJSEnmHSCKRtLa2EgRhZ2fn5eUVEBDwwQcfkBt1ff7557NmzVKum00adLeH5KzyVF4MEgTh5OQ0ZsyY3Nxcpd9B3ZAP6qb1fBgIjIvgWTAuAgrIPaAl5B5Q0HruvZj1YB/Umx7Ks6eDyndtJlAPgg7kw0BgXATPgnERUEDuAS0h94CC1nMP9SDxvHqQIAixWLxjxw6pVErIejxeHctCErR4Tr43uj5OLGcrQB2PExODf79IzKSQn6pmUvTxrPRTaFasajdCRe5pkQrnR6hjYjVyT7WQe4RSuafyKeFOTk6urq4XLlywsbEZ+HdHwcHBYciQIb6+vseOHfPx8ZH/hagHAXrTev0+EOhbagDWj4L+kBtADbkB8CyazE9DQ0NnZ2dnZ+feX+zs7JwxY4aFhUX/4728vNLT069du5aQkDBjxozQ0FB9ff1PP/1UoZMWFxcvWbKk91cCAgKSk5P7HxkbGyuRSHp/5dChQ/b29nKe6MKFCxs3buz5oxLF9cD7h6rtjaN/qF2qXV9FtauTEQTh5OSkr6/v7++vdAdS3TC+0gCMr4B+UFcCNeQe0M+gzj0AAAAAAABQCPoDAzeo62j0DzVA6/3DgoKCMWPG7Nmzh5yuKBaL79+/TxCEmZkZOUsxNDSU/I9z584VFxePGjVqIKcbpDMW5TlM5dv6EIN/XkZvg+7OOyH3z/S507VUPqeVHvvjYNqO/DQ8bUf+w1T+uBGB3NM2+T/LqOfyk1Q4mxW5p1rIPaJfoMnzjJzKp+I6OTlZW1tnZ2dPnDjRwMBAiXeQn4ODg7Gx8fHjx99//319fX05X4V6EKAPrdfvSkN/TwOwXhnIhNwACsgNAAqazE8rK6vAwMDAwEAOh9Pzxb179/J4PEdHxz4Hm5ubx8XFLViwIDk5ee3atbt372axWGPGjFHonwANpisSql7xT07oH+oCVfUPVb4qFNk/tLa2DgoKGuD3qCYYX2kAxldAS6grgQJyD2hp8OYeAAAAAAAAKAr9gYEbvHU0+ocaoPX+YUFBwahRo44cOUJOVxSJROXl5V1dXQYGBs7Ozkwmk81mM5lMT0/Pp0+frlq16v333x/I6QbXdEX5Z5mpfBlY8r7q1KlTFy1apMTLNQD5oAFaz4eBwPgBngXjIqCA3ANaGry5BwAAAAAAAIpCf2DgBm8djf6hBmi9f4j7qoSKFjlU4WJ3BF3Wu+uNltOZlZunLOfam9RosD8vlkOUn+aXQ5Qn+tQ0T59OuVdaWnr27Nme3DM3N7e0tLS1tfX19R03bhyDwdDT01N6OY49e/b88ssvPX/88ccfbW1tlbtOea5BoY/vwe5Z6UQQhImJiYODw5tvvvnuu+8aGhqq6oxqXZVFieWa8TlFovhN6G3GjBmZmZk9f1RVROuggf+aqWM/eoJe6//I88GhwqvVLpUElwp34qDHOAQDbPnp5gBb5RuIICcHtYHnpGqX3ZOZk/+zin1zczNBEJaWloq+dUdHx+7du//9738TBBEcHLx8+XInJ6eWlpYbN27s37//zJkzHh4eO3fuVPRtNebs2bM9P6o+Wltbly1bVlFRQRDE4sWL33rrrTNnzuzbt+/3339fsWLF5MmTFTpMIeQPgvyh6Ijm5mYrKyuFXmJjYyMQCHrXS9u2bfP29iYIYsiQIQKBoPfnTWJi4uuvv67aa+7h5+cnEAgWLFjQ59/A06dP16xZc+XKlVdeeWXr1q0ODg4PHz4Ui8X79+8/e/bs+PHjN2zYoMTpnjx5snHjxitXrow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+ "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mdf_model.to_graph_image(\n", + " engine=\"dot\",\n", + " output_format=\"png\",\n", + " view_on_render=False,\n", + " level=1,\n", + " filename_root=\"example\",\n", + " only_warn_on_fail=True,\n", + " is_horizontal = True\n", + ")\n", + "from IPython.display import Image\n", + "Image(filename=\"example.png\")" + ] + }, + { + "cell_type": "markdown", + "id": "979c49b9", + "metadata": {}, + "source": [ + "### ONNX Graph" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5d6e0b95", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "try:\n", + " from IPython.display import Image\n", + " onnx_graph = Image(filename=\"example.onnx.png\")\n", + " display(onnx_graph)\n", + " \n", + "except:\n", + " import netron\n", + " torch.onnx.export(\n", + " sample_model,\n", + " input,\n", + " \"example.onnx\",\n", + " verbose=True,\n", + " input_names=[],\n", + " opset_version=9,\n", + " )\n", + " netron.start(\"example.onnx\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa84f40b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.7" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/PyTorch/PyTorch_MDF/resNext.json b/examples/PyTorch/PyTorch_MDF/resNext.json new file mode 100644 index 00000000..c094cc10 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/resNext.json @@ -0,0 +1,6655 @@ +{ + "ResNet": { + "format": "ModECI MDF v0.4", + "generating_application": "Python modeci-mdf v0.4.2", + "graphs": { + "ResNetGraph": { + "nodes": { + "Conv_496": { + "input_ports": { + "input1": { + "shape": [ + 1, + 3, + 224, + 224 + ], + "type": "float32" + }, + "onnx_Conv_497": { + "shape": [ + 64, + 3, + 7, + 7 + ], + "type": "float32" + }, + "onnx_Conv_498": { + "shape": [ + 64 + ], + "type": "float32" + } + }, + "parameters": { + "dilations": { + "value": [ + 1, + 1 + ] + }, + "group": { + "value": 1 + }, + "kernel_shape": { + "value": [ + 7, + 7 + ] + }, + "pads": { + "value": [ + 3, + 3, + 3, + 3 + ] + }, + "strides": { + "value": [ + 2, + 2 + ] + }, + "onnx_Conv_1": { + "function": "onnx::Conv", + "args": { + "X": "input1", + "W": "onnx_Conv_497", + "B": "onnx_Conv_498" + } + } + }, + "output_ports": { + "_496": { + "value": "onnx_Conv_1" + } + } + }, + "Relu_323": { + "input_ports": { + "_496": { + "shape": [ + 1, + 64, + 112, + 112 + ], + "type": "float32" + } + }, + "parameters": { + "onnx_Relu_1": { + "function": "onnx::Relu", + "args": { + "X": "_496" + } + } + }, + "output_ports": { + "_323": { + "value": "onnx_Relu_1" + } + } + }, + "MaxPool_324": { + "input_ports": { + "_323": { + "shape": [ + 1, + 64, + 112, + 112 + ], + "type": "float32" + } + }, + "parameters": { + "ceil_mode": { + "value": 0 + }, + "kernel_shape": { + "value": [ + 3, + 3 + ] + }, + "pads": { + "value": [ + 1, + 1, + 1, + 1 + ] + }, + "strides": { + "value": [ + 2, + 2 + ] + }, + "onnx_MaxPool_1": { + "function": "onnx::MaxPool", + "args": { + "X": "_323" + } + } + }, + "output_ports": { + "_324": { + "value": "onnx_MaxPool_1[0]" + } + } + }, + "Conv_499": { + "input_ports": { + 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"_397", + "receiver_port": "_397" + }, + "Relu_398_Conv_568": { + "sender": "Relu_398", + "receiver": "Conv_568", + "sender_port": "_398", + "receiver_port": "_398" + }, + "Relu_398_Conv_577": { + "sender": "Relu_398", + "receiver": "Conv_577", + "sender_port": "_398", + "receiver_port": "_398" + }, + "Conv_568_Relu_401": { + "sender": "Conv_568", + "receiver": "Relu_401", + "sender_port": "_568", + "receiver_port": "_568" + }, + "Relu_401_Conv_571": { + "sender": "Relu_401", + "receiver": "Conv_571", + "sender_port": "_401", + "receiver_port": "_401" + }, + "Conv_571_Relu_404": { + "sender": "Conv_571", + "receiver": "Relu_404", + "sender_port": "_571", + "receiver_port": "_571" + }, + "Relu_404_Conv_574": { + "sender": "Relu_404", + "receiver": "Conv_574", + "sender_port": "_404", + "receiver_port": "_404" + }, + "Conv_574_Add_409": { + "sender": "Conv_574", + "receiver": "Add_409", + "sender_port": "_574", + "receiver_port": "_574" + }, + "Conv_577_Add_409": { + "sender": "Conv_577", + "receiver": "Add_409", + "sender_port": "_577", + "receiver_port": "_577" + }, + "Add_409_Relu_410": { + "sender": "Add_409", + "receiver": "Relu_410", + "sender_port": "_409", + "receiver_port": "_409" + }, + "Relu_410_Conv_580": { + "sender": "Relu_410", + "receiver": "Conv_580", + "sender_port": "_410", + "receiver_port": "_410" + }, + "Relu_410_Add_419": { + "sender": "Relu_410", + "receiver": "Add_419", + "sender_port": "_410", + "receiver_port": "_410" + }, + "Conv_580_Relu_413": { + "sender": "Conv_580", + "receiver": "Relu_413", + "sender_port": "_580", + "receiver_port": "_580" + }, + "Relu_413_Conv_583": { + "sender": "Relu_413", + "receiver": "Conv_583", + "sender_port": "_413", + "receiver_port": "_413" + }, + "Conv_583_Relu_416": { + "sender": "Conv_583", + "receiver": "Relu_416", + "sender_port": "_583", + "receiver_port": "_583" + }, + "Relu_416_Conv_586": { + "sender": "Relu_416", + "receiver": "Conv_586", + "sender_port": "_416", + "receiver_port": "_416" + }, + "Conv_586_Add_419": { + "sender": "Conv_586", + "receiver": "Add_419", + "sender_port": "_586", + "receiver_port": "_586" + }, + "Add_419_Relu_420": { + "sender": "Add_419", + "receiver": "Relu_420", + "sender_port": "_419", + "receiver_port": "_419" + }, + "Relu_420_Conv_589": { + "sender": "Relu_420", + "receiver": "Conv_589", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Relu_420_Add_429": { + "sender": "Relu_420", + "receiver": "Add_429", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Conv_589_Relu_423": { + "sender": "Conv_589", + "receiver": "Relu_423", + "sender_port": "_589", + "receiver_port": "_589" + }, + "Relu_423_Conv_592": { + "sender": "Relu_423", + "receiver": "Conv_592", + "sender_port": "_423", + "receiver_port": "_423" + }, + "Conv_592_Relu_426": { + "sender": "Conv_592", + "receiver": "Relu_426", + "sender_port": "_592", + "receiver_port": "_592" + }, + "Relu_426_Conv_595": { + "sender": "Relu_426", + "receiver": "Conv_595", + "sender_port": "_426", + "receiver_port": "_426" + }, + "Conv_595_Add_429": { + "sender": "Conv_595", + "receiver": "Add_429", + "sender_port": "_595", + "receiver_port": "_595" + }, + "Add_429_Relu_430": { + "sender": "Add_429", + "receiver": "Relu_430", + "sender_port": "_429", + "receiver_port": "_429" + }, + "Relu_430_Conv_598": { + "sender": "Relu_430", + "receiver": "Conv_598", + "sender_port": "_430", + "receiver_port": "_430" + }, + "Relu_430_Add_439": { + "sender": "Relu_430", + "receiver": "Add_439", + "sender_port": "_430", + "receiver_port": "_430" + }, + "Conv_598_Relu_433": { + "sender": "Conv_598", + "receiver": "Relu_433", + "sender_port": "_598", + "receiver_port": "_598" + }, + "Relu_433_Conv_601": { + "sender": "Relu_433", + "receiver": "Conv_601", + "sender_port": "_433", + "receiver_port": "_433" + }, + "Conv_601_Relu_436": { + "sender": "Conv_601", + "receiver": "Relu_436", + "sender_port": "_601", + "receiver_port": "_601" + }, + "Relu_436_Conv_604": { + "sender": "Relu_436", + "receiver": "Conv_604", + "sender_port": "_436", + "receiver_port": "_436" + }, + "Conv_604_Add_439": { + "sender": "Conv_604", + "receiver": "Add_439", + "sender_port": "_604", + "receiver_port": "_604" + }, + "Add_439_Relu_440": { + "sender": "Add_439", + "receiver": "Relu_440", + "sender_port": "_439", + "receiver_port": "_439" + }, + "Relu_440_Conv_607": { + "sender": "Relu_440", + "receiver": "Conv_607", + "sender_port": "_440", + "receiver_port": "_440" + }, + "Relu_440_Add_449": { + "sender": "Relu_440", + "receiver": "Add_449", + "sender_port": "_440", + "receiver_port": "_440" + }, + "Conv_607_Relu_443": { + "sender": "Conv_607", + "receiver": "Relu_443", + "sender_port": "_607", + "receiver_port": "_607" + }, + "Relu_443_Conv_610": { + "sender": "Relu_443", + "receiver": "Conv_610", + "sender_port": "_443", + "receiver_port": "_443" + }, + "Conv_610_Relu_446": { + "sender": "Conv_610", + "receiver": "Relu_446", + "sender_port": "_610", + "receiver_port": "_610" + }, + "Relu_446_Conv_613": { + "sender": "Relu_446", + "receiver": "Conv_613", + "sender_port": "_446", + "receiver_port": "_446" + }, + "Conv_613_Add_449": { + "sender": "Conv_613", + "receiver": "Add_449", + "sender_port": "_613", + "receiver_port": "_613" + }, + "Add_449_Relu_450": { + "sender": "Add_449", + "receiver": "Relu_450", + "sender_port": "_449", + "receiver_port": "_449" + }, + "Relu_450_Conv_616": { + "sender": "Relu_450", + "receiver": "Conv_616", + "sender_port": "_450", + "receiver_port": "_450" + }, + "Relu_450_Add_459": { + "sender": "Relu_450", + "receiver": "Add_459", + "sender_port": "_450", + "receiver_port": "_450" + }, + "Conv_616_Relu_453": { + "sender": "Conv_616", + "receiver": "Relu_453", + "sender_port": "_616", + "receiver_port": "_616" + }, + "Relu_453_Conv_619": { + "sender": "Relu_453", + "receiver": "Conv_619", + "sender_port": "_453", + "receiver_port": "_453" + }, + "Conv_619_Relu_456": { + "sender": "Conv_619", + "receiver": "Relu_456", + "sender_port": "_619", + "receiver_port": "_619" + }, + "Relu_456_Conv_622": { + "sender": "Relu_456", + "receiver": "Conv_622", + "sender_port": "_456", + "receiver_port": "_456" + }, + "Conv_622_Add_459": { + "sender": "Conv_622", + "receiver": "Add_459", + "sender_port": "_622", + "receiver_port": "_622" + }, + "Add_459_Relu_460": { + "sender": "Add_459", + "receiver": "Relu_460", + "sender_port": "_459", + "receiver_port": "_459" + }, + "Relu_460_Conv_625": { + "sender": "Relu_460", + "receiver": "Conv_625", + "sender_port": "_460", + "receiver_port": "_460" + }, + "Relu_460_Conv_634": { + "sender": "Relu_460", + "receiver": "Conv_634", + "sender_port": "_460", + "receiver_port": "_460" + }, + "Conv_625_Relu_463": { + "sender": "Conv_625", + "receiver": "Relu_463", + "sender_port": "_625", + "receiver_port": "_625" + }, + "Relu_463_Conv_628": { + "sender": "Relu_463", + "receiver": "Conv_628", + "sender_port": "_463", + "receiver_port": "_463" + }, + "Conv_628_Relu_466": { + "sender": "Conv_628", + "receiver": "Relu_466", + "sender_port": "_628", + "receiver_port": "_628" + }, + "Relu_466_Conv_631": { + "sender": "Relu_466", + "receiver": "Conv_631", + "sender_port": "_466", + "receiver_port": "_466" + }, + "Conv_631_Add_471": { + "sender": "Conv_631", + "receiver": "Add_471", + "sender_port": "_631", + "receiver_port": "_631" + }, + "Conv_634_Add_471": { + "sender": "Conv_634", + "receiver": "Add_471", + "sender_port": "_634", + "receiver_port": "_634" + }, + "Add_471_Relu_472": { + "sender": "Add_471", + "receiver": "Relu_472", + "sender_port": "_471", + "receiver_port": "_471" + }, + "Relu_472_Conv_637": { + "sender": "Relu_472", + "receiver": "Conv_637", + "sender_port": "_472", + "receiver_port": "_472" + }, + "Relu_472_Add_481": { + "sender": "Relu_472", + "receiver": "Add_481", + "sender_port": "_472", + "receiver_port": "_472" + }, + "Conv_637_Relu_475": { + "sender": "Conv_637", + "receiver": "Relu_475", + "sender_port": "_637", + "receiver_port": "_637" + }, + "Relu_475_Conv_640": { + "sender": "Relu_475", + "receiver": "Conv_640", + "sender_port": "_475", + "receiver_port": "_475" + }, + "Conv_640_Relu_478": { + "sender": "Conv_640", + "receiver": "Relu_478", + "sender_port": "_640", + "receiver_port": "_640" + }, + "Relu_478_Conv_643": { + "sender": "Relu_478", + "receiver": "Conv_643", + "sender_port": "_478", + "receiver_port": "_478" + }, + "Conv_643_Add_481": { + "sender": "Conv_643", + "receiver": "Add_481", + "sender_port": "_643", + "receiver_port": "_643" + }, + "Add_481_Relu_482": { + "sender": "Add_481", + "receiver": "Relu_482", + "sender_port": "_481", + "receiver_port": "_481" + }, + "Relu_482_Conv_646": { + "sender": "Relu_482", + "receiver": "Conv_646", + "sender_port": "_482", + "receiver_port": "_482" + }, + "Relu_482_Add_491": { + "sender": "Relu_482", + "receiver": "Add_491", + "sender_port": "_482", + "receiver_port": "_482" + }, + "Conv_646_Relu_485": { + "sender": "Conv_646", + "receiver": "Relu_485", + "sender_port": "_646", + "receiver_port": "_646" + }, + "Relu_485_Conv_649": { + "sender": "Relu_485", + "receiver": "Conv_649", + "sender_port": "_485", + "receiver_port": "_485" + }, + "Conv_649_Relu_488": { + "sender": "Conv_649", + "receiver": "Relu_488", + "sender_port": "_649", + "receiver_port": "_649" + }, + "Relu_488_Conv_652": { + "sender": "Relu_488", + "receiver": "Conv_652", + "sender_port": "_488", + "receiver_port": "_488" + }, + "Conv_652_Add_491": { + "sender": "Conv_652", + "receiver": "Add_491", + "sender_port": "_652", + "receiver_port": "_652" + }, + "Add_491_Relu_492": { + "sender": "Add_491", + "receiver": "Relu_492", + "sender_port": "_491", + "receiver_port": "_491" + }, + "Relu_492_GlobalAveragePool_493": { + "sender": "Relu_492", + "receiver": "GlobalAveragePool_493", + "sender_port": "_492", + "receiver_port": "_492" + }, + "GlobalAveragePool_493_Flatten_494": { + "sender": "GlobalAveragePool_493", + "receiver": "Flatten_494", + "sender_port": "_493", + "receiver_port": "_493" + }, + "Flatten_494_Gemm_495": { + "sender": "Flatten_494", + "receiver": "Gemm_495", + "sender_port": "_494", + "receiver_port": "_494" + } + } + } + }, + "onnx_opset_version": 9 + } +} diff --git a/examples/PyTorch/PyTorch_MDF/resNext.py b/examples/PyTorch/PyTorch_MDF/resNext.py new file mode 100644 index 00000000..18549182 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/resNext.py @@ -0,0 +1,35 @@ +import torchvision.models as models +import torch +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +resNext = models.resnext50_32x4d(pretrained=False) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + resNext.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = resNext(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=resNext, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("resNext.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/resnet.json b/examples/PyTorch/PyTorch_MDF/resnet.json new file mode 100644 index 00000000..6e03b3a8 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/resnet.json @@ -0,0 +1,2673 @@ +{ + "ResNet": { + "format": "ModECI MDF v0.4", + "generating_application": "Python modeci-mdf v0.4.2", + "graphs": { + "ResNetGraph": { + "nodes": { + "Conv_192": { + "input_ports": { + "input1": { + "shape": [ + 5, + 3, + 224, + 224 + ], + "type": "Tensor" + }, + "input4": { + "shape": [ + 64, + 3, + 7, + 7 + ], + "type": "Tensor" + }, + "input5": { + "shape": [ + 64 + ], + "type": "Tensor" + } + }, + "parameters": { + "dilations": { + "value": [ + 1, + 1 + ] + }, + "group": { + "value": 1 + }, + "kernel_shape": { + "value": [ + 7, + 7 + ] + }, + "pads": { + "value": [ + 3, + 3, + 3, + 3 + ] + }, + "strides": { + "value": [ + 2, + 2 + ] + }, + "onnx::Conv_1": { + "function": "onnx::Conv", + "args": { + "X": "input1", + "W": "input4", + "B": "input5" + } + } + }, + "output_ports": { + "_192": { + "value": "onnx::Conv_1" + } + } + }, + "Relu_125": { + "input_ports": { + "_192": { + "shape": [ + 5, + 64, + 112, + 112 + ], + "type": "Tensor" + } + }, + "parameters": { + "onnx::Relu_1": { + "function": "onnx::Relu", + "args": { + "X": "_192" + } + } + }, + "output_ports": { + "_125": { + "value": "onnx::Relu_1" + } + } + }, + "MaxPool_126": { + "input_ports": { + "_125": { + "shape": [ + 5, + 64, + 112, + 112 + ], + "type": "Tensor" + } + }, + "parameters": { + "ceil_mode": { + "value": 0 + }, + "kernel_shape": { + "value": [ + 3, + 3 + ] + }, + "pads": { + "value": [ + 1, + 1, + 1, + 1 + ] + }, + "strides": { + "value": [ + 2, + 2 + ] + }, + "onnx::MaxPool_1": { + "function": "onnx::MaxPool", + "args": { + "X": "_125" + } + } + }, + "output_ports": { + "_126": { + "value": "onnx::MaxPool_1" + } + } + }, + "Conv_195": { + "input_ports": { + "_126": { + "shape": [ + 5, + 64, + 56, + 56 + ], + "type": "Tensor" + }, + "onnx_Conv_196": { + "shape": [ + 64, + 64, + 3, + 3 + ], + "type": "Tensor" + }, + "onnx_Conv_197": { + "shape": [ + 64 + ], + "type": "Tensor" + } + }, + "parameters": { + "dilations": { + "value": [ + 1, + 1 + ] + }, + "group": { + "value": 1 + }, + "kernel_shape": { + "value": [ + 3, + 3 + ] + }, + "pads": { + "value": [ + 1, + 1, + 1, + 1 + ] + }, + "strides": { + "value": [ + 1, + 1 + ] + }, + "onnx::Conv_1": { + "function": "onnx::Conv", + "args": { + "X": "_126", + "W": "onnx_Conv_196", + "B": "onnx_Conv_197" + } + } + }, + "output_ports": { + "_195": { + "value": "onnx::Conv_1" + } + } + }, + "Relu_129": { + "input_ports": { + "_195": { + "shape": [ + 5, + 64, + 56, + 56 + ], + "type": "Tensor" + } + }, + "parameters": { + "onnx::Relu_1": { + "function": "onnx::Relu", + "args": { + "X": "_195" + } + } + }, + "output_ports": { + "_129": { + "value": "onnx::Relu_1" + } + } + }, + "Conv_198": { + "input_ports": { + "_129": { + "shape": [ + 5, + 64, + 56, + 56 + ], + "type": "Tensor" + }, + "onnx_Conv_199": { + "shape": [ + 64, + 64, + 3, + 3 + ], + "type": "Tensor" + }, + "onnx_Conv_200": { + "shape": [ + 64 + ], + "type": "Tensor" + } + }, + "parameters": { + "dilations": { + "value": [ + 1, + 1 + ] + }, + "group": { + "value": 1 + }, + "kernel_shape": { + "value": [ + 3, + 3 + ] + }, + "pads": { + "value": [ + 1, + 1, + 1, + 1 + ] + }, + "strides": { + "value": [ + 1, + 1 + ] + }, + "onnx::Conv_1": { + "function": "onnx::Conv", + "args": { + "X": "_129", + "W": "onnx_Conv_199", + "B": "onnx_Conv_200" + } + } + }, + "output_ports": { + "_198": { + "value": "onnx::Conv_1" + } + } + }, + "Add_132": { + "input_ports": { + "_198": { + "shape": [ + 5, + 64, + 56, + 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things like BatchNorm or Dropout + resnet18.eval() + + # Run the model once to get some ground truth output (from PyTorch) + # with torch.no_grad(): + output = resnet18(x).detach().numpy() + # print(output) + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=resnet18, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("resnet.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/shufflenet_v2.json b/examples/PyTorch/PyTorch_MDF/shufflenet_v2.json new file mode 100644 index 00000000..1e904814 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/shufflenet_v2.json @@ -0,0 +1,32158 @@ +{ + "ShuffleNetV2": { + "format": "ModECI MDF v0.4", + "generating_application": "Python modeci-mdf v0.4.2", + "graphs": { + "ShuffleNetV2Graph": { + "nodes": { + "Conv_1345": { + "input_ports": { + "input1": { + "shape": [ + 1, + 3, + 224, + 224 + ], + "type": "float32" + 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"receiver_port": "_381" + }, + "Constant_382_Unsqueeze_383": { + "sender": "Constant_382", + "receiver": "Unsqueeze_383", + "sender_port": "_382", + "receiver_port": "_382" + }, + "Unsqueeze_383_Concat_384": { + "sender": "Unsqueeze_383", + "receiver": "Concat_384", + "sender_port": "_383", + "receiver_port": "_383" + }, + "Concat_384_Reshape_385": { + "sender": "Concat_384", + "receiver": "Reshape_385", + "sender_port": "_384", + "receiver_port": "_384" + }, + "Reshape_385_Transpose_386": { + "sender": "Reshape_385", + "receiver": "Transpose_386", + "sender_port": "_385", + "receiver_port": "_385" + }, + "Transpose_386_Reshape_397": { + "sender": "Transpose_386", + "receiver": "Reshape_397", + "sender_port": "_386", + "receiver_port": "_386" + }, + "Constant_387_Unsqueeze_391": { + "sender": "Constant_387", + "receiver": "Unsqueeze_391", + "sender_port": "_387", + "receiver_port": "_387" + }, + "Constant_388_Unsqueeze_389": { + "sender": "Constant_388", + "receiver": "Unsqueeze_389", + "sender_port": "_388", + "receiver_port": "_388" + }, + "Unsqueeze_389_Concat_396": { + "sender": "Unsqueeze_389", + "receiver": "Concat_396", + "sender_port": "_389", + "receiver_port": "_389" + }, + "Constant_390_Unsqueeze_391": { + "sender": "Constant_390", + "receiver": "Unsqueeze_391", + "sender_port": "_390", + "receiver_port": "_390" + }, + "Unsqueeze_391_Concat_396": { + "sender": "Unsqueeze_391", + "receiver": "Concat_396", + "sender_port": "_391", + "receiver_port": "_391" + }, + "Constant_392_Unsqueeze_393": { + "sender": "Constant_392", + "receiver": "Unsqueeze_393", + "sender_port": "_392", + "receiver_port": "_392" + }, + "Unsqueeze_393_Concat_396": { + "sender": "Unsqueeze_393", + "receiver": "Concat_396", + "sender_port": "_393", + "receiver_port": "_393" + }, + "Constant_394_Unsqueeze_395": { + "sender": "Constant_394", + "receiver": "Unsqueeze_395", + "sender_port": "_394", + "receiver_port": "_394" + }, + "Unsqueeze_395_Concat_396": { + "sender": "Unsqueeze_395", + "receiver": "Concat_396", + "sender_port": "_395", + "receiver_port": "_395" + }, + "Concat_396_Reshape_397": { + "sender": "Concat_396", + "receiver": "Reshape_397", + "sender_port": "_396", + "receiver_port": "_396" + }, + "Reshape_397_Shape_398": { + "sender": "Reshape_397", + "receiver": "Shape_398", + "sender_port": "_397", + "receiver_port": "_397" + }, + "Reshape_397_Slice_408": { + "sender": "Reshape_397", + "receiver": "Slice_408", + "sender_port": "_397", + "receiver_port": "_397" + }, + "Reshape_397_Slice_411": { + "sender": "Reshape_397", + "receiver": "Slice_411", + "sender_port": "_397", + "receiver_port": "_397" + }, + "Shape_398_Gather_400": { + "sender": "Shape_398", + "receiver": "Gather_400", + "sender_port": "_398", + "receiver_port": "_398" + }, + "Constant_399_Gather_400": { + "sender": "Constant_399", + "receiver": "Gather_400", + "sender_port": "_399", + "receiver_port": "_399" + }, + "Constant_399_Slice_408": { + "sender": "Constant_399", + "receiver": "Slice_408", + "sender_port": "_399", + "receiver_port": "_399" + }, + "Constant_399_Slice_411": { + "sender": "Constant_399", + "receiver": "Slice_411", + "sender_port": "_399", + "receiver_port": "_399" + }, + "Gather_400_Add_403": { + "sender": "Gather_400", + "receiver": "Add_403", + "sender_port": "_400", + "receiver_port": "_400" + }, + "Constant_401_Slice_408": { + "sender": "Constant_401", + "receiver": "Slice_408", + "sender_port": "_401", + "receiver_port": "_401" + }, + "Constant_402_Add_403": { + "sender": "Constant_402", + "receiver": "Add_403", + "sender_port": "_402", + "receiver_port": "_402" + }, + "Add_403_Div_405": { + "sender": "Add_403", + "receiver": "Div_405", + "sender_port": "_403", + "receiver_port": "_403" + }, + "Constant_404_Div_405": { + "sender": "Constant_404", + "receiver": "Div_405", + "sender_port": "_404", + "receiver_port": "_404" + }, + "Div_405_Mul_407": { + "sender": "Div_405", + "receiver": "Mul_407", + "sender_port": "_405", + "receiver_port": "_405" + }, + "Div_405_Mul_410": { + "sender": "Div_405", + "receiver": "Mul_410", + "sender_port": "_405", + "receiver_port": "_405" + }, + "Constant_406_Mul_407": { + "sender": "Constant_406", + "receiver": "Mul_407", + "sender_port": "_406", + "receiver_port": "_406" + }, + "Mul_407_Slice_408": { + "sender": "Mul_407", + "receiver": "Slice_408", + "sender_port": "_407", + "receiver_port": "_407" + }, + "Mul_407_Slice_411": { + "sender": "Mul_407", + "receiver": "Slice_411", + "sender_port": "_407", + "receiver_port": "_407" + }, + "Slice_408_Concat_420": { + "sender": "Slice_408", + "receiver": "Concat_420", + "sender_port": "_408", + "receiver_port": "_408" + }, + "Constant_409_Mul_410": { + "sender": "Constant_409", + "receiver": "Mul_410", + "sender_port": "_409", + "receiver_port": "_409" + }, + "Mul_410_Slice_411": { + "sender": "Mul_410", + "receiver": "Slice_411", + "sender_port": "_410", + "receiver_port": "_410" + }, + "Slice_411_Conv_1363": { + "sender": "Slice_411", + "receiver": "Conv_1363", + "sender_port": "_411", + "receiver_port": "_411" + }, + "Conv_1363_Relu_414": { + "sender": "Conv_1363", + "receiver": "Relu_414", + "sender_port": "_1363", + "receiver_port": "_1363" + }, + "Relu_414_Conv_1366": { + "sender": "Relu_414", + "receiver": "Conv_1366", + "sender_port": "_414", + "receiver_port": "_414" + }, + "Conv_1366_Conv_1369": { + "sender": "Conv_1366", + "receiver": "Conv_1369", + "sender_port": "_1366", + "receiver_port": "_1366" + }, + "Conv_1369_Relu_419": { + "sender": "Conv_1369", + "receiver": "Relu_419", + "sender_port": "_1369", + "receiver_port": "_1369" + }, + "Relu_419_Concat_420": { + "sender": "Relu_419", + "receiver": "Concat_420", + "sender_port": "_419", + "receiver_port": "_419" + }, + "Concat_420_Shape_421": { + "sender": "Concat_420", + "receiver": "Shape_421", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Concat_420_Shape_424": { + "sender": "Concat_420", + "receiver": "Shape_424", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Concat_420_Shape_427": { + "sender": "Concat_420", + "receiver": "Shape_427", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Concat_420_Shape_430": { + "sender": "Concat_420", + "receiver": "Shape_430", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Concat_420_Reshape_449": { + "sender": "Concat_420", + "receiver": "Reshape_449", + "sender_port": "_420", + "receiver_port": "_420" + }, + "Shape_421_Gather_423": { + "sender": "Shape_421", + "receiver": "Gather_423", + "sender_port": "_421", + "receiver_port": "_421" + }, + "Constant_422_Gather_423": { + "sender": "Constant_422", + "receiver": "Gather_423", + "sender_port": "_422", + "receiver_port": "_422" + }, + "Gather_423_Unsqueeze_439": { + "sender": "Gather_423", + "receiver": "Unsqueeze_439", + "sender_port": "_423", + "receiver_port": "_423" + }, + "Gather_423_Unsqueeze_453": { + "sender": "Gather_423", + "receiver": "Unsqueeze_453", + "sender_port": "_423", + "receiver_port": "_423" + }, + "Shape_424_Gather_426": { + "sender": "Shape_424", + "receiver": "Gather_426", + "sender_port": "_424", + "receiver_port": "_424" + }, + "Constant_425_Gather_426": { + "sender": "Constant_425", + "receiver": "Gather_426", + "sender_port": "_425", + "receiver_port": "_425" + }, + "Gather_426_Div_434": { + "sender": "Gather_426", + "receiver": "Div_434", + "sender_port": "_426", + "receiver_port": "_426" + }, + "Shape_427_Gather_429": { + "sender": "Shape_427", + "receiver": "Gather_429", + "sender_port": "_427", + "receiver_port": "_427" + }, + "Constant_428_Gather_429": { + "sender": "Constant_428", + "receiver": "Gather_429", + "sender_port": "_428", + "receiver_port": "_428" + }, + "Gather_429_Unsqueeze_445": { + "sender": "Gather_429", + "receiver": "Unsqueeze_445", + "sender_port": "_429", + "receiver_port": "_429" + }, + "Gather_429_Unsqueeze_457": { + "sender": "Gather_429", + "receiver": "Unsqueeze_457", + "sender_port": "_429", + "receiver_port": "_429" + }, + "Shape_430_Gather_432": { + "sender": "Shape_430", + "receiver": "Gather_432", + "sender_port": "_430", + "receiver_port": "_430" + }, + "Constant_431_Gather_432": { + "sender": "Constant_431", + "receiver": "Gather_432", + "sender_port": "_431", + "receiver_port": "_431" + }, + "Gather_432_Unsqueeze_447": { + "sender": "Gather_432", + "receiver": "Unsqueeze_447", + "sender_port": "_432", + "receiver_port": "_432" + }, + "Gather_432_Unsqueeze_459": { + "sender": "Gather_432", + "receiver": "Unsqueeze_459", + "sender_port": "_432", + "receiver_port": "_432" + }, + "Constant_433_Div_434": { + "sender": "Constant_433", + "receiver": "Div_434", + "sender_port": "_433", + "receiver_port": "_433" + }, + "Div_434_Cast_435": { + "sender": "Div_434", + "receiver": "Cast_435", + "sender_port": "_434", + "receiver_port": "_434" + }, + "Cast_435_Cast_436": { + "sender": "Cast_435", + "receiver": "Cast_436", + "sender_port": "_435", + "receiver_port": "_435" + }, + "Cast_436_Unsqueeze_443": { + "sender": "Cast_436", + "receiver": "Unsqueeze_443", + "sender_port": "_436", + "receiver_port": "_436" + }, + "Constant_437_Unsqueeze_441": { + "sender": "Constant_437", + "receiver": "Unsqueeze_441", + "sender_port": "_437", + "receiver_port": "_437" + }, + "Constant_438_Unsqueeze_439": { + "sender": "Constant_438", + "receiver": "Unsqueeze_439", + "sender_port": "_438", + "receiver_port": "_438" + }, + "Unsqueeze_439_Concat_448": { + "sender": "Unsqueeze_439", + "receiver": "Concat_448", + "sender_port": "_439", + "receiver_port": "_439" + }, + "Constant_440_Unsqueeze_441": { + "sender": "Constant_440", + "receiver": "Unsqueeze_441", + "sender_port": "_440", + "receiver_port": "_440" + }, + "Unsqueeze_441_Concat_448": { + "sender": "Unsqueeze_441", + "receiver": "Concat_448", + "sender_port": "_441", + "receiver_port": "_441" + }, + "Constant_442_Unsqueeze_443": { + "sender": "Constant_442", + "receiver": "Unsqueeze_443", + "sender_port": "_442", + "receiver_port": "_442" + }, + "Unsqueeze_443_Concat_448": { + "sender": "Unsqueeze_443", + "receiver": "Concat_448", + "sender_port": "_443", + "receiver_port": "_443" + }, + "Constant_444_Unsqueeze_445": { + "sender": "Constant_444", + "receiver": "Unsqueeze_445", + "sender_port": "_444", + "receiver_port": "_444" + }, + "Unsqueeze_445_Concat_448": { + "sender": "Unsqueeze_445", + "receiver": "Concat_448", + "sender_port": "_445", + "receiver_port": "_445" + }, + "Constant_446_Unsqueeze_447": { + "sender": "Constant_446", + "receiver": "Unsqueeze_447", + "sender_port": "_446", + "receiver_port": "_446" + }, + "Unsqueeze_447_Concat_448": { + "sender": "Unsqueeze_447", + "receiver": "Concat_448", + "sender_port": "_447", + "receiver_port": "_447" + }, + "Concat_448_Reshape_449": { + "sender": "Concat_448", + "receiver": "Reshape_449", + "sender_port": "_448", + "receiver_port": "_448" + }, + "Reshape_449_Transpose_450": { + "sender": "Reshape_449", + "receiver": "Transpose_450", + "sender_port": "_449", + "receiver_port": "_449" + }, + "Transpose_450_Reshape_461": { + "sender": "Transpose_450", + "receiver": "Reshape_461", + "sender_port": "_450", + "receiver_port": "_450" + }, + "Constant_451_Unsqueeze_455": { + "sender": "Constant_451", + "receiver": "Unsqueeze_455", + "sender_port": "_451", + "receiver_port": "_451" + }, + "Constant_452_Unsqueeze_453": { + "sender": "Constant_452", + "receiver": "Unsqueeze_453", + "sender_port": "_452", + "receiver_port": "_452" + }, + "Unsqueeze_453_Concat_460": { + "sender": "Unsqueeze_453", + "receiver": "Concat_460", + "sender_port": "_453", + "receiver_port": "_453" + }, + "Constant_454_Unsqueeze_455": { + "sender": "Constant_454", + "receiver": "Unsqueeze_455", + "sender_port": "_454", + "receiver_port": "_454" + }, + "Unsqueeze_455_Concat_460": { + "sender": "Unsqueeze_455", + "receiver": "Concat_460", + "sender_port": "_455", + "receiver_port": "_455" + }, + "Constant_456_Unsqueeze_457": { + "sender": "Constant_456", + "receiver": "Unsqueeze_457", + "sender_port": "_456", + "receiver_port": "_456" + }, + "Unsqueeze_457_Concat_460": { + "sender": "Unsqueeze_457", + "receiver": "Concat_460", + "sender_port": "_457", + "receiver_port": "_457" + }, + "Constant_458_Unsqueeze_459": { + "sender": "Constant_458", + "receiver": "Unsqueeze_459", + "sender_port": "_458", + "receiver_port": "_458" + }, + "Unsqueeze_459_Concat_460": { + "sender": "Unsqueeze_459", + "receiver": "Concat_460", + "sender_port": "_459", + "receiver_port": "_459" + }, + "Concat_460_Reshape_461": { + "sender": "Concat_460", + "receiver": "Reshape_461", + "sender_port": "_460", + "receiver_port": "_460" + }, + "Reshape_461_Shape_462": { + "sender": "Reshape_461", + "receiver": "Shape_462", + "sender_port": "_461", + "receiver_port": "_461" + }, + "Reshape_461_Slice_472": { + "sender": "Reshape_461", + "receiver": "Slice_472", + "sender_port": "_461", + "receiver_port": "_461" + }, + "Reshape_461_Slice_475": { + "sender": "Reshape_461", + "receiver": "Slice_475", + "sender_port": "_461", + "receiver_port": "_461" + }, + "Shape_462_Gather_464": { + "sender": "Shape_462", + "receiver": "Gather_464", + "sender_port": "_462", + "receiver_port": "_462" + }, + "Constant_463_Gather_464": { + "sender": "Constant_463", + "receiver": "Gather_464", + "sender_port": "_463", + "receiver_port": "_463" + }, + "Constant_463_Slice_472": { + "sender": "Constant_463", + "receiver": "Slice_472", + "sender_port": "_463", + "receiver_port": "_463" + }, + "Constant_463_Slice_475": { + "sender": "Constant_463", + "receiver": "Slice_475", + "sender_port": "_463", + "receiver_port": "_463" + }, + "Gather_464_Add_467": { + "sender": "Gather_464", + "receiver": "Add_467", + "sender_port": "_464", + "receiver_port": "_464" + }, + "Constant_465_Slice_472": { + "sender": "Constant_465", + "receiver": "Slice_472", + "sender_port": "_465", + "receiver_port": "_465" + }, + "Constant_466_Add_467": { + "sender": "Constant_466", + "receiver": "Add_467", + "sender_port": "_466", + "receiver_port": "_466" + }, + "Add_467_Div_469": { + "sender": "Add_467", + "receiver": "Div_469", + "sender_port": "_467", + "receiver_port": "_467" + }, + "Constant_468_Div_469": { + "sender": "Constant_468", + "receiver": "Div_469", + "sender_port": "_468", + "receiver_port": "_468" + }, + "Div_469_Mul_471": { + "sender": "Div_469", + "receiver": "Mul_471", + "sender_port": "_469", + "receiver_port": "_469" + }, + "Div_469_Mul_474": { + "sender": "Div_469", + "receiver": "Mul_474", + "sender_port": "_469", + "receiver_port": "_469" + }, + "Constant_470_Mul_471": { + "sender": "Constant_470", + "receiver": "Mul_471", + "sender_port": "_470", + "receiver_port": "_470" + }, + "Mul_471_Slice_472": { + "sender": "Mul_471", + "receiver": "Slice_472", + "sender_port": "_471", + "receiver_port": "_471" + }, + "Mul_471_Slice_475": { + "sender": "Mul_471", + "receiver": "Slice_475", + "sender_port": "_471", + "receiver_port": "_471" + }, + "Slice_472_Concat_484": { + "sender": "Slice_472", + "receiver": "Concat_484", + "sender_port": "_472", + "receiver_port": "_472" + }, + "Constant_473_Mul_474": { + "sender": "Constant_473", + "receiver": "Mul_474", + "sender_port": "_473", + "receiver_port": "_473" + }, + "Mul_474_Slice_475": { + "sender": "Mul_474", + "receiver": "Slice_475", + "sender_port": "_474", + "receiver_port": "_474" + }, + "Slice_475_Conv_1372": { + "sender": "Slice_475", + "receiver": "Conv_1372", + "sender_port": "_475", + "receiver_port": "_475" + }, + "Conv_1372_Relu_478": { + "sender": "Conv_1372", + "receiver": "Relu_478", + "sender_port": "_1372", + "receiver_port": "_1372" + }, + "Relu_478_Conv_1375": { + "sender": "Relu_478", + "receiver": "Conv_1375", + "sender_port": "_478", + "receiver_port": "_478" + }, + "Conv_1375_Conv_1378": { + "sender": "Conv_1375", + "receiver": "Conv_1378", + "sender_port": "_1375", + "receiver_port": "_1375" + }, + "Conv_1378_Relu_483": { + "sender": "Conv_1378", + "receiver": "Relu_483", + "sender_port": "_1378", + "receiver_port": "_1378" + }, + "Relu_483_Concat_484": { + "sender": "Relu_483", + "receiver": "Concat_484", + "sender_port": "_483", + "receiver_port": "_483" + }, + "Concat_484_Shape_485": { + "sender": "Concat_484", + "receiver": "Shape_485", + "sender_port": "_484", + "receiver_port": "_484" + }, + "Concat_484_Shape_488": { + "sender": "Concat_484", + "receiver": "Shape_488", + "sender_port": "_484", + "receiver_port": "_484" + }, + "Concat_484_Shape_491": { + "sender": "Concat_484", + "receiver": "Shape_491", + "sender_port": "_484", + "receiver_port": "_484" + }, + "Concat_484_Shape_494": { + "sender": "Concat_484", + "receiver": "Shape_494", + "sender_port": "_484", + "receiver_port": "_484" + }, + "Concat_484_Reshape_513": { + "sender": "Concat_484", + "receiver": "Reshape_513", + "sender_port": "_484", + "receiver_port": "_484" + }, + "Shape_485_Gather_487": { + "sender": "Shape_485", + "receiver": "Gather_487", + "sender_port": "_485", + "receiver_port": "_485" + }, + "Constant_486_Gather_487": { + "sender": "Constant_486", + "receiver": "Gather_487", + "sender_port": "_486", + "receiver_port": "_486" + }, + "Gather_487_Unsqueeze_503": { + "sender": "Gather_487", + "receiver": "Unsqueeze_503", + "sender_port": "_487", + "receiver_port": "_487" + }, + "Gather_487_Unsqueeze_517": { + "sender": "Gather_487", + "receiver": "Unsqueeze_517", + "sender_port": "_487", + "receiver_port": "_487" + }, + "Shape_488_Gather_490": { + "sender": "Shape_488", + "receiver": "Gather_490", + "sender_port": "_488", + "receiver_port": "_488" + }, + "Constant_489_Gather_490": { + "sender": "Constant_489", + "receiver": "Gather_490", + "sender_port": "_489", + "receiver_port": "_489" + }, + "Gather_490_Div_498": { + "sender": "Gather_490", + "receiver": "Div_498", + "sender_port": "_490", + "receiver_port": "_490" + }, + "Shape_491_Gather_493": { + "sender": "Shape_491", + "receiver": "Gather_493", + "sender_port": "_491", + "receiver_port": "_491" + }, + "Constant_492_Gather_493": { + "sender": "Constant_492", + "receiver": "Gather_493", + "sender_port": "_492", + "receiver_port": "_492" + }, + "Gather_493_Unsqueeze_509": { + "sender": "Gather_493", + "receiver": "Unsqueeze_509", + "sender_port": "_493", + "receiver_port": "_493" + }, + "Gather_493_Unsqueeze_521": { + "sender": "Gather_493", + "receiver": "Unsqueeze_521", + "sender_port": "_493", + "receiver_port": "_493" + }, + "Shape_494_Gather_496": { + "sender": "Shape_494", + "receiver": "Gather_496", + "sender_port": "_494", + "receiver_port": "_494" + }, + "Constant_495_Gather_496": { + "sender": "Constant_495", + "receiver": "Gather_496", + "sender_port": "_495", + "receiver_port": "_495" + }, + "Gather_496_Unsqueeze_511": { + "sender": "Gather_496", + "receiver": "Unsqueeze_511", + "sender_port": "_496", + "receiver_port": "_496" + }, + "Gather_496_Unsqueeze_523": { + "sender": "Gather_496", + "receiver": "Unsqueeze_523", + "sender_port": "_496", + "receiver_port": "_496" + }, + "Constant_497_Div_498": { + "sender": "Constant_497", + "receiver": "Div_498", + "sender_port": "_497", + "receiver_port": "_497" + }, + "Div_498_Cast_499": { + "sender": "Div_498", + "receiver": "Cast_499", + "sender_port": "_498", + "receiver_port": "_498" + }, + "Cast_499_Cast_500": { + "sender": "Cast_499", + "receiver": "Cast_500", + "sender_port": "_499", + "receiver_port": "_499" + }, + "Cast_500_Unsqueeze_507": { + "sender": "Cast_500", + "receiver": "Unsqueeze_507", + "sender_port": "_500", + "receiver_port": "_500" + }, + "Constant_501_Unsqueeze_505": { + "sender": "Constant_501", + "receiver": "Unsqueeze_505", + "sender_port": "_501", + "receiver_port": "_501" + }, + "Constant_502_Unsqueeze_503": { + "sender": "Constant_502", + "receiver": "Unsqueeze_503", + "sender_port": "_502", + "receiver_port": "_502" + }, + "Unsqueeze_503_Concat_512": { + "sender": "Unsqueeze_503", + "receiver": "Concat_512", + "sender_port": "_503", + "receiver_port": "_503" + }, + "Constant_504_Unsqueeze_505": { + "sender": "Constant_504", + "receiver": "Unsqueeze_505", + "sender_port": "_504", + "receiver_port": "_504" + }, + "Unsqueeze_505_Concat_512": { + "sender": "Unsqueeze_505", + "receiver": "Concat_512", + "sender_port": "_505", + "receiver_port": "_505" + }, + "Constant_506_Unsqueeze_507": { + "sender": "Constant_506", + "receiver": "Unsqueeze_507", + "sender_port": "_506", + "receiver_port": "_506" + }, + "Unsqueeze_507_Concat_512": { + "sender": "Unsqueeze_507", + "receiver": "Concat_512", + "sender_port": "_507", + "receiver_port": "_507" + }, + "Constant_508_Unsqueeze_509": { + "sender": "Constant_508", + "receiver": "Unsqueeze_509", + "sender_port": "_508", + "receiver_port": "_508" + }, + "Unsqueeze_509_Concat_512": { + "sender": "Unsqueeze_509", + "receiver": "Concat_512", + "sender_port": "_509", + "receiver_port": "_509" + }, + "Constant_510_Unsqueeze_511": { + "sender": "Constant_510", + "receiver": "Unsqueeze_511", + "sender_port": "_510", + "receiver_port": "_510" + }, + "Unsqueeze_511_Concat_512": { + "sender": "Unsqueeze_511", + "receiver": "Concat_512", + "sender_port": "_511", + "receiver_port": "_511" + }, + "Concat_512_Reshape_513": { + "sender": "Concat_512", + "receiver": "Reshape_513", + "sender_port": "_512", + "receiver_port": "_512" + }, + "Reshape_513_Transpose_514": { + "sender": "Reshape_513", + "receiver": "Transpose_514", + "sender_port": "_513", + "receiver_port": "_513" + }, + "Transpose_514_Reshape_525": { + "sender": "Transpose_514", + "receiver": "Reshape_525", + "sender_port": "_514", + "receiver_port": "_514" + }, + "Constant_515_Unsqueeze_519": { + "sender": "Constant_515", + "receiver": "Unsqueeze_519", + "sender_port": "_515", + "receiver_port": "_515" + }, + "Constant_516_Unsqueeze_517": { + "sender": "Constant_516", + "receiver": "Unsqueeze_517", + "sender_port": "_516", + "receiver_port": "_516" + }, + "Unsqueeze_517_Concat_524": { + "sender": "Unsqueeze_517", + "receiver": "Concat_524", + "sender_port": "_517", + "receiver_port": "_517" + }, + "Constant_518_Unsqueeze_519": { + "sender": "Constant_518", + "receiver": "Unsqueeze_519", + "sender_port": "_518", + "receiver_port": "_518" + }, + "Unsqueeze_519_Concat_524": { + "sender": "Unsqueeze_519", + "receiver": "Concat_524", + "sender_port": "_519", + "receiver_port": "_519" + }, + "Constant_520_Unsqueeze_521": { + "sender": "Constant_520", + "receiver": "Unsqueeze_521", + "sender_port": "_520", + "receiver_port": "_520" + }, + "Unsqueeze_521_Concat_524": { + "sender": "Unsqueeze_521", + "receiver": "Concat_524", + "sender_port": "_521", + "receiver_port": "_521" + }, + "Constant_522_Unsqueeze_523": { + "sender": "Constant_522", + "receiver": "Unsqueeze_523", + "sender_port": "_522", + "receiver_port": "_522" + }, + "Unsqueeze_523_Concat_524": { + "sender": "Unsqueeze_523", + "receiver": "Concat_524", + "sender_port": "_523", + "receiver_port": "_523" + }, + "Concat_524_Reshape_525": { + "sender": "Concat_524", + "receiver": "Reshape_525", + "sender_port": "_524", + "receiver_port": "_524" + }, + "Reshape_525_Shape_526": { + "sender": "Reshape_525", + "receiver": "Shape_526", + "sender_port": "_525", + "receiver_port": "_525" + }, + "Reshape_525_Slice_536": { + "sender": "Reshape_525", + "receiver": "Slice_536", + "sender_port": "_525", + "receiver_port": "_525" + }, + "Reshape_525_Slice_539": { + "sender": "Reshape_525", + "receiver": "Slice_539", + "sender_port": "_525", + "receiver_port": "_525" + }, + "Shape_526_Gather_528": { + "sender": "Shape_526", + "receiver": "Gather_528", + "sender_port": "_526", + "receiver_port": "_526" + }, + "Constant_527_Gather_528": { + "sender": "Constant_527", + "receiver": "Gather_528", + "sender_port": "_527", + "receiver_port": "_527" + }, + "Constant_527_Slice_536": { + "sender": "Constant_527", + "receiver": "Slice_536", + "sender_port": "_527", + "receiver_port": "_527" + }, + "Constant_527_Slice_539": { + "sender": "Constant_527", + "receiver": "Slice_539", + "sender_port": "_527", + "receiver_port": "_527" + }, + "Gather_528_Add_531": { + "sender": "Gather_528", + "receiver": "Add_531", + "sender_port": "_528", + "receiver_port": "_528" + }, + "Constant_529_Slice_536": { + "sender": "Constant_529", + "receiver": "Slice_536", + "sender_port": "_529", + "receiver_port": "_529" + }, + "Constant_530_Add_531": { + "sender": "Constant_530", + "receiver": "Add_531", + "sender_port": "_530", + "receiver_port": "_530" + }, + "Add_531_Div_533": { + "sender": "Add_531", + "receiver": "Div_533", + "sender_port": "_531", + "receiver_port": "_531" + }, + "Constant_532_Div_533": { + "sender": "Constant_532", + "receiver": "Div_533", + "sender_port": "_532", + "receiver_port": "_532" + }, + "Div_533_Mul_535": { + "sender": "Div_533", + "receiver": "Mul_535", + "sender_port": "_533", + "receiver_port": "_533" + }, + "Div_533_Mul_538": { + "sender": "Div_533", + "receiver": "Mul_538", + "sender_port": "_533", + "receiver_port": "_533" + }, + "Constant_534_Mul_535": { + "sender": "Constant_534", + "receiver": "Mul_535", + "sender_port": "_534", + "receiver_port": "_534" + }, + "Mul_535_Slice_536": { + "sender": "Mul_535", + "receiver": "Slice_536", + "sender_port": "_535", + "receiver_port": "_535" + }, + "Mul_535_Slice_539": { + "sender": "Mul_535", + "receiver": "Slice_539", + "sender_port": "_535", + "receiver_port": "_535" + }, + "Slice_536_Concat_548": { + "sender": "Slice_536", + "receiver": "Concat_548", + "sender_port": "_536", + "receiver_port": "_536" + }, + "Constant_537_Mul_538": { + "sender": "Constant_537", + "receiver": "Mul_538", + "sender_port": "_537", + "receiver_port": "_537" + }, + "Mul_538_Slice_539": { + "sender": "Mul_538", + "receiver": "Slice_539", + "sender_port": "_538", + "receiver_port": "_538" + }, + "Slice_539_Conv_1381": { + "sender": "Slice_539", + "receiver": "Conv_1381", + "sender_port": "_539", + "receiver_port": "_539" + }, + "Conv_1381_Relu_542": { + "sender": "Conv_1381", + "receiver": "Relu_542", + "sender_port": "_1381", + "receiver_port": "_1381" + }, + "Relu_542_Conv_1384": { + "sender": "Relu_542", + "receiver": "Conv_1384", + "sender_port": "_542", + "receiver_port": "_542" + }, + "Conv_1384_Conv_1387": { + "sender": "Conv_1384", + "receiver": "Conv_1387", + "sender_port": "_1384", + "receiver_port": "_1384" + }, + "Conv_1387_Relu_547": { + "sender": "Conv_1387", + "receiver": "Relu_547", + "sender_port": "_1387", + "receiver_port": "_1387" + }, + "Relu_547_Concat_548": { + "sender": "Relu_547", + "receiver": "Concat_548", + "sender_port": "_547", + "receiver_port": "_547" + }, + "Concat_548_Shape_549": { + "sender": "Concat_548", + "receiver": "Shape_549", + "sender_port": "_548", + "receiver_port": "_548" + }, + "Concat_548_Shape_552": { + "sender": "Concat_548", + "receiver": "Shape_552", + "sender_port": "_548", + "receiver_port": "_548" + }, + "Concat_548_Shape_555": { + "sender": "Concat_548", + "receiver": "Shape_555", + "sender_port": "_548", + "receiver_port": "_548" + }, + "Concat_548_Shape_558": { + "sender": "Concat_548", + "receiver": "Shape_558", + "sender_port": "_548", + "receiver_port": "_548" + }, + "Concat_548_Reshape_577": { + "sender": "Concat_548", + "receiver": "Reshape_577", + "sender_port": "_548", + "receiver_port": "_548" + }, + "Shape_549_Gather_551": { + "sender": "Shape_549", + "receiver": "Gather_551", + "sender_port": "_549", + "receiver_port": "_549" + }, + "Constant_550_Gather_551": { + "sender": "Constant_550", + "receiver": "Gather_551", + "sender_port": "_550", + "receiver_port": "_550" + }, + "Gather_551_Unsqueeze_567": { + "sender": "Gather_551", + "receiver": "Unsqueeze_567", + "sender_port": "_551", + "receiver_port": "_551" + }, + "Gather_551_Unsqueeze_581": { + "sender": "Gather_551", + "receiver": "Unsqueeze_581", + "sender_port": "_551", + "receiver_port": "_551" + }, + "Shape_552_Gather_554": { + "sender": "Shape_552", + "receiver": "Gather_554", + "sender_port": "_552", + "receiver_port": "_552" + }, + "Constant_553_Gather_554": { + "sender": "Constant_553", + "receiver": "Gather_554", + "sender_port": "_553", + "receiver_port": "_553" + }, + "Gather_554_Div_562": { + "sender": "Gather_554", + "receiver": "Div_562", + "sender_port": "_554", + "receiver_port": "_554" + }, + "Shape_555_Gather_557": { + "sender": "Shape_555", + "receiver": "Gather_557", + "sender_port": "_555", + "receiver_port": "_555" + }, + "Constant_556_Gather_557": { + "sender": "Constant_556", + "receiver": "Gather_557", + "sender_port": "_556", + "receiver_port": "_556" + }, + "Gather_557_Unsqueeze_573": { + "sender": "Gather_557", + "receiver": "Unsqueeze_573", + "sender_port": "_557", + "receiver_port": "_557" + }, + "Gather_557_Unsqueeze_585": { + "sender": "Gather_557", + "receiver": "Unsqueeze_585", + "sender_port": "_557", + "receiver_port": "_557" + }, + "Shape_558_Gather_560": { + "sender": "Shape_558", + "receiver": "Gather_560", + "sender_port": "_558", + "receiver_port": "_558" + }, + "Constant_559_Gather_560": { + "sender": "Constant_559", + "receiver": "Gather_560", + "sender_port": "_559", + "receiver_port": "_559" + }, + "Gather_560_Unsqueeze_575": { + "sender": "Gather_560", + "receiver": "Unsqueeze_575", + "sender_port": "_560", + "receiver_port": "_560" + }, + "Gather_560_Unsqueeze_587": { + "sender": "Gather_560", + "receiver": "Unsqueeze_587", + "sender_port": "_560", + "receiver_port": "_560" + }, + "Constant_561_Div_562": { + "sender": "Constant_561", + "receiver": "Div_562", + "sender_port": "_561", + "receiver_port": "_561" + }, + "Div_562_Cast_563": { + "sender": "Div_562", + "receiver": "Cast_563", + "sender_port": "_562", + "receiver_port": "_562" + }, + "Cast_563_Cast_564": { + "sender": "Cast_563", + "receiver": "Cast_564", + "sender_port": "_563", + "receiver_port": "_563" + }, + "Cast_564_Unsqueeze_571": { + "sender": "Cast_564", + "receiver": "Unsqueeze_571", + "sender_port": "_564", + "receiver_port": "_564" + }, + "Constant_565_Unsqueeze_569": { + "sender": "Constant_565", + "receiver": "Unsqueeze_569", + "sender_port": "_565", + "receiver_port": "_565" + }, + "Constant_566_Unsqueeze_567": { + "sender": "Constant_566", + "receiver": "Unsqueeze_567", + "sender_port": "_566", + "receiver_port": "_566" + }, + "Unsqueeze_567_Concat_576": { + "sender": "Unsqueeze_567", + "receiver": "Concat_576", + "sender_port": "_567", + "receiver_port": "_567" + }, + "Constant_568_Unsqueeze_569": { + "sender": "Constant_568", + "receiver": "Unsqueeze_569", + "sender_port": "_568", + "receiver_port": "_568" + }, + "Unsqueeze_569_Concat_576": { + "sender": "Unsqueeze_569", + "receiver": "Concat_576", + "sender_port": "_569", + "receiver_port": "_569" + }, + "Constant_570_Unsqueeze_571": { + "sender": "Constant_570", + "receiver": "Unsqueeze_571", + "sender_port": "_570", + "receiver_port": "_570" + }, + "Unsqueeze_571_Concat_576": { + "sender": "Unsqueeze_571", + "receiver": "Concat_576", + "sender_port": "_571", + "receiver_port": "_571" + }, + "Constant_572_Unsqueeze_573": { + "sender": "Constant_572", + "receiver": "Unsqueeze_573", + "sender_port": "_572", + "receiver_port": "_572" + }, + "Unsqueeze_573_Concat_576": { + "sender": "Unsqueeze_573", + "receiver": "Concat_576", + "sender_port": "_573", + "receiver_port": "_573" + }, + "Constant_574_Unsqueeze_575": { + "sender": "Constant_574", + "receiver": "Unsqueeze_575", + "sender_port": "_574", + "receiver_port": "_574" + }, + "Unsqueeze_575_Concat_576": { + "sender": "Unsqueeze_575", + "receiver": "Concat_576", + "sender_port": "_575", + "receiver_port": "_575" + }, + "Concat_576_Reshape_577": { + "sender": "Concat_576", + "receiver": "Reshape_577", + "sender_port": "_576", + "receiver_port": "_576" + }, + "Reshape_577_Transpose_578": { + "sender": "Reshape_577", + "receiver": "Transpose_578", + "sender_port": "_577", + "receiver_port": "_577" + }, + "Transpose_578_Reshape_589": { + "sender": "Transpose_578", + "receiver": "Reshape_589", + "sender_port": "_578", + "receiver_port": "_578" + }, + "Constant_579_Unsqueeze_583": { + "sender": "Constant_579", + "receiver": "Unsqueeze_583", + "sender_port": "_579", + "receiver_port": "_579" + }, + "Constant_580_Unsqueeze_581": { + "sender": "Constant_580", + "receiver": "Unsqueeze_581", + "sender_port": "_580", + "receiver_port": "_580" + }, + "Unsqueeze_581_Concat_588": { + "sender": "Unsqueeze_581", + "receiver": "Concat_588", + "sender_port": "_581", + "receiver_port": "_581" + }, + "Constant_582_Unsqueeze_583": { + "sender": "Constant_582", + "receiver": "Unsqueeze_583", + "sender_port": "_582", + "receiver_port": "_582" + }, + "Unsqueeze_583_Concat_588": { + "sender": "Unsqueeze_583", + "receiver": "Concat_588", + "sender_port": "_583", + "receiver_port": "_583" + }, + "Constant_584_Unsqueeze_585": { + "sender": "Constant_584", + "receiver": "Unsqueeze_585", + "sender_port": "_584", + "receiver_port": "_584" + }, + "Unsqueeze_585_Concat_588": { + "sender": "Unsqueeze_585", + "receiver": "Concat_588", + "sender_port": "_585", + "receiver_port": "_585" + }, + "Constant_586_Unsqueeze_587": { + "sender": "Constant_586", + "receiver": "Unsqueeze_587", + "sender_port": "_586", + "receiver_port": "_586" + }, + "Unsqueeze_587_Concat_588": { + "sender": "Unsqueeze_587", + "receiver": "Concat_588", + "sender_port": "_587", + "receiver_port": "_587" + }, + "Concat_588_Reshape_589": { + "sender": "Concat_588", + "receiver": "Reshape_589", + "sender_port": "_588", + "receiver_port": "_588" + }, + "Reshape_589_Conv_1390": { + "sender": "Reshape_589", + "receiver": "Conv_1390", + "sender_port": "_589", + "receiver_port": "_589" + }, + "Reshape_589_Conv_1396": { + "sender": "Reshape_589", + "receiver": "Conv_1396", + "sender_port": "_589", + "receiver_port": "_589" + }, + "Conv_1390_Conv_1393": { + "sender": "Conv_1390", + "receiver": "Conv_1393", + "sender_port": "_1390", + "receiver_port": "_1390" + }, + "Conv_1393_Relu_594": { + "sender": "Conv_1393", + "receiver": "Relu_594", + "sender_port": "_1393", + "receiver_port": "_1393" + }, + "Relu_594_Concat_603": { + "sender": "Relu_594", + "receiver": "Concat_603", + "sender_port": "_594", + "receiver_port": "_594" + }, + "Conv_1396_Relu_597": { + "sender": "Conv_1396", + "receiver": "Relu_597", + "sender_port": "_1396", + "receiver_port": "_1396" + }, + "Relu_597_Conv_1399": { + "sender": "Relu_597", + "receiver": "Conv_1399", + "sender_port": "_597", + "receiver_port": "_597" + }, + "Conv_1399_Conv_1402": { + "sender": "Conv_1399", + "receiver": "Conv_1402", + "sender_port": "_1399", + "receiver_port": "_1399" + }, + "Conv_1402_Relu_602": { + "sender": "Conv_1402", + "receiver": "Relu_602", + "sender_port": "_1402", + "receiver_port": "_1402" + }, + "Relu_602_Concat_603": { + "sender": "Relu_602", + "receiver": "Concat_603", + "sender_port": "_602", + "receiver_port": "_602" + }, + "Concat_603_Shape_604": { + "sender": "Concat_603", + "receiver": "Shape_604", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Concat_603_Shape_607": { + "sender": "Concat_603", + "receiver": "Shape_607", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Concat_603_Shape_610": { + "sender": "Concat_603", + "receiver": "Shape_610", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Concat_603_Shape_613": { + "sender": "Concat_603", + "receiver": "Shape_613", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Concat_603_Reshape_632": { + "sender": "Concat_603", + "receiver": "Reshape_632", + "sender_port": "_603", + "receiver_port": "_603" + }, + "Shape_604_Gather_606": { + "sender": "Shape_604", + "receiver": "Gather_606", + "sender_port": "_604", + "receiver_port": "_604" + }, + "Constant_605_Gather_606": { + "sender": "Constant_605", + "receiver": "Gather_606", + "sender_port": "_605", + "receiver_port": "_605" + }, + "Gather_606_Unsqueeze_622": { + "sender": "Gather_606", + "receiver": "Unsqueeze_622", + "sender_port": "_606", + "receiver_port": "_606" + }, + "Gather_606_Unsqueeze_636": { + "sender": "Gather_606", + "receiver": "Unsqueeze_636", + "sender_port": "_606", + "receiver_port": "_606" + }, + "Shape_607_Gather_609": { + "sender": "Shape_607", + "receiver": "Gather_609", + "sender_port": "_607", + "receiver_port": "_607" + }, + "Constant_608_Gather_609": { + "sender": "Constant_608", + "receiver": "Gather_609", + "sender_port": "_608", + "receiver_port": "_608" + }, + "Gather_609_Div_617": { + "sender": "Gather_609", + "receiver": "Div_617", + "sender_port": "_609", + "receiver_port": "_609" + }, + "Shape_610_Gather_612": { + "sender": "Shape_610", + "receiver": "Gather_612", + "sender_port": "_610", + "receiver_port": "_610" + }, + "Constant_611_Gather_612": { + "sender": "Constant_611", + "receiver": "Gather_612", + "sender_port": "_611", + "receiver_port": "_611" + }, + "Gather_612_Unsqueeze_628": { + "sender": "Gather_612", + "receiver": "Unsqueeze_628", + "sender_port": "_612", + "receiver_port": "_612" + }, + "Gather_612_Unsqueeze_640": { + "sender": "Gather_612", + "receiver": "Unsqueeze_640", + "sender_port": "_612", + "receiver_port": "_612" + }, + "Shape_613_Gather_615": { + "sender": "Shape_613", + "receiver": "Gather_615", + "sender_port": "_613", + "receiver_port": "_613" + }, + "Constant_614_Gather_615": { + "sender": "Constant_614", + "receiver": "Gather_615", + "sender_port": "_614", + "receiver_port": "_614" + }, + "Gather_615_Unsqueeze_630": { + "sender": "Gather_615", + "receiver": "Unsqueeze_630", + "sender_port": "_615", + "receiver_port": "_615" + }, + "Gather_615_Unsqueeze_642": { + "sender": "Gather_615", + "receiver": "Unsqueeze_642", + "sender_port": "_615", + "receiver_port": "_615" + }, + "Constant_616_Div_617": { + "sender": "Constant_616", + "receiver": "Div_617", + "sender_port": "_616", + "receiver_port": "_616" + }, + "Div_617_Cast_618": { + "sender": "Div_617", + "receiver": "Cast_618", + "sender_port": "_617", + "receiver_port": "_617" + }, + "Cast_618_Cast_619": { + "sender": "Cast_618", + "receiver": "Cast_619", + "sender_port": "_618", + "receiver_port": "_618" + }, + "Cast_619_Unsqueeze_626": { + "sender": "Cast_619", + "receiver": "Unsqueeze_626", + "sender_port": "_619", + "receiver_port": "_619" + }, + "Constant_620_Unsqueeze_624": { + "sender": "Constant_620", + "receiver": "Unsqueeze_624", + "sender_port": "_620", + "receiver_port": "_620" + }, + "Constant_621_Unsqueeze_622": { + "sender": "Constant_621", + "receiver": "Unsqueeze_622", + "sender_port": "_621", + "receiver_port": "_621" + }, + "Unsqueeze_622_Concat_631": { + "sender": "Unsqueeze_622", + "receiver": "Concat_631", + "sender_port": "_622", + "receiver_port": "_622" + }, + "Constant_623_Unsqueeze_624": { + "sender": "Constant_623", + "receiver": "Unsqueeze_624", + "sender_port": "_623", + "receiver_port": "_623" + }, + "Unsqueeze_624_Concat_631": { + "sender": "Unsqueeze_624", + "receiver": "Concat_631", + "sender_port": "_624", + "receiver_port": "_624" + }, + "Constant_625_Unsqueeze_626": { + "sender": "Constant_625", + "receiver": "Unsqueeze_626", + "sender_port": "_625", + "receiver_port": "_625" + }, + "Unsqueeze_626_Concat_631": { + "sender": "Unsqueeze_626", + "receiver": "Concat_631", + "sender_port": "_626", + "receiver_port": "_626" + }, + "Constant_627_Unsqueeze_628": { + "sender": "Constant_627", + "receiver": "Unsqueeze_628", + "sender_port": "_627", + "receiver_port": "_627" + }, + "Unsqueeze_628_Concat_631": { + "sender": "Unsqueeze_628", + "receiver": "Concat_631", + "sender_port": "_628", + "receiver_port": "_628" + }, + "Constant_629_Unsqueeze_630": { + "sender": "Constant_629", + "receiver": "Unsqueeze_630", + "sender_port": "_629", + "receiver_port": "_629" + }, + "Unsqueeze_630_Concat_631": { + "sender": "Unsqueeze_630", + "receiver": "Concat_631", + "sender_port": "_630", + "receiver_port": "_630" + }, + "Concat_631_Reshape_632": { + "sender": "Concat_631", + "receiver": "Reshape_632", + "sender_port": "_631", + "receiver_port": "_631" + }, + "Reshape_632_Transpose_633": { + "sender": "Reshape_632", + "receiver": "Transpose_633", + "sender_port": "_632", + "receiver_port": "_632" + }, + "Transpose_633_Reshape_644": { + "sender": "Transpose_633", + "receiver": "Reshape_644", + "sender_port": "_633", + "receiver_port": "_633" + }, + "Constant_634_Unsqueeze_638": { + "sender": "Constant_634", + "receiver": "Unsqueeze_638", + "sender_port": "_634", + "receiver_port": "_634" + }, + "Constant_635_Unsqueeze_636": { + "sender": "Constant_635", + "receiver": "Unsqueeze_636", + "sender_port": "_635", + "receiver_port": "_635" + }, + "Unsqueeze_636_Concat_643": { + "sender": "Unsqueeze_636", + "receiver": "Concat_643", + "sender_port": "_636", + "receiver_port": "_636" + }, + "Constant_637_Unsqueeze_638": { + "sender": "Constant_637", + "receiver": "Unsqueeze_638", + "sender_port": "_637", + "receiver_port": "_637" + }, + "Unsqueeze_638_Concat_643": { + "sender": "Unsqueeze_638", + "receiver": "Concat_643", + "sender_port": "_638", + "receiver_port": "_638" + }, + "Constant_639_Unsqueeze_640": { + "sender": "Constant_639", + "receiver": "Unsqueeze_640", + "sender_port": "_639", + "receiver_port": "_639" + }, + "Unsqueeze_640_Concat_643": { + "sender": "Unsqueeze_640", + "receiver": "Concat_643", + "sender_port": "_640", + "receiver_port": "_640" + }, + "Constant_641_Unsqueeze_642": { + "sender": "Constant_641", + "receiver": "Unsqueeze_642", + "sender_port": "_641", + "receiver_port": "_641" + }, + "Unsqueeze_642_Concat_643": { + "sender": "Unsqueeze_642", + "receiver": "Concat_643", + "sender_port": "_642", + "receiver_port": "_642" + }, + "Concat_643_Reshape_644": { + "sender": "Concat_643", + "receiver": "Reshape_644", + "sender_port": "_643", + "receiver_port": "_643" + }, + "Reshape_644_Shape_645": { + "sender": "Reshape_644", + "receiver": "Shape_645", + "sender_port": "_644", + "receiver_port": "_644" + }, + "Reshape_644_Slice_655": { + "sender": "Reshape_644", + "receiver": "Slice_655", + "sender_port": "_644", + "receiver_port": "_644" + }, + "Reshape_644_Slice_658": { + "sender": "Reshape_644", + "receiver": "Slice_658", + "sender_port": "_644", + "receiver_port": "_644" + }, + "Shape_645_Gather_647": { + "sender": "Shape_645", + "receiver": "Gather_647", + "sender_port": "_645", + "receiver_port": "_645" + }, + "Constant_646_Gather_647": { + "sender": "Constant_646", + "receiver": "Gather_647", + "sender_port": "_646", + "receiver_port": "_646" + }, + "Constant_646_Slice_655": { + "sender": "Constant_646", + "receiver": "Slice_655", + "sender_port": "_646", + "receiver_port": "_646" + }, + "Constant_646_Slice_658": { + "sender": "Constant_646", + "receiver": "Slice_658", + "sender_port": "_646", + "receiver_port": "_646" + }, + "Gather_647_Add_650": { + "sender": "Gather_647", + "receiver": "Add_650", + "sender_port": "_647", + "receiver_port": "_647" + }, + "Constant_648_Slice_655": { + "sender": "Constant_648", + "receiver": "Slice_655", + "sender_port": "_648", + "receiver_port": "_648" + }, + "Constant_649_Add_650": { + "sender": "Constant_649", + "receiver": "Add_650", + "sender_port": "_649", + "receiver_port": "_649" + }, + "Add_650_Div_652": { + "sender": "Add_650", + "receiver": "Div_652", + "sender_port": "_650", + "receiver_port": "_650" + }, + "Constant_651_Div_652": { + "sender": "Constant_651", + "receiver": "Div_652", + "sender_port": "_651", + "receiver_port": "_651" + }, + "Div_652_Mul_654": { + "sender": "Div_652", + "receiver": "Mul_654", + "sender_port": "_652", + "receiver_port": "_652" + }, + "Div_652_Mul_657": { + "sender": "Div_652", + "receiver": "Mul_657", + "sender_port": "_652", + "receiver_port": "_652" + }, + "Constant_653_Mul_654": { + "sender": "Constant_653", + "receiver": "Mul_654", + "sender_port": "_653", + "receiver_port": "_653" + }, + "Mul_654_Slice_655": { + "sender": "Mul_654", + "receiver": "Slice_655", + "sender_port": "_654", + "receiver_port": "_654" + }, + "Mul_654_Slice_658": { + "sender": "Mul_654", + "receiver": "Slice_658", + "sender_port": "_654", + "receiver_port": "_654" + }, + "Slice_655_Concat_667": { + "sender": "Slice_655", + "receiver": "Concat_667", + "sender_port": "_655", + "receiver_port": "_655" + }, + "Constant_656_Mul_657": { + "sender": "Constant_656", + "receiver": "Mul_657", + "sender_port": "_656", + "receiver_port": "_656" + }, + "Mul_657_Slice_658": { + "sender": "Mul_657", + "receiver": "Slice_658", + "sender_port": "_657", + "receiver_port": "_657" + }, + "Slice_658_Conv_1405": { + "sender": "Slice_658", + "receiver": "Conv_1405", + "sender_port": "_658", + "receiver_port": "_658" + }, + "Conv_1405_Relu_661": { + "sender": "Conv_1405", + "receiver": "Relu_661", + "sender_port": "_1405", + "receiver_port": "_1405" + }, + "Relu_661_Conv_1408": { + "sender": "Relu_661", + "receiver": "Conv_1408", + "sender_port": "_661", + "receiver_port": "_661" + }, + "Conv_1408_Conv_1411": { + "sender": "Conv_1408", + "receiver": "Conv_1411", + "sender_port": "_1408", + "receiver_port": "_1408" + }, + "Conv_1411_Relu_666": { + "sender": "Conv_1411", + "receiver": "Relu_666", + "sender_port": "_1411", + "receiver_port": "_1411" + }, + "Relu_666_Concat_667": { + "sender": "Relu_666", + "receiver": "Concat_667", + "sender_port": "_666", + "receiver_port": "_666" + }, + "Concat_667_Shape_668": { + "sender": "Concat_667", + "receiver": "Shape_668", + "sender_port": "_667", + "receiver_port": "_667" + }, + "Concat_667_Shape_671": { + "sender": "Concat_667", + "receiver": "Shape_671", + "sender_port": "_667", + "receiver_port": "_667" + }, + "Concat_667_Shape_674": { + "sender": "Concat_667", + "receiver": "Shape_674", + "sender_port": "_667", + "receiver_port": "_667" + }, + "Concat_667_Shape_677": { + "sender": "Concat_667", + "receiver": "Shape_677", + "sender_port": "_667", + "receiver_port": "_667" + }, + "Concat_667_Reshape_696": { + "sender": "Concat_667", + "receiver": "Reshape_696", + "sender_port": "_667", + "receiver_port": "_667" + }, + "Shape_668_Gather_670": { + "sender": "Shape_668", + "receiver": "Gather_670", + "sender_port": "_668", + "receiver_port": "_668" + }, + "Constant_669_Gather_670": { + "sender": "Constant_669", + "receiver": "Gather_670", + "sender_port": "_669", + "receiver_port": "_669" + }, + "Gather_670_Unsqueeze_686": { + "sender": "Gather_670", + "receiver": "Unsqueeze_686", + "sender_port": "_670", + "receiver_port": "_670" + }, + "Gather_670_Unsqueeze_700": { + "sender": "Gather_670", + "receiver": "Unsqueeze_700", + "sender_port": "_670", + "receiver_port": "_670" + }, + "Shape_671_Gather_673": { + "sender": "Shape_671", + "receiver": "Gather_673", + "sender_port": "_671", + "receiver_port": "_671" + }, + "Constant_672_Gather_673": { + "sender": "Constant_672", + "receiver": "Gather_673", + "sender_port": "_672", + "receiver_port": "_672" + }, + "Gather_673_Div_681": { + "sender": "Gather_673", + "receiver": "Div_681", + "sender_port": "_673", + "receiver_port": "_673" + }, + "Shape_674_Gather_676": { + "sender": "Shape_674", + "receiver": "Gather_676", + "sender_port": "_674", + "receiver_port": "_674" + }, + "Constant_675_Gather_676": { + "sender": "Constant_675", + "receiver": "Gather_676", + "sender_port": "_675", + "receiver_port": "_675" + }, + "Gather_676_Unsqueeze_692": { + "sender": "Gather_676", + "receiver": "Unsqueeze_692", + "sender_port": "_676", + "receiver_port": "_676" + }, + "Gather_676_Unsqueeze_704": { + "sender": "Gather_676", + "receiver": "Unsqueeze_704", + "sender_port": "_676", + "receiver_port": "_676" + }, + "Shape_677_Gather_679": { + "sender": "Shape_677", + "receiver": "Gather_679", + "sender_port": "_677", + "receiver_port": "_677" + }, + "Constant_678_Gather_679": { + "sender": "Constant_678", + "receiver": "Gather_679", + "sender_port": "_678", + "receiver_port": "_678" + }, + "Gather_679_Unsqueeze_694": { + "sender": "Gather_679", + "receiver": "Unsqueeze_694", + "sender_port": "_679", + "receiver_port": "_679" + }, + "Gather_679_Unsqueeze_706": { + "sender": "Gather_679", + "receiver": "Unsqueeze_706", + "sender_port": "_679", + "receiver_port": "_679" + }, + "Constant_680_Div_681": { + "sender": "Constant_680", + "receiver": "Div_681", + "sender_port": "_680", + "receiver_port": "_680" + }, + "Div_681_Cast_682": { + "sender": "Div_681", + "receiver": "Cast_682", + "sender_port": "_681", + "receiver_port": "_681" + }, + "Cast_682_Cast_683": { + "sender": "Cast_682", + "receiver": "Cast_683", + "sender_port": "_682", + "receiver_port": "_682" + }, + "Cast_683_Unsqueeze_690": { + "sender": "Cast_683", + "receiver": "Unsqueeze_690", + "sender_port": "_683", + "receiver_port": "_683" + }, + "Constant_684_Unsqueeze_688": { + "sender": "Constant_684", + "receiver": "Unsqueeze_688", + "sender_port": "_684", + "receiver_port": "_684" + }, + "Constant_685_Unsqueeze_686": { + "sender": "Constant_685", + "receiver": "Unsqueeze_686", + "sender_port": "_685", + "receiver_port": "_685" + }, + "Unsqueeze_686_Concat_695": { + "sender": "Unsqueeze_686", + "receiver": "Concat_695", + "sender_port": "_686", + "receiver_port": "_686" + }, + "Constant_687_Unsqueeze_688": { + "sender": "Constant_687", + "receiver": "Unsqueeze_688", + "sender_port": "_687", + "receiver_port": "_687" + }, + "Unsqueeze_688_Concat_695": { + "sender": "Unsqueeze_688", + "receiver": "Concat_695", + "sender_port": "_688", + "receiver_port": "_688" + }, + "Constant_689_Unsqueeze_690": { + "sender": "Constant_689", + "receiver": "Unsqueeze_690", + "sender_port": "_689", + "receiver_port": "_689" + }, + "Unsqueeze_690_Concat_695": { + "sender": "Unsqueeze_690", + "receiver": "Concat_695", + "sender_port": "_690", + "receiver_port": "_690" + }, + "Constant_691_Unsqueeze_692": { + "sender": "Constant_691", + "receiver": "Unsqueeze_692", + "sender_port": "_691", + "receiver_port": "_691" + }, + "Unsqueeze_692_Concat_695": { + "sender": "Unsqueeze_692", + "receiver": "Concat_695", + "sender_port": "_692", + "receiver_port": "_692" + }, + "Constant_693_Unsqueeze_694": { + "sender": "Constant_693", + "receiver": "Unsqueeze_694", + "sender_port": "_693", + "receiver_port": "_693" + }, + "Unsqueeze_694_Concat_695": { + "sender": "Unsqueeze_694", + "receiver": "Concat_695", + "sender_port": "_694", + "receiver_port": "_694" + }, + "Concat_695_Reshape_696": { + "sender": "Concat_695", + "receiver": "Reshape_696", + "sender_port": "_695", + "receiver_port": "_695" + }, + "Reshape_696_Transpose_697": { + "sender": "Reshape_696", + "receiver": "Transpose_697", + "sender_port": "_696", + "receiver_port": "_696" + }, + "Transpose_697_Reshape_708": { + "sender": "Transpose_697", + "receiver": "Reshape_708", + "sender_port": "_697", + "receiver_port": "_697" + }, + "Constant_698_Unsqueeze_702": { + "sender": "Constant_698", + "receiver": "Unsqueeze_702", + "sender_port": "_698", + "receiver_port": "_698" + }, + "Constant_699_Unsqueeze_700": { + "sender": "Constant_699", + "receiver": "Unsqueeze_700", + "sender_port": "_699", + "receiver_port": "_699" + }, + "Unsqueeze_700_Concat_707": { + "sender": "Unsqueeze_700", + "receiver": "Concat_707", + "sender_port": "_700", + "receiver_port": "_700" + }, + "Constant_701_Unsqueeze_702": { + "sender": "Constant_701", + "receiver": "Unsqueeze_702", + "sender_port": "_701", + "receiver_port": "_701" + }, + "Unsqueeze_702_Concat_707": { + "sender": "Unsqueeze_702", + "receiver": "Concat_707", + "sender_port": "_702", + "receiver_port": "_702" + }, + "Constant_703_Unsqueeze_704": { + "sender": "Constant_703", + "receiver": "Unsqueeze_704", + "sender_port": "_703", + "receiver_port": "_703" + }, + "Unsqueeze_704_Concat_707": { + "sender": "Unsqueeze_704", + "receiver": "Concat_707", + "sender_port": "_704", + "receiver_port": "_704" + }, + "Constant_705_Unsqueeze_706": { + "sender": "Constant_705", + "receiver": "Unsqueeze_706", + "sender_port": "_705", + "receiver_port": "_705" + }, + "Unsqueeze_706_Concat_707": { + "sender": "Unsqueeze_706", + "receiver": "Concat_707", + "sender_port": "_706", + "receiver_port": "_706" + }, + "Concat_707_Reshape_708": { + "sender": "Concat_707", + "receiver": "Reshape_708", + "sender_port": "_707", + "receiver_port": "_707" + }, + "Reshape_708_Shape_709": { + "sender": "Reshape_708", + "receiver": "Shape_709", + "sender_port": "_708", + "receiver_port": "_708" + }, + "Reshape_708_Slice_719": { + "sender": "Reshape_708", + "receiver": "Slice_719", + "sender_port": "_708", + "receiver_port": "_708" + }, + "Reshape_708_Slice_722": { + "sender": "Reshape_708", + "receiver": "Slice_722", + "sender_port": "_708", + "receiver_port": "_708" + }, + "Shape_709_Gather_711": { + "sender": "Shape_709", + "receiver": "Gather_711", + "sender_port": "_709", + "receiver_port": "_709" + }, + "Constant_710_Gather_711": { + "sender": "Constant_710", + "receiver": "Gather_711", + "sender_port": "_710", + "receiver_port": "_710" + }, + "Constant_710_Slice_719": { + "sender": "Constant_710", + "receiver": "Slice_719", + "sender_port": "_710", + "receiver_port": "_710" + }, + "Constant_710_Slice_722": { + "sender": "Constant_710", + "receiver": "Slice_722", + "sender_port": "_710", + "receiver_port": "_710" + }, + "Gather_711_Add_714": { + "sender": "Gather_711", + "receiver": "Add_714", + "sender_port": "_711", + "receiver_port": "_711" + }, + "Constant_712_Slice_719": { + "sender": "Constant_712", + "receiver": "Slice_719", + "sender_port": "_712", + "receiver_port": "_712" + }, + "Constant_713_Add_714": { + "sender": "Constant_713", + "receiver": "Add_714", + "sender_port": "_713", + "receiver_port": "_713" + }, + "Add_714_Div_716": { + "sender": "Add_714", + "receiver": "Div_716", + "sender_port": "_714", + "receiver_port": "_714" + }, + "Constant_715_Div_716": { + "sender": "Constant_715", + "receiver": "Div_716", + "sender_port": "_715", + "receiver_port": "_715" + }, + "Div_716_Mul_718": { + "sender": "Div_716", + "receiver": "Mul_718", + "sender_port": "_716", + "receiver_port": "_716" + }, + "Div_716_Mul_721": { + "sender": "Div_716", + "receiver": "Mul_721", + "sender_port": "_716", + "receiver_port": "_716" + }, + "Constant_717_Mul_718": { + "sender": "Constant_717", + "receiver": "Mul_718", + "sender_port": "_717", + "receiver_port": "_717" + }, + "Mul_718_Slice_719": { + "sender": "Mul_718", + "receiver": "Slice_719", + "sender_port": "_718", + "receiver_port": "_718" + }, + "Mul_718_Slice_722": { + "sender": "Mul_718", + "receiver": "Slice_722", + "sender_port": "_718", + "receiver_port": "_718" + }, + "Slice_719_Concat_731": { + "sender": "Slice_719", + "receiver": "Concat_731", + "sender_port": "_719", + "receiver_port": "_719" + }, + "Constant_720_Mul_721": { + "sender": "Constant_720", + "receiver": "Mul_721", + "sender_port": "_720", + "receiver_port": "_720" + }, + "Mul_721_Slice_722": { + "sender": "Mul_721", + "receiver": "Slice_722", + "sender_port": "_721", + "receiver_port": "_721" + }, + "Slice_722_Conv_1414": { + "sender": "Slice_722", + "receiver": "Conv_1414", + "sender_port": "_722", + "receiver_port": "_722" + }, + "Conv_1414_Relu_725": { + "sender": "Conv_1414", + "receiver": "Relu_725", + "sender_port": "_1414", + "receiver_port": "_1414" + }, + "Relu_725_Conv_1417": { + "sender": "Relu_725", + "receiver": "Conv_1417", + "sender_port": "_725", + "receiver_port": "_725" + }, + "Conv_1417_Conv_1420": { + "sender": "Conv_1417", + "receiver": "Conv_1420", + "sender_port": "_1417", + "receiver_port": "_1417" + }, + "Conv_1420_Relu_730": { + "sender": "Conv_1420", + "receiver": "Relu_730", + "sender_port": "_1420", + "receiver_port": "_1420" + }, + "Relu_730_Concat_731": { + "sender": "Relu_730", + "receiver": "Concat_731", + "sender_port": "_730", + "receiver_port": "_730" + }, + "Concat_731_Shape_732": { + "sender": "Concat_731", + "receiver": "Shape_732", + "sender_port": "_731", + "receiver_port": "_731" + }, + "Concat_731_Shape_735": { + "sender": "Concat_731", + "receiver": "Shape_735", + "sender_port": "_731", + "receiver_port": "_731" + }, + "Concat_731_Shape_738": { + "sender": "Concat_731", + "receiver": "Shape_738", + "sender_port": "_731", + "receiver_port": "_731" + }, + "Concat_731_Shape_741": { + "sender": "Concat_731", + "receiver": "Shape_741", + "sender_port": "_731", + "receiver_port": "_731" + }, + "Concat_731_Reshape_760": { + "sender": "Concat_731", + "receiver": "Reshape_760", + "sender_port": "_731", + "receiver_port": "_731" + }, + "Shape_732_Gather_734": { + "sender": "Shape_732", + "receiver": "Gather_734", + "sender_port": "_732", + "receiver_port": "_732" + }, + "Constant_733_Gather_734": { + "sender": "Constant_733", + "receiver": "Gather_734", + "sender_port": "_733", + "receiver_port": "_733" + }, + "Gather_734_Unsqueeze_750": { + "sender": "Gather_734", + "receiver": "Unsqueeze_750", + "sender_port": "_734", + "receiver_port": "_734" + }, + "Gather_734_Unsqueeze_764": { + "sender": "Gather_734", + "receiver": "Unsqueeze_764", + "sender_port": "_734", + "receiver_port": "_734" + }, + "Shape_735_Gather_737": { + "sender": "Shape_735", + "receiver": "Gather_737", + "sender_port": "_735", + "receiver_port": "_735" + }, + "Constant_736_Gather_737": { + "sender": "Constant_736", + "receiver": "Gather_737", + "sender_port": "_736", + "receiver_port": "_736" + }, + "Gather_737_Div_745": { + "sender": "Gather_737", + "receiver": "Div_745", + "sender_port": "_737", + "receiver_port": "_737" + }, + "Shape_738_Gather_740": { + "sender": "Shape_738", + "receiver": "Gather_740", + "sender_port": "_738", + "receiver_port": "_738" + }, + "Constant_739_Gather_740": { + "sender": "Constant_739", + "receiver": "Gather_740", + "sender_port": "_739", + "receiver_port": "_739" + }, + "Gather_740_Unsqueeze_756": { + "sender": "Gather_740", + "receiver": "Unsqueeze_756", + "sender_port": "_740", + "receiver_port": "_740" + }, + "Gather_740_Unsqueeze_768": { + "sender": "Gather_740", + "receiver": "Unsqueeze_768", + "sender_port": "_740", + "receiver_port": "_740" + }, + "Shape_741_Gather_743": { + "sender": "Shape_741", + "receiver": "Gather_743", + "sender_port": "_741", + "receiver_port": "_741" + }, + "Constant_742_Gather_743": { + "sender": "Constant_742", + "receiver": "Gather_743", + "sender_port": "_742", + "receiver_port": "_742" + }, + "Gather_743_Unsqueeze_758": { + "sender": "Gather_743", + "receiver": "Unsqueeze_758", + "sender_port": "_743", + "receiver_port": "_743" + }, + "Gather_743_Unsqueeze_770": { + "sender": "Gather_743", + "receiver": "Unsqueeze_770", + "sender_port": "_743", + "receiver_port": "_743" + }, + "Constant_744_Div_745": { + "sender": "Constant_744", + "receiver": "Div_745", + "sender_port": "_744", + "receiver_port": "_744" + }, + "Div_745_Cast_746": { + "sender": "Div_745", + "receiver": "Cast_746", + "sender_port": "_745", + "receiver_port": "_745" + }, + "Cast_746_Cast_747": { + "sender": "Cast_746", + "receiver": "Cast_747", + "sender_port": "_746", + "receiver_port": "_746" + }, + "Cast_747_Unsqueeze_754": { + "sender": "Cast_747", + "receiver": "Unsqueeze_754", + "sender_port": "_747", + "receiver_port": "_747" + }, + "Constant_748_Unsqueeze_752": { + "sender": "Constant_748", + "receiver": "Unsqueeze_752", + "sender_port": "_748", + "receiver_port": "_748" + }, + "Constant_749_Unsqueeze_750": { + "sender": "Constant_749", + "receiver": "Unsqueeze_750", + "sender_port": "_749", + "receiver_port": "_749" + }, + "Unsqueeze_750_Concat_759": { + "sender": "Unsqueeze_750", + "receiver": "Concat_759", + "sender_port": "_750", + "receiver_port": "_750" + }, + "Constant_751_Unsqueeze_752": { + "sender": "Constant_751", + "receiver": "Unsqueeze_752", + "sender_port": "_751", + "receiver_port": "_751" + }, + "Unsqueeze_752_Concat_759": { + "sender": "Unsqueeze_752", + "receiver": "Concat_759", + "sender_port": "_752", + "receiver_port": "_752" + }, + "Constant_753_Unsqueeze_754": { + "sender": "Constant_753", + "receiver": "Unsqueeze_754", + "sender_port": "_753", + "receiver_port": "_753" + }, + "Unsqueeze_754_Concat_759": { + "sender": "Unsqueeze_754", + "receiver": "Concat_759", + "sender_port": "_754", + "receiver_port": "_754" + }, + "Constant_755_Unsqueeze_756": { + "sender": "Constant_755", + "receiver": "Unsqueeze_756", + "sender_port": "_755", + "receiver_port": "_755" + }, + "Unsqueeze_756_Concat_759": { + "sender": "Unsqueeze_756", + "receiver": "Concat_759", + "sender_port": "_756", + "receiver_port": "_756" + }, + "Constant_757_Unsqueeze_758": { + "sender": "Constant_757", + "receiver": "Unsqueeze_758", + "sender_port": "_757", + "receiver_port": "_757" + }, + "Unsqueeze_758_Concat_759": { + "sender": "Unsqueeze_758", + "receiver": "Concat_759", + "sender_port": "_758", + "receiver_port": "_758" + }, + "Concat_759_Reshape_760": { + "sender": "Concat_759", + "receiver": "Reshape_760", + "sender_port": "_759", + "receiver_port": "_759" + }, + "Reshape_760_Transpose_761": { + "sender": "Reshape_760", + "receiver": "Transpose_761", + "sender_port": "_760", + "receiver_port": "_760" + }, + "Transpose_761_Reshape_772": { + "sender": "Transpose_761", + "receiver": "Reshape_772", + "sender_port": "_761", + "receiver_port": "_761" + }, + "Constant_762_Unsqueeze_766": { + "sender": "Constant_762", + "receiver": "Unsqueeze_766", + "sender_port": "_762", + "receiver_port": "_762" + }, + "Constant_763_Unsqueeze_764": { + "sender": "Constant_763", + "receiver": "Unsqueeze_764", + "sender_port": "_763", + "receiver_port": "_763" + }, + "Unsqueeze_764_Concat_771": { + "sender": "Unsqueeze_764", + "receiver": "Concat_771", + "sender_port": "_764", + "receiver_port": "_764" + }, + "Constant_765_Unsqueeze_766": { + "sender": "Constant_765", + "receiver": "Unsqueeze_766", + "sender_port": "_765", + "receiver_port": "_765" + }, + "Unsqueeze_766_Concat_771": { + "sender": "Unsqueeze_766", + "receiver": "Concat_771", + "sender_port": "_766", + "receiver_port": "_766" + }, + "Constant_767_Unsqueeze_768": { + "sender": "Constant_767", + "receiver": "Unsqueeze_768", + "sender_port": "_767", + "receiver_port": "_767" + }, + "Unsqueeze_768_Concat_771": { + "sender": "Unsqueeze_768", + "receiver": "Concat_771", + "sender_port": "_768", + "receiver_port": "_768" + }, + "Constant_769_Unsqueeze_770": { + "sender": "Constant_769", + "receiver": "Unsqueeze_770", + "sender_port": "_769", + "receiver_port": "_769" + }, + "Unsqueeze_770_Concat_771": { + "sender": "Unsqueeze_770", + "receiver": "Concat_771", + "sender_port": "_770", + "receiver_port": "_770" + }, + "Concat_771_Reshape_772": { + "sender": "Concat_771", + "receiver": "Reshape_772", + "sender_port": "_771", + "receiver_port": "_771" + }, + "Reshape_772_Shape_773": { + "sender": "Reshape_772", + "receiver": "Shape_773", + "sender_port": "_772", + "receiver_port": "_772" + }, + "Reshape_772_Slice_783": { + "sender": "Reshape_772", + "receiver": "Slice_783", + "sender_port": "_772", + "receiver_port": "_772" + }, + "Reshape_772_Slice_786": { + "sender": "Reshape_772", + "receiver": "Slice_786", + "sender_port": "_772", + "receiver_port": "_772" + }, + "Shape_773_Gather_775": { + "sender": "Shape_773", + "receiver": "Gather_775", + "sender_port": "_773", + "receiver_port": "_773" + }, + "Constant_774_Gather_775": { + "sender": "Constant_774", + "receiver": "Gather_775", + "sender_port": "_774", + "receiver_port": "_774" + }, + "Constant_774_Slice_783": { + "sender": "Constant_774", + "receiver": "Slice_783", + "sender_port": "_774", + "receiver_port": "_774" + }, + "Constant_774_Slice_786": { + "sender": "Constant_774", + "receiver": "Slice_786", + "sender_port": "_774", + "receiver_port": "_774" + }, + "Gather_775_Add_778": { + "sender": "Gather_775", + "receiver": "Add_778", + "sender_port": "_775", + "receiver_port": "_775" + }, + "Constant_776_Slice_783": { + "sender": "Constant_776", + "receiver": "Slice_783", + "sender_port": "_776", + "receiver_port": "_776" + }, + "Constant_777_Add_778": { + "sender": "Constant_777", + "receiver": "Add_778", + "sender_port": "_777", + "receiver_port": "_777" + }, + "Add_778_Div_780": { + "sender": "Add_778", + "receiver": "Div_780", + "sender_port": "_778", + "receiver_port": "_778" + }, + "Constant_779_Div_780": { + "sender": "Constant_779", + "receiver": "Div_780", + "sender_port": "_779", + "receiver_port": "_779" + }, + "Div_780_Mul_782": { + "sender": "Div_780", + "receiver": "Mul_782", + "sender_port": "_780", + "receiver_port": "_780" + }, + "Div_780_Mul_785": { + "sender": "Div_780", + "receiver": "Mul_785", + "sender_port": "_780", + "receiver_port": "_780" + }, + "Constant_781_Mul_782": { + "sender": "Constant_781", + "receiver": "Mul_782", + "sender_port": "_781", + "receiver_port": "_781" + }, + "Mul_782_Slice_783": { + "sender": "Mul_782", + "receiver": "Slice_783", + "sender_port": "_782", + "receiver_port": "_782" + }, + "Mul_782_Slice_786": { + "sender": "Mul_782", + "receiver": "Slice_786", + "sender_port": "_782", + "receiver_port": "_782" + }, + "Slice_783_Concat_795": { + "sender": "Slice_783", + "receiver": "Concat_795", + "sender_port": "_783", + "receiver_port": "_783" + }, + "Constant_784_Mul_785": { + "sender": "Constant_784", + "receiver": "Mul_785", + "sender_port": "_784", + "receiver_port": "_784" + }, + "Mul_785_Slice_786": { + "sender": "Mul_785", + "receiver": "Slice_786", + "sender_port": "_785", + "receiver_port": "_785" + }, + "Slice_786_Conv_1423": { + "sender": "Slice_786", + "receiver": "Conv_1423", + "sender_port": "_786", + "receiver_port": "_786" + }, + "Conv_1423_Relu_789": { + "sender": "Conv_1423", + "receiver": "Relu_789", + "sender_port": "_1423", + "receiver_port": "_1423" + }, + "Relu_789_Conv_1426": { + "sender": "Relu_789", + "receiver": "Conv_1426", + "sender_port": "_789", + "receiver_port": "_789" + }, + "Conv_1426_Conv_1429": { + "sender": "Conv_1426", + "receiver": "Conv_1429", + "sender_port": "_1426", + "receiver_port": "_1426" + }, + "Conv_1429_Relu_794": { + "sender": "Conv_1429", + "receiver": "Relu_794", + "sender_port": "_1429", + "receiver_port": "_1429" + }, + "Relu_794_Concat_795": { + "sender": "Relu_794", + "receiver": "Concat_795", + "sender_port": "_794", + "receiver_port": "_794" + }, + "Concat_795_Shape_796": { + "sender": "Concat_795", + "receiver": "Shape_796", + "sender_port": "_795", + "receiver_port": "_795" + }, + "Concat_795_Shape_799": { + "sender": "Concat_795", + "receiver": "Shape_799", + "sender_port": "_795", + "receiver_port": "_795" + }, + "Concat_795_Shape_802": { + "sender": "Concat_795", + "receiver": "Shape_802", + "sender_port": "_795", + "receiver_port": "_795" + }, + "Concat_795_Shape_805": { + "sender": "Concat_795", + "receiver": "Shape_805", + "sender_port": "_795", + "receiver_port": "_795" + }, + "Concat_795_Reshape_824": { + "sender": "Concat_795", + "receiver": "Reshape_824", + "sender_port": "_795", + "receiver_port": "_795" + }, + "Shape_796_Gather_798": { + "sender": "Shape_796", + "receiver": "Gather_798", + "sender_port": "_796", + "receiver_port": "_796" + }, + "Constant_797_Gather_798": { + "sender": "Constant_797", + "receiver": "Gather_798", + "sender_port": "_797", + "receiver_port": "_797" + }, + "Gather_798_Unsqueeze_814": { + "sender": "Gather_798", + "receiver": "Unsqueeze_814", + "sender_port": "_798", + "receiver_port": "_798" + }, + "Gather_798_Unsqueeze_828": { + "sender": "Gather_798", + "receiver": "Unsqueeze_828", + "sender_port": "_798", + "receiver_port": "_798" + }, + "Shape_799_Gather_801": { + "sender": "Shape_799", + "receiver": "Gather_801", + "sender_port": "_799", + "receiver_port": "_799" + }, + "Constant_800_Gather_801": { + "sender": "Constant_800", + "receiver": "Gather_801", + "sender_port": "_800", + "receiver_port": "_800" + }, + "Gather_801_Div_809": { + "sender": "Gather_801", + "receiver": "Div_809", + "sender_port": "_801", + "receiver_port": "_801" + }, + "Shape_802_Gather_804": { + "sender": "Shape_802", + "receiver": "Gather_804", + "sender_port": "_802", + "receiver_port": "_802" + }, + "Constant_803_Gather_804": { + "sender": "Constant_803", + "receiver": "Gather_804", + "sender_port": "_803", + "receiver_port": "_803" + }, + "Gather_804_Unsqueeze_820": { + "sender": "Gather_804", + "receiver": "Unsqueeze_820", + "sender_port": "_804", + "receiver_port": "_804" + }, + "Gather_804_Unsqueeze_832": { + "sender": "Gather_804", + "receiver": "Unsqueeze_832", + "sender_port": "_804", + "receiver_port": "_804" + }, + "Shape_805_Gather_807": { + "sender": "Shape_805", + "receiver": "Gather_807", + "sender_port": "_805", + "receiver_port": "_805" + }, + "Constant_806_Gather_807": { + "sender": "Constant_806", + "receiver": "Gather_807", + "sender_port": "_806", + "receiver_port": "_806" + }, + "Gather_807_Unsqueeze_822": { + "sender": "Gather_807", + "receiver": "Unsqueeze_822", + "sender_port": "_807", + "receiver_port": "_807" + }, + "Gather_807_Unsqueeze_834": { + "sender": "Gather_807", + "receiver": "Unsqueeze_834", + "sender_port": "_807", + "receiver_port": "_807" + }, + "Constant_808_Div_809": { + "sender": "Constant_808", + "receiver": "Div_809", + "sender_port": "_808", + "receiver_port": "_808" + }, + "Div_809_Cast_810": { + "sender": "Div_809", + "receiver": "Cast_810", + "sender_port": "_809", + "receiver_port": "_809" + }, + "Cast_810_Cast_811": { + "sender": "Cast_810", + "receiver": "Cast_811", + "sender_port": "_810", + "receiver_port": "_810" + }, + "Cast_811_Unsqueeze_818": { + "sender": "Cast_811", + "receiver": "Unsqueeze_818", + "sender_port": "_811", + "receiver_port": "_811" + }, + "Constant_812_Unsqueeze_816": { + "sender": "Constant_812", + "receiver": "Unsqueeze_816", + "sender_port": "_812", + "receiver_port": "_812" + }, + "Constant_813_Unsqueeze_814": { + "sender": "Constant_813", + "receiver": "Unsqueeze_814", + "sender_port": "_813", + "receiver_port": "_813" + }, + "Unsqueeze_814_Concat_823": { + "sender": "Unsqueeze_814", + "receiver": "Concat_823", + "sender_port": "_814", + "receiver_port": "_814" + }, + "Constant_815_Unsqueeze_816": { + "sender": "Constant_815", + "receiver": "Unsqueeze_816", + "sender_port": "_815", + "receiver_port": "_815" + }, + "Unsqueeze_816_Concat_823": { + "sender": "Unsqueeze_816", + "receiver": "Concat_823", + "sender_port": "_816", + "receiver_port": "_816" + }, + "Constant_817_Unsqueeze_818": { + "sender": "Constant_817", + "receiver": "Unsqueeze_818", + "sender_port": "_817", + "receiver_port": "_817" + }, + "Unsqueeze_818_Concat_823": { + "sender": "Unsqueeze_818", + "receiver": "Concat_823", + "sender_port": "_818", + "receiver_port": "_818" + }, + "Constant_819_Unsqueeze_820": { + "sender": "Constant_819", + "receiver": "Unsqueeze_820", + "sender_port": "_819", + "receiver_port": "_819" + }, + "Unsqueeze_820_Concat_823": { + "sender": "Unsqueeze_820", + "receiver": "Concat_823", + "sender_port": "_820", + "receiver_port": "_820" + }, + "Constant_821_Unsqueeze_822": { + "sender": "Constant_821", + "receiver": "Unsqueeze_822", + "sender_port": "_821", + "receiver_port": "_821" + }, + "Unsqueeze_822_Concat_823": { + "sender": "Unsqueeze_822", + "receiver": "Concat_823", + "sender_port": "_822", + "receiver_port": "_822" + }, + "Concat_823_Reshape_824": { + "sender": "Concat_823", + "receiver": "Reshape_824", + "sender_port": "_823", + "receiver_port": "_823" + }, + "Reshape_824_Transpose_825": { + "sender": "Reshape_824", + "receiver": "Transpose_825", + "sender_port": "_824", + "receiver_port": "_824" + }, + "Transpose_825_Reshape_836": { + "sender": "Transpose_825", + "receiver": "Reshape_836", + "sender_port": "_825", + "receiver_port": "_825" + }, + "Constant_826_Unsqueeze_830": { + "sender": "Constant_826", + "receiver": "Unsqueeze_830", + "sender_port": "_826", + "receiver_port": "_826" + }, + "Constant_827_Unsqueeze_828": { + "sender": "Constant_827", + "receiver": "Unsqueeze_828", + "sender_port": "_827", + "receiver_port": "_827" + }, + "Unsqueeze_828_Concat_835": { + "sender": "Unsqueeze_828", + "receiver": "Concat_835", + "sender_port": "_828", + "receiver_port": "_828" + }, + "Constant_829_Unsqueeze_830": { + "sender": "Constant_829", + "receiver": "Unsqueeze_830", + "sender_port": "_829", + "receiver_port": "_829" + }, + "Unsqueeze_830_Concat_835": { + "sender": "Unsqueeze_830", + "receiver": "Concat_835", + "sender_port": "_830", + "receiver_port": "_830" + }, + "Constant_831_Unsqueeze_832": { + "sender": "Constant_831", + "receiver": "Unsqueeze_832", + "sender_port": "_831", + "receiver_port": "_831" + }, + "Unsqueeze_832_Concat_835": { + "sender": "Unsqueeze_832", + "receiver": "Concat_835", + "sender_port": "_832", + "receiver_port": "_832" + }, + "Constant_833_Unsqueeze_834": { + "sender": "Constant_833", + "receiver": "Unsqueeze_834", + "sender_port": "_833", + "receiver_port": "_833" + }, + "Unsqueeze_834_Concat_835": { + "sender": "Unsqueeze_834", + "receiver": "Concat_835", + "sender_port": "_834", + "receiver_port": "_834" + }, + "Concat_835_Reshape_836": { + "sender": "Concat_835", + "receiver": "Reshape_836", + "sender_port": "_835", + "receiver_port": "_835" + }, + "Reshape_836_Shape_837": { + "sender": "Reshape_836", + "receiver": "Shape_837", + "sender_port": "_836", + "receiver_port": "_836" + }, + "Reshape_836_Slice_847": { + "sender": "Reshape_836", + "receiver": "Slice_847", + "sender_port": "_836", + "receiver_port": "_836" + }, + "Reshape_836_Slice_850": { + "sender": "Reshape_836", + "receiver": "Slice_850", + "sender_port": "_836", + "receiver_port": "_836" + }, + "Shape_837_Gather_839": { + "sender": "Shape_837", + "receiver": "Gather_839", + "sender_port": "_837", + "receiver_port": "_837" + }, + "Constant_838_Gather_839": { + "sender": "Constant_838", + "receiver": "Gather_839", + "sender_port": "_838", + "receiver_port": "_838" + }, + "Constant_838_Slice_847": { + "sender": "Constant_838", + "receiver": "Slice_847", + "sender_port": "_838", + "receiver_port": "_838" + }, + "Constant_838_Slice_850": { + "sender": "Constant_838", + "receiver": "Slice_850", + "sender_port": "_838", + "receiver_port": "_838" + }, + "Gather_839_Add_842": { + "sender": "Gather_839", + "receiver": "Add_842", + "sender_port": "_839", + "receiver_port": "_839" + }, + "Constant_840_Slice_847": { + "sender": "Constant_840", + "receiver": "Slice_847", + "sender_port": "_840", + "receiver_port": "_840" + }, + "Constant_841_Add_842": { + "sender": "Constant_841", + "receiver": "Add_842", + "sender_port": "_841", + "receiver_port": "_841" + }, + "Add_842_Div_844": { + "sender": "Add_842", + "receiver": "Div_844", + "sender_port": "_842", + "receiver_port": "_842" + }, + "Constant_843_Div_844": { + "sender": "Constant_843", + "receiver": "Div_844", + "sender_port": "_843", + "receiver_port": "_843" + }, + "Div_844_Mul_846": { + "sender": "Div_844", + "receiver": "Mul_846", + "sender_port": "_844", + "receiver_port": "_844" + }, + "Div_844_Mul_849": { + "sender": "Div_844", + "receiver": "Mul_849", + "sender_port": "_844", + "receiver_port": "_844" + }, + "Constant_845_Mul_846": { + "sender": "Constant_845", + "receiver": "Mul_846", + "sender_port": "_845", + "receiver_port": "_845" + }, + "Mul_846_Slice_847": { + "sender": "Mul_846", + "receiver": "Slice_847", + "sender_port": "_846", + "receiver_port": "_846" + }, + "Mul_846_Slice_850": { + "sender": "Mul_846", + "receiver": "Slice_850", + "sender_port": "_846", + "receiver_port": "_846" + }, + "Slice_847_Concat_859": { + "sender": "Slice_847", + "receiver": "Concat_859", + "sender_port": "_847", + "receiver_port": "_847" + }, + "Constant_848_Mul_849": { + "sender": "Constant_848", + "receiver": "Mul_849", + "sender_port": "_848", + "receiver_port": "_848" + }, + "Mul_849_Slice_850": { + "sender": "Mul_849", + "receiver": "Slice_850", + "sender_port": "_849", + "receiver_port": "_849" + }, + "Slice_850_Conv_1432": { + "sender": "Slice_850", + "receiver": "Conv_1432", + "sender_port": "_850", + "receiver_port": "_850" + }, + "Conv_1432_Relu_853": { + "sender": "Conv_1432", + "receiver": "Relu_853", + "sender_port": "_1432", + "receiver_port": "_1432" + }, + "Relu_853_Conv_1435": { + "sender": "Relu_853", + "receiver": "Conv_1435", + "sender_port": "_853", + "receiver_port": "_853" + }, + "Conv_1435_Conv_1438": { + "sender": "Conv_1435", + "receiver": "Conv_1438", + "sender_port": "_1435", + "receiver_port": "_1435" + }, + "Conv_1438_Relu_858": { + "sender": "Conv_1438", + "receiver": "Relu_858", + "sender_port": "_1438", + "receiver_port": "_1438" + }, + "Relu_858_Concat_859": { + "sender": "Relu_858", + "receiver": "Concat_859", + "sender_port": "_858", + "receiver_port": "_858" + }, + "Concat_859_Shape_860": { + "sender": "Concat_859", + "receiver": "Shape_860", + "sender_port": "_859", + "receiver_port": "_859" + }, + "Concat_859_Shape_863": { + "sender": "Concat_859", + "receiver": "Shape_863", + "sender_port": "_859", + "receiver_port": "_859" + }, + "Concat_859_Shape_866": { + "sender": "Concat_859", + "receiver": "Shape_866", + "sender_port": "_859", + "receiver_port": "_859" + }, + "Concat_859_Shape_869": { + "sender": "Concat_859", + "receiver": "Shape_869", + "sender_port": "_859", + "receiver_port": "_859" + }, + "Concat_859_Reshape_888": { + "sender": "Concat_859", + "receiver": "Reshape_888", + "sender_port": "_859", + "receiver_port": "_859" + }, + "Shape_860_Gather_862": { + "sender": "Shape_860", + "receiver": "Gather_862", + "sender_port": "_860", + "receiver_port": "_860" + }, + "Constant_861_Gather_862": { + "sender": "Constant_861", + "receiver": "Gather_862", + "sender_port": "_861", + "receiver_port": "_861" + }, + "Gather_862_Unsqueeze_878": { + "sender": "Gather_862", + "receiver": "Unsqueeze_878", + "sender_port": "_862", + "receiver_port": "_862" + }, + "Gather_862_Unsqueeze_892": { + "sender": "Gather_862", + "receiver": "Unsqueeze_892", + "sender_port": "_862", + "receiver_port": "_862" + }, + "Shape_863_Gather_865": { + "sender": "Shape_863", + "receiver": "Gather_865", + "sender_port": "_863", + "receiver_port": "_863" + }, + "Constant_864_Gather_865": { + "sender": "Constant_864", + "receiver": "Gather_865", + "sender_port": "_864", + "receiver_port": "_864" + }, + "Gather_865_Div_873": { + "sender": "Gather_865", + "receiver": "Div_873", + "sender_port": "_865", + "receiver_port": "_865" + }, + "Shape_866_Gather_868": { + "sender": "Shape_866", + "receiver": "Gather_868", + "sender_port": "_866", + "receiver_port": "_866" + }, + "Constant_867_Gather_868": { + "sender": "Constant_867", + "receiver": "Gather_868", + "sender_port": "_867", + "receiver_port": "_867" + }, + "Gather_868_Unsqueeze_884": { + "sender": "Gather_868", + "receiver": "Unsqueeze_884", + "sender_port": "_868", + "receiver_port": "_868" + }, + "Gather_868_Unsqueeze_896": { + "sender": "Gather_868", + "receiver": "Unsqueeze_896", + "sender_port": "_868", + "receiver_port": "_868" + }, + "Shape_869_Gather_871": { + "sender": "Shape_869", + "receiver": "Gather_871", + "sender_port": "_869", + "receiver_port": "_869" + }, + "Constant_870_Gather_871": { + "sender": "Constant_870", + "receiver": "Gather_871", + "sender_port": "_870", + "receiver_port": "_870" + }, + "Gather_871_Unsqueeze_886": { + "sender": "Gather_871", + "receiver": "Unsqueeze_886", + "sender_port": "_871", + "receiver_port": "_871" + }, + "Gather_871_Unsqueeze_898": { + "sender": "Gather_871", + "receiver": "Unsqueeze_898", + "sender_port": "_871", + "receiver_port": "_871" + }, + "Constant_872_Div_873": { + "sender": "Constant_872", + "receiver": "Div_873", + "sender_port": "_872", + "receiver_port": "_872" + }, + "Div_873_Cast_874": { + "sender": "Div_873", + "receiver": "Cast_874", + "sender_port": "_873", + "receiver_port": "_873" + }, + "Cast_874_Cast_875": { + "sender": "Cast_874", + "receiver": "Cast_875", + "sender_port": "_874", + "receiver_port": "_874" + }, + "Cast_875_Unsqueeze_882": { + "sender": "Cast_875", + "receiver": "Unsqueeze_882", + "sender_port": "_875", + "receiver_port": "_875" + }, + "Constant_876_Unsqueeze_880": { + "sender": "Constant_876", + "receiver": "Unsqueeze_880", + "sender_port": "_876", + "receiver_port": "_876" + }, + "Constant_877_Unsqueeze_878": { + "sender": "Constant_877", + "receiver": "Unsqueeze_878", + "sender_port": "_877", + "receiver_port": "_877" + }, + "Unsqueeze_878_Concat_887": { + "sender": "Unsqueeze_878", + "receiver": "Concat_887", + "sender_port": "_878", + "receiver_port": "_878" + }, + "Constant_879_Unsqueeze_880": { + "sender": "Constant_879", + "receiver": "Unsqueeze_880", + "sender_port": "_879", + "receiver_port": "_879" + }, + "Unsqueeze_880_Concat_887": { + "sender": "Unsqueeze_880", + "receiver": "Concat_887", + "sender_port": "_880", + "receiver_port": "_880" + }, + "Constant_881_Unsqueeze_882": { + "sender": "Constant_881", + "receiver": "Unsqueeze_882", + "sender_port": "_881", + "receiver_port": "_881" + }, + "Unsqueeze_882_Concat_887": { + "sender": "Unsqueeze_882", + "receiver": "Concat_887", + "sender_port": "_882", + "receiver_port": "_882" + }, + "Constant_883_Unsqueeze_884": { + "sender": "Constant_883", + "receiver": "Unsqueeze_884", + "sender_port": "_883", + "receiver_port": "_883" + }, + "Unsqueeze_884_Concat_887": { + "sender": "Unsqueeze_884", + "receiver": "Concat_887", + "sender_port": "_884", + "receiver_port": "_884" + }, + "Constant_885_Unsqueeze_886": { + "sender": "Constant_885", + "receiver": "Unsqueeze_886", + "sender_port": "_885", + "receiver_port": "_885" + }, + "Unsqueeze_886_Concat_887": { + "sender": "Unsqueeze_886", + "receiver": "Concat_887", + "sender_port": "_886", + "receiver_port": "_886" + }, + "Concat_887_Reshape_888": { + "sender": "Concat_887", + "receiver": "Reshape_888", + "sender_port": "_887", + "receiver_port": "_887" + }, + "Reshape_888_Transpose_889": { + "sender": "Reshape_888", + "receiver": "Transpose_889", + "sender_port": "_888", + "receiver_port": "_888" + }, + "Transpose_889_Reshape_900": { + "sender": "Transpose_889", + "receiver": "Reshape_900", + "sender_port": "_889", + "receiver_port": "_889" + }, + "Constant_890_Unsqueeze_894": { + "sender": "Constant_890", + "receiver": "Unsqueeze_894", + "sender_port": "_890", + "receiver_port": "_890" + }, + "Constant_891_Unsqueeze_892": { + "sender": "Constant_891", + "receiver": "Unsqueeze_892", + "sender_port": "_891", + "receiver_port": "_891" + }, + "Unsqueeze_892_Concat_899": { + "sender": "Unsqueeze_892", + "receiver": "Concat_899", + "sender_port": "_892", + "receiver_port": "_892" + }, + "Constant_893_Unsqueeze_894": { + "sender": "Constant_893", + "receiver": "Unsqueeze_894", + "sender_port": "_893", + "receiver_port": "_893" + }, + "Unsqueeze_894_Concat_899": { + "sender": "Unsqueeze_894", + "receiver": "Concat_899", + "sender_port": "_894", + "receiver_port": "_894" + }, + "Constant_895_Unsqueeze_896": { + "sender": "Constant_895", + "receiver": "Unsqueeze_896", + "sender_port": "_895", + "receiver_port": "_895" + }, + "Unsqueeze_896_Concat_899": { + "sender": "Unsqueeze_896", + "receiver": "Concat_899", + "sender_port": "_896", + "receiver_port": "_896" + }, + "Constant_897_Unsqueeze_898": { + "sender": "Constant_897", + "receiver": "Unsqueeze_898", + "sender_port": "_897", + "receiver_port": "_897" + }, + "Unsqueeze_898_Concat_899": { + "sender": "Unsqueeze_898", + "receiver": "Concat_899", + "sender_port": "_898", + "receiver_port": "_898" + }, + "Concat_899_Reshape_900": { + "sender": "Concat_899", + "receiver": "Reshape_900", + "sender_port": "_899", + "receiver_port": "_899" + }, + "Reshape_900_Shape_901": { + "sender": "Reshape_900", + "receiver": "Shape_901", + "sender_port": "_900", + "receiver_port": "_900" + }, + "Reshape_900_Slice_911": { + "sender": "Reshape_900", + "receiver": "Slice_911", + "sender_port": "_900", + "receiver_port": "_900" + }, + "Reshape_900_Slice_914": { + "sender": "Reshape_900", + "receiver": "Slice_914", + "sender_port": "_900", + "receiver_port": "_900" + }, + "Shape_901_Gather_903": { + "sender": "Shape_901", + "receiver": "Gather_903", + "sender_port": "_901", + "receiver_port": "_901" + }, + "Constant_902_Gather_903": { + "sender": "Constant_902", + "receiver": "Gather_903", + "sender_port": "_902", + "receiver_port": "_902" + }, + "Constant_902_Slice_911": { + "sender": "Constant_902", + "receiver": "Slice_911", + "sender_port": "_902", + "receiver_port": "_902" + }, + "Constant_902_Slice_914": { + "sender": "Constant_902", + "receiver": "Slice_914", + "sender_port": "_902", + "receiver_port": "_902" + }, + "Gather_903_Add_906": { + "sender": "Gather_903", + "receiver": "Add_906", + "sender_port": "_903", + "receiver_port": "_903" + }, + "Constant_904_Slice_911": { + "sender": "Constant_904", + "receiver": "Slice_911", + "sender_port": "_904", + "receiver_port": "_904" + }, + "Constant_905_Add_906": { + "sender": "Constant_905", + "receiver": "Add_906", + "sender_port": "_905", + "receiver_port": "_905" + }, + "Add_906_Div_908": { + "sender": "Add_906", + "receiver": "Div_908", + "sender_port": "_906", + "receiver_port": "_906" + }, + "Constant_907_Div_908": { + "sender": "Constant_907", + "receiver": "Div_908", + "sender_port": "_907", + "receiver_port": "_907" + }, + "Div_908_Mul_910": { + "sender": "Div_908", + "receiver": "Mul_910", + "sender_port": "_908", + "receiver_port": "_908" + }, + "Div_908_Mul_913": { + "sender": "Div_908", + "receiver": "Mul_913", + "sender_port": "_908", + "receiver_port": "_908" + }, + "Constant_909_Mul_910": { + "sender": "Constant_909", + "receiver": "Mul_910", + "sender_port": "_909", + "receiver_port": "_909" + }, + "Mul_910_Slice_911": { + "sender": "Mul_910", + "receiver": "Slice_911", + "sender_port": "_910", + "receiver_port": "_910" + }, + "Mul_910_Slice_914": { + "sender": "Mul_910", + "receiver": "Slice_914", + "sender_port": "_910", + "receiver_port": "_910" + }, + "Slice_911_Concat_923": { + "sender": "Slice_911", + "receiver": "Concat_923", + "sender_port": "_911", + "receiver_port": "_911" + }, + "Constant_912_Mul_913": { + "sender": "Constant_912", + "receiver": "Mul_913", + "sender_port": "_912", + "receiver_port": "_912" + }, + "Mul_913_Slice_914": { + "sender": "Mul_913", + "receiver": "Slice_914", + "sender_port": "_913", + "receiver_port": "_913" + }, + "Slice_914_Conv_1441": { + "sender": "Slice_914", + "receiver": "Conv_1441", + "sender_port": "_914", + "receiver_port": "_914" + }, + "Conv_1441_Relu_917": { + "sender": "Conv_1441", + "receiver": "Relu_917", + "sender_port": "_1441", + "receiver_port": "_1441" + }, + "Relu_917_Conv_1444": { + "sender": "Relu_917", + "receiver": "Conv_1444", + "sender_port": "_917", + "receiver_port": "_917" + }, + "Conv_1444_Conv_1447": { + "sender": "Conv_1444", + "receiver": "Conv_1447", + "sender_port": "_1444", + "receiver_port": "_1444" + }, + "Conv_1447_Relu_922": { + "sender": "Conv_1447", + "receiver": "Relu_922", + "sender_port": "_1447", + "receiver_port": "_1447" + }, + "Relu_922_Concat_923": { + "sender": "Relu_922", + "receiver": "Concat_923", + "sender_port": "_922", + "receiver_port": "_922" + }, + "Concat_923_Shape_924": { + "sender": "Concat_923", + "receiver": "Shape_924", + "sender_port": "_923", + "receiver_port": "_923" + }, + "Concat_923_Shape_927": { + "sender": "Concat_923", + "receiver": "Shape_927", + "sender_port": "_923", + "receiver_port": "_923" + }, + "Concat_923_Shape_930": { + "sender": "Concat_923", + "receiver": "Shape_930", + "sender_port": "_923", + "receiver_port": "_923" + }, + "Concat_923_Shape_933": { + "sender": "Concat_923", + "receiver": "Shape_933", + "sender_port": "_923", + "receiver_port": "_923" + }, + "Concat_923_Reshape_952": { + "sender": "Concat_923", + "receiver": "Reshape_952", + "sender_port": "_923", + "receiver_port": "_923" + }, + "Shape_924_Gather_926": { + "sender": "Shape_924", + "receiver": "Gather_926", + "sender_port": "_924", + "receiver_port": "_924" + }, + "Constant_925_Gather_926": { + "sender": "Constant_925", + "receiver": "Gather_926", + "sender_port": "_925", + "receiver_port": "_925" + }, + "Gather_926_Unsqueeze_942": { + "sender": "Gather_926", + "receiver": "Unsqueeze_942", + "sender_port": "_926", + "receiver_port": "_926" + }, + "Gather_926_Unsqueeze_956": { + "sender": "Gather_926", + "receiver": "Unsqueeze_956", + "sender_port": "_926", + "receiver_port": "_926" + }, + "Shape_927_Gather_929": { + "sender": "Shape_927", + "receiver": "Gather_929", + "sender_port": "_927", + "receiver_port": "_927" + }, + "Constant_928_Gather_929": { + "sender": "Constant_928", + "receiver": "Gather_929", + "sender_port": "_928", + "receiver_port": "_928" + }, + "Gather_929_Div_937": { + "sender": "Gather_929", + "receiver": "Div_937", + "sender_port": "_929", + "receiver_port": "_929" + }, + "Shape_930_Gather_932": { + "sender": "Shape_930", + "receiver": "Gather_932", + "sender_port": "_930", + "receiver_port": "_930" + }, + "Constant_931_Gather_932": { + "sender": "Constant_931", + "receiver": "Gather_932", + "sender_port": "_931", + "receiver_port": "_931" + }, + "Gather_932_Unsqueeze_948": { + "sender": "Gather_932", + "receiver": "Unsqueeze_948", + "sender_port": "_932", + "receiver_port": "_932" + }, + "Gather_932_Unsqueeze_960": { + "sender": "Gather_932", + "receiver": "Unsqueeze_960", + "sender_port": "_932", + "receiver_port": "_932" + }, + "Shape_933_Gather_935": { + "sender": "Shape_933", + "receiver": "Gather_935", + "sender_port": "_933", + "receiver_port": "_933" + }, + "Constant_934_Gather_935": { + "sender": "Constant_934", + "receiver": "Gather_935", + "sender_port": "_934", + "receiver_port": "_934" + }, + "Gather_935_Unsqueeze_950": { + "sender": "Gather_935", + "receiver": "Unsqueeze_950", + "sender_port": "_935", + "receiver_port": "_935" + }, + "Gather_935_Unsqueeze_962": { + "sender": "Gather_935", + "receiver": "Unsqueeze_962", + "sender_port": "_935", + "receiver_port": "_935" + }, + "Constant_936_Div_937": { + "sender": "Constant_936", + "receiver": "Div_937", + "sender_port": "_936", + "receiver_port": "_936" + }, + "Div_937_Cast_938": { + "sender": "Div_937", + "receiver": "Cast_938", + "sender_port": "_937", + "receiver_port": "_937" + }, + "Cast_938_Cast_939": { + "sender": "Cast_938", + "receiver": "Cast_939", + "sender_port": "_938", + "receiver_port": "_938" + }, + "Cast_939_Unsqueeze_946": { + "sender": "Cast_939", + "receiver": "Unsqueeze_946", + "sender_port": "_939", + "receiver_port": "_939" + }, + "Constant_940_Unsqueeze_944": { + "sender": "Constant_940", + "receiver": "Unsqueeze_944", + "sender_port": "_940", + "receiver_port": "_940" + }, + "Constant_941_Unsqueeze_942": { + "sender": "Constant_941", + "receiver": "Unsqueeze_942", + "sender_port": "_941", + "receiver_port": "_941" + }, + "Unsqueeze_942_Concat_951": { + "sender": "Unsqueeze_942", + "receiver": "Concat_951", + "sender_port": "_942", + "receiver_port": "_942" + }, + "Constant_943_Unsqueeze_944": { + "sender": "Constant_943", + "receiver": "Unsqueeze_944", + "sender_port": "_943", + "receiver_port": "_943" + }, + "Unsqueeze_944_Concat_951": { + "sender": "Unsqueeze_944", + "receiver": "Concat_951", + "sender_port": "_944", + "receiver_port": "_944" + }, + "Constant_945_Unsqueeze_946": { + "sender": "Constant_945", + "receiver": "Unsqueeze_946", + "sender_port": "_945", + "receiver_port": "_945" + }, + "Unsqueeze_946_Concat_951": { + "sender": "Unsqueeze_946", + "receiver": "Concat_951", + "sender_port": "_946", + "receiver_port": "_946" + }, + "Constant_947_Unsqueeze_948": { + "sender": "Constant_947", + "receiver": "Unsqueeze_948", + "sender_port": "_947", + "receiver_port": "_947" + }, + "Unsqueeze_948_Concat_951": { + "sender": "Unsqueeze_948", + "receiver": "Concat_951", + "sender_port": "_948", + "receiver_port": "_948" + }, + "Constant_949_Unsqueeze_950": { + "sender": "Constant_949", + "receiver": "Unsqueeze_950", + "sender_port": "_949", + "receiver_port": "_949" + }, + "Unsqueeze_950_Concat_951": { + "sender": "Unsqueeze_950", + "receiver": "Concat_951", + "sender_port": "_950", + "receiver_port": "_950" + }, + "Concat_951_Reshape_952": { + "sender": "Concat_951", + "receiver": "Reshape_952", + "sender_port": "_951", + "receiver_port": "_951" + }, + "Reshape_952_Transpose_953": { + "sender": "Reshape_952", + "receiver": "Transpose_953", + "sender_port": "_952", + "receiver_port": "_952" + }, + "Transpose_953_Reshape_964": { + "sender": "Transpose_953", + "receiver": "Reshape_964", + "sender_port": "_953", + "receiver_port": "_953" + }, + "Constant_954_Unsqueeze_958": { + "sender": "Constant_954", + "receiver": "Unsqueeze_958", + "sender_port": "_954", + "receiver_port": "_954" + }, + "Constant_955_Unsqueeze_956": { + "sender": "Constant_955", + "receiver": "Unsqueeze_956", + "sender_port": "_955", + "receiver_port": "_955" + }, + "Unsqueeze_956_Concat_963": { + "sender": "Unsqueeze_956", + "receiver": "Concat_963", + "sender_port": "_956", + "receiver_port": "_956" + }, + "Constant_957_Unsqueeze_958": { + "sender": "Constant_957", + "receiver": "Unsqueeze_958", + "sender_port": "_957", + "receiver_port": "_957" + }, + "Unsqueeze_958_Concat_963": { + "sender": "Unsqueeze_958", + "receiver": "Concat_963", + "sender_port": "_958", + "receiver_port": "_958" + }, + "Constant_959_Unsqueeze_960": { + "sender": "Constant_959", + "receiver": "Unsqueeze_960", + "sender_port": "_959", + "receiver_port": "_959" + }, + "Unsqueeze_960_Concat_963": { + "sender": "Unsqueeze_960", + "receiver": "Concat_963", + "sender_port": "_960", + "receiver_port": "_960" + }, + "Constant_961_Unsqueeze_962": { + "sender": "Constant_961", + "receiver": "Unsqueeze_962", + "sender_port": "_961", + "receiver_port": "_961" + }, + "Unsqueeze_962_Concat_963": { + "sender": "Unsqueeze_962", + "receiver": "Concat_963", + "sender_port": "_962", + "receiver_port": "_962" + }, + "Concat_963_Reshape_964": { + "sender": "Concat_963", + "receiver": "Reshape_964", + "sender_port": "_963", + "receiver_port": "_963" + }, + "Reshape_964_Shape_965": { + "sender": "Reshape_964", + "receiver": "Shape_965", + "sender_port": "_964", + "receiver_port": "_964" + }, + "Reshape_964_Slice_975": { + "sender": "Reshape_964", + "receiver": "Slice_975", + "sender_port": "_964", + "receiver_port": "_964" + }, + "Reshape_964_Slice_978": { + "sender": "Reshape_964", + "receiver": "Slice_978", + "sender_port": "_964", + "receiver_port": "_964" + }, + "Shape_965_Gather_967": { + "sender": "Shape_965", + "receiver": "Gather_967", + "sender_port": "_965", + "receiver_port": "_965" + }, + "Constant_966_Gather_967": { + "sender": "Constant_966", + "receiver": "Gather_967", + "sender_port": "_966", + "receiver_port": "_966" + }, + "Constant_966_Slice_975": { + "sender": "Constant_966", + "receiver": "Slice_975", + "sender_port": "_966", + "receiver_port": "_966" + }, + "Constant_966_Slice_978": { + "sender": "Constant_966", + "receiver": "Slice_978", + "sender_port": "_966", + "receiver_port": "_966" + }, + "Gather_967_Add_970": { + "sender": "Gather_967", + "receiver": "Add_970", + "sender_port": "_967", + "receiver_port": "_967" + }, + "Constant_968_Slice_975": { + "sender": "Constant_968", + "receiver": "Slice_975", + "sender_port": "_968", + "receiver_port": "_968" + }, + "Constant_969_Add_970": { + "sender": "Constant_969", + "receiver": "Add_970", + "sender_port": "_969", + "receiver_port": "_969" + }, + "Add_970_Div_972": { + "sender": "Add_970", + "receiver": "Div_972", + "sender_port": "_970", + "receiver_port": "_970" + }, + "Constant_971_Div_972": { + "sender": "Constant_971", + "receiver": "Div_972", + "sender_port": "_971", + "receiver_port": "_971" + }, + "Div_972_Mul_974": { + "sender": "Div_972", + "receiver": "Mul_974", + "sender_port": "_972", + "receiver_port": "_972" + }, + "Div_972_Mul_977": { + "sender": "Div_972", + "receiver": "Mul_977", + "sender_port": "_972", + "receiver_port": "_972" + }, + "Constant_973_Mul_974": { + "sender": "Constant_973", + "receiver": "Mul_974", + "sender_port": "_973", + "receiver_port": "_973" + }, + "Mul_974_Slice_975": { + "sender": "Mul_974", + "receiver": "Slice_975", + "sender_port": "_974", + "receiver_port": "_974" + }, + "Mul_974_Slice_978": { + "sender": "Mul_974", + "receiver": "Slice_978", + "sender_port": "_974", + "receiver_port": "_974" + }, + "Slice_975_Concat_987": { + "sender": "Slice_975", + "receiver": "Concat_987", + "sender_port": "_975", + "receiver_port": "_975" + }, + "Constant_976_Mul_977": { + "sender": "Constant_976", + "receiver": "Mul_977", + "sender_port": "_976", + "receiver_port": "_976" + }, + "Mul_977_Slice_978": { + "sender": "Mul_977", + "receiver": "Slice_978", + "sender_port": "_977", + "receiver_port": "_977" + }, + "Slice_978_Conv_1450": { + "sender": "Slice_978", + "receiver": "Conv_1450", + "sender_port": "_978", + "receiver_port": "_978" + }, + "Conv_1450_Relu_981": { + "sender": "Conv_1450", + "receiver": "Relu_981", + "sender_port": "_1450", + "receiver_port": "_1450" + }, + "Relu_981_Conv_1453": { + "sender": "Relu_981", + "receiver": "Conv_1453", + "sender_port": "_981", + "receiver_port": "_981" + }, + "Conv_1453_Conv_1456": { + "sender": "Conv_1453", + "receiver": "Conv_1456", + "sender_port": "_1453", + "receiver_port": "_1453" + }, + "Conv_1456_Relu_986": { + "sender": "Conv_1456", + "receiver": "Relu_986", + "sender_port": "_1456", + "receiver_port": "_1456" + }, + "Relu_986_Concat_987": { + "sender": "Relu_986", + "receiver": "Concat_987", + "sender_port": "_986", + "receiver_port": "_986" + }, + "Concat_987_Shape_988": { + "sender": "Concat_987", + "receiver": "Shape_988", + "sender_port": "_987", + "receiver_port": "_987" + }, + "Concat_987_Shape_991": { + "sender": "Concat_987", + "receiver": "Shape_991", + "sender_port": "_987", + "receiver_port": "_987" + }, + "Concat_987_Shape_994": { + "sender": "Concat_987", + "receiver": "Shape_994", + "sender_port": "_987", + "receiver_port": "_987" + }, + "Concat_987_Shape_997": { + "sender": "Concat_987", + "receiver": "Shape_997", + "sender_port": "_987", + "receiver_port": "_987" + }, + "Concat_987_Reshape_1016": { + "sender": "Concat_987", + "receiver": "Reshape_1016", + "sender_port": "_987", + "receiver_port": "_987" + }, + "Shape_988_Gather_990": { + "sender": "Shape_988", + "receiver": "Gather_990", + "sender_port": "_988", + "receiver_port": "_988" + }, + "Constant_989_Gather_990": { + "sender": "Constant_989", + "receiver": "Gather_990", + "sender_port": "_989", + "receiver_port": "_989" + }, + "Gather_990_Unsqueeze_1006": { + "sender": "Gather_990", + "receiver": "Unsqueeze_1006", + "sender_port": "_990", + "receiver_port": "_990" + }, + "Gather_990_Unsqueeze_1020": { + "sender": "Gather_990", + "receiver": "Unsqueeze_1020", + "sender_port": "_990", + "receiver_port": "_990" + }, + "Shape_991_Gather_993": { + "sender": "Shape_991", + "receiver": "Gather_993", + "sender_port": "_991", + "receiver_port": "_991" + }, + "Constant_992_Gather_993": { + "sender": "Constant_992", + "receiver": "Gather_993", + "sender_port": "_992", + "receiver_port": "_992" + }, + "Gather_993_Div_1001": { + "sender": "Gather_993", + "receiver": "Div_1001", + "sender_port": "_993", + "receiver_port": "_993" + }, + "Shape_994_Gather_996": { + "sender": "Shape_994", + "receiver": "Gather_996", + "sender_port": "_994", + "receiver_port": "_994" + }, + "Constant_995_Gather_996": { + "sender": "Constant_995", + "receiver": "Gather_996", + "sender_port": "_995", + "receiver_port": "_995" + }, + "Gather_996_Unsqueeze_1012": { + "sender": "Gather_996", + "receiver": "Unsqueeze_1012", + "sender_port": "_996", + "receiver_port": "_996" + }, + "Gather_996_Unsqueeze_1024": { + "sender": "Gather_996", + "receiver": "Unsqueeze_1024", + "sender_port": "_996", + "receiver_port": "_996" + }, + "Shape_997_Gather_999": { + "sender": "Shape_997", + "receiver": "Gather_999", + "sender_port": "_997", + "receiver_port": "_997" + }, + "Constant_998_Gather_999": { + "sender": "Constant_998", + "receiver": "Gather_999", + "sender_port": "_998", + "receiver_port": "_998" + }, + "Gather_999_Unsqueeze_1014": { + "sender": "Gather_999", + "receiver": "Unsqueeze_1014", + "sender_port": "_999", + "receiver_port": "_999" + }, + "Gather_999_Unsqueeze_1026": { + "sender": "Gather_999", + "receiver": "Unsqueeze_1026", + "sender_port": "_999", + "receiver_port": "_999" + }, + "Constant_1000_Div_1001": { + "sender": "Constant_1000", + "receiver": "Div_1001", + "sender_port": "_1000", + "receiver_port": "_1000" + }, + "Div_1001_Cast_1002": { + "sender": "Div_1001", + "receiver": "Cast_1002", + "sender_port": "_1001", + "receiver_port": "_1001" + }, + "Cast_1002_Cast_1003": { + "sender": "Cast_1002", + "receiver": "Cast_1003", + "sender_port": "_1002", + "receiver_port": "_1002" + }, + "Cast_1003_Unsqueeze_1010": { + "sender": "Cast_1003", + "receiver": "Unsqueeze_1010", + "sender_port": "_1003", + "receiver_port": "_1003" + }, + "Constant_1004_Unsqueeze_1008": { + "sender": "Constant_1004", + "receiver": "Unsqueeze_1008", + "sender_port": "_1004", + "receiver_port": "_1004" + }, + "Constant_1005_Unsqueeze_1006": { + "sender": "Constant_1005", + "receiver": "Unsqueeze_1006", + "sender_port": "_1005", + "receiver_port": "_1005" + }, + "Unsqueeze_1006_Concat_1015": { + "sender": "Unsqueeze_1006", + "receiver": "Concat_1015", + "sender_port": "_1006", + "receiver_port": "_1006" + }, + "Constant_1007_Unsqueeze_1008": { + "sender": "Constant_1007", + "receiver": "Unsqueeze_1008", + "sender_port": "_1007", + "receiver_port": "_1007" + }, + "Unsqueeze_1008_Concat_1015": { + "sender": "Unsqueeze_1008", + "receiver": "Concat_1015", + "sender_port": "_1008", + "receiver_port": "_1008" + }, + "Constant_1009_Unsqueeze_1010": { + "sender": "Constant_1009", + "receiver": "Unsqueeze_1010", + "sender_port": "_1009", + "receiver_port": "_1009" + }, + "Unsqueeze_1010_Concat_1015": { + "sender": "Unsqueeze_1010", + "receiver": "Concat_1015", + "sender_port": "_1010", + "receiver_port": "_1010" + }, + "Constant_1011_Unsqueeze_1012": { + "sender": "Constant_1011", + "receiver": "Unsqueeze_1012", + "sender_port": "_1011", + "receiver_port": "_1011" + }, + "Unsqueeze_1012_Concat_1015": { + "sender": "Unsqueeze_1012", + "receiver": "Concat_1015", + "sender_port": "_1012", + "receiver_port": "_1012" + }, + "Constant_1013_Unsqueeze_1014": { + "sender": "Constant_1013", + "receiver": "Unsqueeze_1014", + "sender_port": "_1013", + "receiver_port": "_1013" + }, + "Unsqueeze_1014_Concat_1015": { + "sender": "Unsqueeze_1014", + "receiver": "Concat_1015", + "sender_port": "_1014", + "receiver_port": "_1014" + }, + "Concat_1015_Reshape_1016": { + "sender": "Concat_1015", + "receiver": "Reshape_1016", + "sender_port": "_1015", + "receiver_port": "_1015" + }, + "Reshape_1016_Transpose_1017": { + "sender": "Reshape_1016", + "receiver": "Transpose_1017", + "sender_port": "_1016", + "receiver_port": "_1016" + }, + "Transpose_1017_Reshape_1028": { + "sender": "Transpose_1017", + "receiver": "Reshape_1028", + "sender_port": "_1017", + "receiver_port": "_1017" + }, + "Constant_1018_Unsqueeze_1022": { + "sender": "Constant_1018", + "receiver": "Unsqueeze_1022", + "sender_port": "_1018", + "receiver_port": "_1018" + }, + "Constant_1019_Unsqueeze_1020": { + "sender": "Constant_1019", + "receiver": "Unsqueeze_1020", + "sender_port": "_1019", + "receiver_port": "_1019" + }, + "Unsqueeze_1020_Concat_1027": { + "sender": "Unsqueeze_1020", + "receiver": "Concat_1027", + "sender_port": "_1020", + "receiver_port": "_1020" + }, + "Constant_1021_Unsqueeze_1022": { + "sender": "Constant_1021", + "receiver": "Unsqueeze_1022", + "sender_port": "_1021", + "receiver_port": "_1021" + }, + "Unsqueeze_1022_Concat_1027": { + "sender": "Unsqueeze_1022", + "receiver": "Concat_1027", + "sender_port": "_1022", + "receiver_port": "_1022" + }, + "Constant_1023_Unsqueeze_1024": { + "sender": "Constant_1023", + "receiver": "Unsqueeze_1024", + "sender_port": "_1023", + "receiver_port": "_1023" + }, + "Unsqueeze_1024_Concat_1027": { + "sender": "Unsqueeze_1024", + "receiver": "Concat_1027", + "sender_port": "_1024", + "receiver_port": "_1024" + }, + "Constant_1025_Unsqueeze_1026": { + "sender": "Constant_1025", + "receiver": "Unsqueeze_1026", + "sender_port": "_1025", + "receiver_port": "_1025" + }, + "Unsqueeze_1026_Concat_1027": { + "sender": "Unsqueeze_1026", + "receiver": "Concat_1027", + "sender_port": "_1026", + "receiver_port": "_1026" + }, + "Concat_1027_Reshape_1028": { + "sender": "Concat_1027", + "receiver": "Reshape_1028", + "sender_port": "_1027", + "receiver_port": "_1027" + }, + "Reshape_1028_Shape_1029": { + "sender": "Reshape_1028", + "receiver": "Shape_1029", + "sender_port": "_1028", + "receiver_port": "_1028" + }, + "Reshape_1028_Slice_1039": { + "sender": "Reshape_1028", + "receiver": "Slice_1039", + "sender_port": "_1028", + "receiver_port": "_1028" + }, + "Reshape_1028_Slice_1042": { + "sender": "Reshape_1028", + "receiver": "Slice_1042", + "sender_port": "_1028", + "receiver_port": "_1028" + }, + "Shape_1029_Gather_1031": { + "sender": "Shape_1029", + "receiver": "Gather_1031", + "sender_port": "_1029", + "receiver_port": "_1029" + }, + "Constant_1030_Gather_1031": { + "sender": "Constant_1030", + "receiver": "Gather_1031", + "sender_port": "_1030", + "receiver_port": "_1030" + }, + "Constant_1030_Slice_1039": { + "sender": "Constant_1030", + "receiver": "Slice_1039", + "sender_port": "_1030", + "receiver_port": "_1030" + }, + "Constant_1030_Slice_1042": { + "sender": "Constant_1030", + "receiver": "Slice_1042", + "sender_port": "_1030", + "receiver_port": "_1030" + }, + "Gather_1031_Add_1034": { + "sender": "Gather_1031", + "receiver": "Add_1034", + "sender_port": "_1031", + "receiver_port": "_1031" + }, + "Constant_1032_Slice_1039": { + "sender": "Constant_1032", + "receiver": "Slice_1039", + "sender_port": "_1032", + "receiver_port": "_1032" + }, + "Constant_1033_Add_1034": { + "sender": "Constant_1033", + "receiver": "Add_1034", + "sender_port": "_1033", + "receiver_port": "_1033" + }, + "Add_1034_Div_1036": { + "sender": "Add_1034", + "receiver": "Div_1036", + "sender_port": "_1034", + "receiver_port": "_1034" + }, + "Constant_1035_Div_1036": { + "sender": "Constant_1035", + "receiver": "Div_1036", + "sender_port": "_1035", + "receiver_port": "_1035" + }, + "Div_1036_Mul_1038": { + "sender": "Div_1036", + "receiver": "Mul_1038", + "sender_port": "_1036", + "receiver_port": "_1036" + }, + "Div_1036_Mul_1041": { + "sender": "Div_1036", + "receiver": "Mul_1041", + "sender_port": "_1036", + "receiver_port": "_1036" + }, + "Constant_1037_Mul_1038": { + "sender": "Constant_1037", + "receiver": "Mul_1038", + "sender_port": "_1037", + "receiver_port": "_1037" + }, + "Mul_1038_Slice_1039": { + "sender": "Mul_1038", + "receiver": "Slice_1039", + "sender_port": "_1038", + "receiver_port": "_1038" + }, + "Mul_1038_Slice_1042": { + "sender": "Mul_1038", + "receiver": "Slice_1042", + "sender_port": "_1038", + "receiver_port": "_1038" + }, + "Slice_1039_Concat_1051": { + "sender": "Slice_1039", + "receiver": "Concat_1051", + "sender_port": "_1039", + "receiver_port": "_1039" + }, + "Constant_1040_Mul_1041": { + "sender": "Constant_1040", + "receiver": "Mul_1041", + "sender_port": "_1040", + "receiver_port": "_1040" + }, + "Mul_1041_Slice_1042": { + "sender": "Mul_1041", + "receiver": "Slice_1042", + "sender_port": "_1041", + "receiver_port": "_1041" + }, + "Slice_1042_Conv_1459": { + "sender": "Slice_1042", + "receiver": "Conv_1459", + "sender_port": "_1042", + "receiver_port": "_1042" + }, + "Conv_1459_Relu_1045": { + "sender": "Conv_1459", + "receiver": "Relu_1045", + "sender_port": "_1459", + "receiver_port": "_1459" + }, + "Relu_1045_Conv_1462": { + "sender": "Relu_1045", + "receiver": "Conv_1462", + "sender_port": "_1045", + "receiver_port": "_1045" + }, + "Conv_1462_Conv_1465": { + "sender": "Conv_1462", + "receiver": "Conv_1465", + "sender_port": "_1462", + "receiver_port": "_1462" + }, + "Conv_1465_Relu_1050": { + "sender": "Conv_1465", + "receiver": "Relu_1050", + "sender_port": "_1465", + "receiver_port": "_1465" + }, + "Relu_1050_Concat_1051": { + "sender": "Relu_1050", + "receiver": "Concat_1051", + "sender_port": "_1050", + "receiver_port": "_1050" + }, + "Concat_1051_Shape_1052": { + "sender": "Concat_1051", + "receiver": "Shape_1052", + "sender_port": "_1051", + "receiver_port": "_1051" + }, + "Concat_1051_Shape_1055": { + "sender": "Concat_1051", + "receiver": "Shape_1055", + "sender_port": "_1051", + "receiver_port": "_1051" + }, + "Concat_1051_Shape_1058": { + "sender": "Concat_1051", + "receiver": "Shape_1058", + "sender_port": "_1051", + "receiver_port": "_1051" + }, + "Concat_1051_Shape_1061": { + "sender": "Concat_1051", + "receiver": "Shape_1061", + "sender_port": "_1051", + "receiver_port": "_1051" + }, + "Concat_1051_Reshape_1080": { + "sender": "Concat_1051", + "receiver": "Reshape_1080", + "sender_port": "_1051", + "receiver_port": "_1051" + }, + "Shape_1052_Gather_1054": { + "sender": "Shape_1052", + "receiver": "Gather_1054", + "sender_port": "_1052", + "receiver_port": "_1052" + }, + "Constant_1053_Gather_1054": { + "sender": "Constant_1053", + "receiver": "Gather_1054", + "sender_port": "_1053", + "receiver_port": "_1053" + }, + "Gather_1054_Unsqueeze_1070": { + "sender": "Gather_1054", + "receiver": "Unsqueeze_1070", + "sender_port": "_1054", + "receiver_port": "_1054" + }, + "Gather_1054_Unsqueeze_1084": { + "sender": "Gather_1054", + "receiver": "Unsqueeze_1084", + "sender_port": "_1054", + "receiver_port": "_1054" + }, + "Shape_1055_Gather_1057": { + "sender": "Shape_1055", + "receiver": "Gather_1057", + "sender_port": "_1055", + "receiver_port": "_1055" + }, + "Constant_1056_Gather_1057": { + "sender": "Constant_1056", + "receiver": "Gather_1057", + "sender_port": "_1056", + "receiver_port": "_1056" + }, + "Gather_1057_Div_1065": { + "sender": "Gather_1057", + "receiver": "Div_1065", + "sender_port": "_1057", + "receiver_port": "_1057" + }, + "Shape_1058_Gather_1060": { + "sender": "Shape_1058", + "receiver": "Gather_1060", + "sender_port": "_1058", + "receiver_port": "_1058" + }, + "Constant_1059_Gather_1060": { + "sender": "Constant_1059", + "receiver": "Gather_1060", + "sender_port": "_1059", + "receiver_port": "_1059" + }, + "Gather_1060_Unsqueeze_1076": { + "sender": "Gather_1060", + "receiver": "Unsqueeze_1076", + "sender_port": "_1060", + "receiver_port": "_1060" + }, + "Gather_1060_Unsqueeze_1088": { + "sender": "Gather_1060", + "receiver": "Unsqueeze_1088", + "sender_port": "_1060", + "receiver_port": "_1060" + }, + "Shape_1061_Gather_1063": { + "sender": "Shape_1061", + "receiver": "Gather_1063", + "sender_port": "_1061", + "receiver_port": "_1061" + }, + "Constant_1062_Gather_1063": { + "sender": "Constant_1062", + "receiver": "Gather_1063", + "sender_port": "_1062", + "receiver_port": "_1062" + }, + "Gather_1063_Unsqueeze_1078": { + "sender": "Gather_1063", + "receiver": "Unsqueeze_1078", + "sender_port": "_1063", + "receiver_port": "_1063" + }, + "Gather_1063_Unsqueeze_1090": { + "sender": "Gather_1063", + "receiver": "Unsqueeze_1090", + "sender_port": "_1063", + "receiver_port": "_1063" + }, + "Constant_1064_Div_1065": { + "sender": "Constant_1064", + "receiver": "Div_1065", + "sender_port": "_1064", + "receiver_port": "_1064" + }, + "Div_1065_Cast_1066": { + "sender": "Div_1065", + "receiver": "Cast_1066", + "sender_port": "_1065", + "receiver_port": "_1065" + }, + "Cast_1066_Cast_1067": { + "sender": "Cast_1066", + "receiver": "Cast_1067", + "sender_port": "_1066", + "receiver_port": "_1066" + }, + "Cast_1067_Unsqueeze_1074": { + "sender": "Cast_1067", + "receiver": "Unsqueeze_1074", + "sender_port": "_1067", + "receiver_port": "_1067" + }, + "Constant_1068_Unsqueeze_1072": { + "sender": "Constant_1068", + "receiver": "Unsqueeze_1072", + "sender_port": "_1068", + "receiver_port": "_1068" + }, + "Constant_1069_Unsqueeze_1070": { + "sender": "Constant_1069", + "receiver": "Unsqueeze_1070", + "sender_port": "_1069", + "receiver_port": "_1069" + }, + "Unsqueeze_1070_Concat_1079": { + "sender": "Unsqueeze_1070", + "receiver": "Concat_1079", + "sender_port": "_1070", + "receiver_port": "_1070" + }, + "Constant_1071_Unsqueeze_1072": { + "sender": "Constant_1071", + "receiver": "Unsqueeze_1072", + "sender_port": "_1071", + "receiver_port": "_1071" + }, + "Unsqueeze_1072_Concat_1079": { + "sender": "Unsqueeze_1072", + "receiver": "Concat_1079", + "sender_port": "_1072", + "receiver_port": "_1072" + }, + "Constant_1073_Unsqueeze_1074": { + "sender": "Constant_1073", + "receiver": "Unsqueeze_1074", + "sender_port": "_1073", + "receiver_port": "_1073" + }, + "Unsqueeze_1074_Concat_1079": { + "sender": "Unsqueeze_1074", + "receiver": "Concat_1079", + "sender_port": "_1074", + "receiver_port": "_1074" + }, + "Constant_1075_Unsqueeze_1076": { + "sender": "Constant_1075", + "receiver": "Unsqueeze_1076", + "sender_port": "_1075", + "receiver_port": "_1075" + }, + "Unsqueeze_1076_Concat_1079": { + "sender": "Unsqueeze_1076", + "receiver": "Concat_1079", + "sender_port": "_1076", + "receiver_port": "_1076" + }, + "Constant_1077_Unsqueeze_1078": { + "sender": "Constant_1077", + "receiver": "Unsqueeze_1078", + "sender_port": "_1077", + "receiver_port": "_1077" + }, + "Unsqueeze_1078_Concat_1079": { + "sender": "Unsqueeze_1078", + "receiver": "Concat_1079", + "sender_port": "_1078", + "receiver_port": "_1078" + }, + "Concat_1079_Reshape_1080": { + "sender": "Concat_1079", + "receiver": "Reshape_1080", + "sender_port": "_1079", + "receiver_port": "_1079" + }, + "Reshape_1080_Transpose_1081": { + "sender": "Reshape_1080", + "receiver": "Transpose_1081", + "sender_port": "_1080", + "receiver_port": "_1080" + }, + "Transpose_1081_Reshape_1092": { + "sender": "Transpose_1081", + "receiver": "Reshape_1092", + "sender_port": "_1081", + "receiver_port": "_1081" + }, + "Constant_1082_Unsqueeze_1086": { + "sender": "Constant_1082", + "receiver": "Unsqueeze_1086", + "sender_port": "_1082", + "receiver_port": "_1082" + }, + "Constant_1083_Unsqueeze_1084": { + "sender": "Constant_1083", + "receiver": "Unsqueeze_1084", + "sender_port": "_1083", + "receiver_port": "_1083" + }, + "Unsqueeze_1084_Concat_1091": { + "sender": "Unsqueeze_1084", + "receiver": "Concat_1091", + "sender_port": "_1084", + "receiver_port": "_1084" + }, + "Constant_1085_Unsqueeze_1086": { + "sender": "Constant_1085", + "receiver": "Unsqueeze_1086", + "sender_port": "_1085", + "receiver_port": "_1085" + }, + "Unsqueeze_1086_Concat_1091": { + "sender": "Unsqueeze_1086", + "receiver": "Concat_1091", + "sender_port": "_1086", + "receiver_port": "_1086" + }, + "Constant_1087_Unsqueeze_1088": { + "sender": "Constant_1087", + "receiver": "Unsqueeze_1088", + "sender_port": "_1087", + "receiver_port": "_1087" + }, + "Unsqueeze_1088_Concat_1091": { + "sender": "Unsqueeze_1088", + "receiver": "Concat_1091", + "sender_port": "_1088", + "receiver_port": "_1088" + }, + "Constant_1089_Unsqueeze_1090": { + "sender": "Constant_1089", + "receiver": "Unsqueeze_1090", + "sender_port": "_1089", + "receiver_port": "_1089" + }, + "Unsqueeze_1090_Concat_1091": { + "sender": "Unsqueeze_1090", + "receiver": "Concat_1091", + "sender_port": "_1090", + "receiver_port": "_1090" + }, + "Concat_1091_Reshape_1092": { + "sender": "Concat_1091", + "receiver": "Reshape_1092", + "sender_port": "_1091", + "receiver_port": "_1091" + }, + "Reshape_1092_Conv_1468": { + "sender": "Reshape_1092", + "receiver": "Conv_1468", + "sender_port": "_1092", + "receiver_port": "_1092" + }, + "Reshape_1092_Conv_1474": { + "sender": "Reshape_1092", + "receiver": "Conv_1474", + "sender_port": "_1092", + "receiver_port": "_1092" + }, + "Conv_1468_Conv_1471": { + "sender": "Conv_1468", + "receiver": "Conv_1471", + "sender_port": "_1468", + "receiver_port": "_1468" + }, + "Conv_1471_Relu_1097": { + "sender": "Conv_1471", + "receiver": "Relu_1097", + "sender_port": "_1471", + "receiver_port": "_1471" + }, + "Relu_1097_Concat_1106": { + "sender": "Relu_1097", + "receiver": "Concat_1106", + "sender_port": "_1097", + "receiver_port": "_1097" + }, + "Conv_1474_Relu_1100": { + "sender": "Conv_1474", + "receiver": "Relu_1100", + "sender_port": "_1474", + "receiver_port": "_1474" + }, + "Relu_1100_Conv_1477": { + "sender": "Relu_1100", + "receiver": "Conv_1477", + "sender_port": "_1100", + "receiver_port": "_1100" + }, + "Conv_1477_Conv_1480": { + "sender": "Conv_1477", + "receiver": "Conv_1480", + "sender_port": "_1477", + "receiver_port": "_1477" + }, + "Conv_1480_Relu_1105": { + "sender": "Conv_1480", + "receiver": "Relu_1105", + "sender_port": "_1480", + "receiver_port": "_1480" + }, + "Relu_1105_Concat_1106": { + "sender": "Relu_1105", + "receiver": "Concat_1106", + "sender_port": "_1105", + "receiver_port": "_1105" + }, + "Concat_1106_Shape_1107": { + "sender": "Concat_1106", + "receiver": "Shape_1107", + "sender_port": "_1106", + "receiver_port": "_1106" + }, + "Concat_1106_Shape_1110": { + "sender": "Concat_1106", + "receiver": "Shape_1110", + "sender_port": "_1106", + "receiver_port": "_1106" + }, + "Concat_1106_Shape_1113": { + "sender": "Concat_1106", + "receiver": "Shape_1113", + "sender_port": "_1106", + "receiver_port": "_1106" + }, + "Concat_1106_Shape_1116": { + "sender": "Concat_1106", + "receiver": "Shape_1116", + "sender_port": "_1106", + "receiver_port": "_1106" + }, + "Concat_1106_Reshape_1135": { + "sender": "Concat_1106", + "receiver": "Reshape_1135", + "sender_port": "_1106", + "receiver_port": "_1106" + }, + "Shape_1107_Gather_1109": { + "sender": "Shape_1107", + "receiver": "Gather_1109", + "sender_port": "_1107", + "receiver_port": "_1107" + }, + "Constant_1108_Gather_1109": { + "sender": "Constant_1108", + "receiver": "Gather_1109", + "sender_port": "_1108", + "receiver_port": "_1108" + }, + "Gather_1109_Unsqueeze_1125": { + "sender": "Gather_1109", + "receiver": "Unsqueeze_1125", + "sender_port": "_1109", + "receiver_port": "_1109" + }, + "Gather_1109_Unsqueeze_1139": { + "sender": "Gather_1109", + "receiver": "Unsqueeze_1139", + "sender_port": "_1109", + "receiver_port": "_1109" + }, + "Shape_1110_Gather_1112": { + "sender": "Shape_1110", + "receiver": "Gather_1112", + "sender_port": "_1110", + "receiver_port": "_1110" + }, + "Constant_1111_Gather_1112": { + "sender": "Constant_1111", + "receiver": "Gather_1112", + "sender_port": "_1111", + "receiver_port": "_1111" + }, + "Gather_1112_Div_1120": { + "sender": "Gather_1112", + "receiver": "Div_1120", + "sender_port": "_1112", + "receiver_port": "_1112" + }, + "Shape_1113_Gather_1115": { + "sender": "Shape_1113", + "receiver": "Gather_1115", + "sender_port": "_1113", + "receiver_port": "_1113" + }, + "Constant_1114_Gather_1115": { + "sender": "Constant_1114", + "receiver": "Gather_1115", + "sender_port": "_1114", + "receiver_port": "_1114" + }, + "Gather_1115_Unsqueeze_1131": { + "sender": "Gather_1115", + "receiver": "Unsqueeze_1131", + "sender_port": "_1115", + "receiver_port": "_1115" + }, + "Gather_1115_Unsqueeze_1143": { + "sender": "Gather_1115", + "receiver": "Unsqueeze_1143", + "sender_port": "_1115", + "receiver_port": "_1115" + }, + "Shape_1116_Gather_1118": { + "sender": "Shape_1116", + "receiver": "Gather_1118", + "sender_port": "_1116", + "receiver_port": "_1116" + }, + "Constant_1117_Gather_1118": { + "sender": "Constant_1117", + "receiver": "Gather_1118", + "sender_port": "_1117", + "receiver_port": "_1117" + }, + "Gather_1118_Unsqueeze_1133": { + "sender": "Gather_1118", + "receiver": "Unsqueeze_1133", + "sender_port": "_1118", + "receiver_port": "_1118" + }, + "Gather_1118_Unsqueeze_1145": { + "sender": "Gather_1118", + "receiver": "Unsqueeze_1145", + "sender_port": "_1118", + "receiver_port": "_1118" + }, + "Constant_1119_Div_1120": { + "sender": "Constant_1119", + "receiver": "Div_1120", + "sender_port": "_1119", + "receiver_port": "_1119" + }, + "Div_1120_Cast_1121": { + "sender": "Div_1120", + "receiver": "Cast_1121", + "sender_port": "_1120", + "receiver_port": "_1120" + }, + "Cast_1121_Cast_1122": { + "sender": "Cast_1121", + "receiver": "Cast_1122", + "sender_port": "_1121", + "receiver_port": "_1121" + }, + "Cast_1122_Unsqueeze_1129": { + "sender": "Cast_1122", + "receiver": "Unsqueeze_1129", + "sender_port": "_1122", + "receiver_port": "_1122" + }, + "Constant_1123_Unsqueeze_1127": { + "sender": "Constant_1123", + "receiver": "Unsqueeze_1127", + "sender_port": "_1123", + "receiver_port": "_1123" + }, + "Constant_1124_Unsqueeze_1125": { + "sender": "Constant_1124", + "receiver": "Unsqueeze_1125", + "sender_port": "_1124", + "receiver_port": "_1124" + }, + "Unsqueeze_1125_Concat_1134": { + "sender": "Unsqueeze_1125", + "receiver": "Concat_1134", + "sender_port": "_1125", + "receiver_port": "_1125" + }, + "Constant_1126_Unsqueeze_1127": { + "sender": "Constant_1126", + "receiver": "Unsqueeze_1127", + "sender_port": "_1126", + "receiver_port": "_1126" + }, + "Unsqueeze_1127_Concat_1134": { + "sender": "Unsqueeze_1127", + "receiver": "Concat_1134", + "sender_port": "_1127", + "receiver_port": "_1127" + }, + "Constant_1128_Unsqueeze_1129": { + "sender": "Constant_1128", + "receiver": "Unsqueeze_1129", + "sender_port": "_1128", + "receiver_port": "_1128" + }, + "Unsqueeze_1129_Concat_1134": { + "sender": "Unsqueeze_1129", + "receiver": "Concat_1134", + "sender_port": "_1129", + "receiver_port": "_1129" + }, + "Constant_1130_Unsqueeze_1131": { + "sender": "Constant_1130", + "receiver": "Unsqueeze_1131", + "sender_port": "_1130", + "receiver_port": "_1130" + }, + "Unsqueeze_1131_Concat_1134": { + "sender": "Unsqueeze_1131", + "receiver": "Concat_1134", + "sender_port": "_1131", + "receiver_port": "_1131" + }, + "Constant_1132_Unsqueeze_1133": { + "sender": "Constant_1132", + "receiver": "Unsqueeze_1133", + "sender_port": "_1132", + "receiver_port": "_1132" + }, + "Unsqueeze_1133_Concat_1134": { + "sender": "Unsqueeze_1133", + "receiver": "Concat_1134", + "sender_port": "_1133", + "receiver_port": "_1133" + }, + "Concat_1134_Reshape_1135": { + "sender": "Concat_1134", + "receiver": "Reshape_1135", + "sender_port": "_1134", + "receiver_port": "_1134" + }, + "Reshape_1135_Transpose_1136": { + "sender": "Reshape_1135", + "receiver": "Transpose_1136", + "sender_port": "_1135", + "receiver_port": "_1135" + }, + "Transpose_1136_Reshape_1147": { + "sender": "Transpose_1136", + "receiver": "Reshape_1147", + "sender_port": "_1136", + "receiver_port": "_1136" + }, + "Constant_1137_Unsqueeze_1141": { + "sender": "Constant_1137", + "receiver": "Unsqueeze_1141", + "sender_port": "_1137", + "receiver_port": "_1137" + }, + "Constant_1138_Unsqueeze_1139": { + "sender": "Constant_1138", + "receiver": "Unsqueeze_1139", + "sender_port": "_1138", + "receiver_port": "_1138" + }, + "Unsqueeze_1139_Concat_1146": { + "sender": "Unsqueeze_1139", + "receiver": "Concat_1146", + "sender_port": "_1139", + "receiver_port": "_1139" + }, + "Constant_1140_Unsqueeze_1141": { + "sender": "Constant_1140", + "receiver": "Unsqueeze_1141", + "sender_port": "_1140", + "receiver_port": "_1140" + }, + "Unsqueeze_1141_Concat_1146": { + "sender": "Unsqueeze_1141", + "receiver": "Concat_1146", + "sender_port": "_1141", + "receiver_port": "_1141" + }, + "Constant_1142_Unsqueeze_1143": { + "sender": "Constant_1142", + "receiver": "Unsqueeze_1143", + "sender_port": "_1142", + "receiver_port": "_1142" + }, + "Unsqueeze_1143_Concat_1146": { + "sender": "Unsqueeze_1143", + "receiver": "Concat_1146", + "sender_port": "_1143", + "receiver_port": "_1143" + }, + "Constant_1144_Unsqueeze_1145": { + "sender": "Constant_1144", + "receiver": "Unsqueeze_1145", + "sender_port": "_1144", + "receiver_port": "_1144" + }, + "Unsqueeze_1145_Concat_1146": { + "sender": "Unsqueeze_1145", + "receiver": "Concat_1146", + "sender_port": "_1145", + "receiver_port": "_1145" + }, + "Concat_1146_Reshape_1147": { + "sender": "Concat_1146", + "receiver": "Reshape_1147", + "sender_port": "_1146", + "receiver_port": "_1146" + }, + "Reshape_1147_Shape_1148": { + "sender": "Reshape_1147", + "receiver": "Shape_1148", + "sender_port": "_1147", + "receiver_port": "_1147" + }, + "Reshape_1147_Slice_1158": { + "sender": "Reshape_1147", + "receiver": "Slice_1158", + "sender_port": "_1147", + "receiver_port": "_1147" + }, + "Reshape_1147_Slice_1161": { + "sender": "Reshape_1147", + "receiver": "Slice_1161", + "sender_port": "_1147", + "receiver_port": "_1147" + }, + "Shape_1148_Gather_1150": { + "sender": "Shape_1148", + "receiver": "Gather_1150", + "sender_port": "_1148", + "receiver_port": "_1148" + }, + "Constant_1149_Gather_1150": { + "sender": "Constant_1149", + "receiver": "Gather_1150", + "sender_port": "_1149", + "receiver_port": "_1149" + }, + "Constant_1149_Slice_1158": { + "sender": "Constant_1149", + "receiver": "Slice_1158", + "sender_port": "_1149", + "receiver_port": "_1149" + }, + "Constant_1149_Slice_1161": { + "sender": "Constant_1149", + "receiver": "Slice_1161", + "sender_port": "_1149", + "receiver_port": "_1149" + }, + "Gather_1150_Add_1153": { + "sender": "Gather_1150", + "receiver": "Add_1153", + "sender_port": "_1150", + "receiver_port": "_1150" + }, + "Constant_1151_Slice_1158": { + "sender": "Constant_1151", + "receiver": "Slice_1158", + "sender_port": "_1151", + "receiver_port": "_1151" + }, + "Constant_1152_Add_1153": { + "sender": "Constant_1152", + "receiver": "Add_1153", + "sender_port": "_1152", + "receiver_port": "_1152" + }, + "Add_1153_Div_1155": { + "sender": "Add_1153", + "receiver": "Div_1155", + "sender_port": "_1153", + "receiver_port": "_1153" + }, + "Constant_1154_Div_1155": { + "sender": "Constant_1154", + "receiver": "Div_1155", + "sender_port": "_1154", + "receiver_port": "_1154" + }, + "Div_1155_Mul_1157": { + "sender": "Div_1155", + "receiver": "Mul_1157", + "sender_port": "_1155", + "receiver_port": "_1155" + }, + "Div_1155_Mul_1160": { + "sender": "Div_1155", + "receiver": "Mul_1160", + "sender_port": "_1155", + "receiver_port": "_1155" + }, + "Constant_1156_Mul_1157": { + "sender": "Constant_1156", + "receiver": "Mul_1157", + "sender_port": "_1156", + "receiver_port": "_1156" + }, + "Mul_1157_Slice_1158": { + "sender": "Mul_1157", + "receiver": "Slice_1158", + "sender_port": "_1157", + "receiver_port": "_1157" + }, + "Mul_1157_Slice_1161": { + "sender": "Mul_1157", + "receiver": "Slice_1161", + "sender_port": "_1157", + "receiver_port": "_1157" + }, + "Slice_1158_Concat_1170": { + "sender": "Slice_1158", + "receiver": "Concat_1170", + "sender_port": "_1158", + "receiver_port": "_1158" + }, + "Constant_1159_Mul_1160": { + "sender": "Constant_1159", + "receiver": "Mul_1160", + "sender_port": "_1159", + "receiver_port": "_1159" + }, + "Mul_1160_Slice_1161": { + "sender": "Mul_1160", + "receiver": "Slice_1161", + "sender_port": "_1160", + "receiver_port": "_1160" + }, + "Slice_1161_Conv_1483": { + "sender": "Slice_1161", + "receiver": "Conv_1483", + "sender_port": "_1161", + "receiver_port": "_1161" + }, + "Conv_1483_Relu_1164": { + "sender": "Conv_1483", + "receiver": "Relu_1164", + "sender_port": "_1483", + "receiver_port": "_1483" + }, + "Relu_1164_Conv_1486": { + "sender": "Relu_1164", + "receiver": "Conv_1486", + "sender_port": "_1164", + "receiver_port": "_1164" + }, + "Conv_1486_Conv_1489": { + "sender": "Conv_1486", + "receiver": "Conv_1489", + "sender_port": "_1486", + "receiver_port": "_1486" + }, + "Conv_1489_Relu_1169": { + "sender": "Conv_1489", + "receiver": "Relu_1169", + "sender_port": "_1489", + "receiver_port": "_1489" + }, + "Relu_1169_Concat_1170": { + "sender": "Relu_1169", + "receiver": "Concat_1170", + "sender_port": "_1169", + "receiver_port": "_1169" + }, + "Concat_1170_Shape_1171": { + "sender": "Concat_1170", + "receiver": "Shape_1171", + "sender_port": "_1170", + "receiver_port": "_1170" + }, + "Concat_1170_Shape_1174": { + "sender": "Concat_1170", + "receiver": "Shape_1174", + "sender_port": "_1170", + "receiver_port": "_1170" + }, + "Concat_1170_Shape_1177": { + "sender": "Concat_1170", + "receiver": "Shape_1177", + "sender_port": "_1170", + "receiver_port": "_1170" + }, + "Concat_1170_Shape_1180": { + "sender": "Concat_1170", + "receiver": "Shape_1180", + "sender_port": "_1170", + "receiver_port": "_1170" + }, + "Concat_1170_Reshape_1199": { + "sender": "Concat_1170", + "receiver": "Reshape_1199", + "sender_port": "_1170", + "receiver_port": "_1170" + }, + "Shape_1171_Gather_1173": { + "sender": "Shape_1171", + "receiver": "Gather_1173", + "sender_port": "_1171", + "receiver_port": "_1171" + }, + "Constant_1172_Gather_1173": { + "sender": "Constant_1172", + "receiver": "Gather_1173", + "sender_port": "_1172", + "receiver_port": "_1172" + }, + "Gather_1173_Unsqueeze_1189": { + "sender": "Gather_1173", + "receiver": "Unsqueeze_1189", + "sender_port": "_1173", + "receiver_port": "_1173" + }, + "Gather_1173_Unsqueeze_1203": { + "sender": "Gather_1173", + "receiver": "Unsqueeze_1203", + "sender_port": "_1173", + "receiver_port": "_1173" + }, + "Shape_1174_Gather_1176": { + "sender": "Shape_1174", + "receiver": "Gather_1176", + "sender_port": "_1174", + "receiver_port": "_1174" + }, + "Constant_1175_Gather_1176": { + "sender": "Constant_1175", + "receiver": "Gather_1176", + "sender_port": "_1175", + "receiver_port": "_1175" + }, + "Gather_1176_Div_1184": { + "sender": "Gather_1176", + "receiver": "Div_1184", + "sender_port": "_1176", + "receiver_port": "_1176" + }, + "Shape_1177_Gather_1179": { + "sender": "Shape_1177", + "receiver": "Gather_1179", + "sender_port": "_1177", + "receiver_port": "_1177" + }, + "Constant_1178_Gather_1179": { + "sender": "Constant_1178", + "receiver": "Gather_1179", + "sender_port": "_1178", + "receiver_port": "_1178" + }, + "Gather_1179_Unsqueeze_1195": { + "sender": "Gather_1179", + "receiver": "Unsqueeze_1195", + "sender_port": "_1179", + "receiver_port": "_1179" + }, + "Gather_1179_Unsqueeze_1207": { + "sender": "Gather_1179", + "receiver": "Unsqueeze_1207", + "sender_port": "_1179", + "receiver_port": "_1179" + }, + "Shape_1180_Gather_1182": { + "sender": "Shape_1180", + "receiver": "Gather_1182", + "sender_port": "_1180", + "receiver_port": "_1180" + }, + "Constant_1181_Gather_1182": { + "sender": "Constant_1181", + "receiver": "Gather_1182", + "sender_port": "_1181", + "receiver_port": "_1181" + }, + "Gather_1182_Unsqueeze_1197": { + "sender": "Gather_1182", + "receiver": "Unsqueeze_1197", + "sender_port": "_1182", + "receiver_port": "_1182" + }, + "Gather_1182_Unsqueeze_1209": { + "sender": "Gather_1182", + "receiver": "Unsqueeze_1209", + "sender_port": "_1182", + "receiver_port": "_1182" + }, + "Constant_1183_Div_1184": { + "sender": "Constant_1183", + "receiver": "Div_1184", + "sender_port": "_1183", + "receiver_port": "_1183" + }, + "Div_1184_Cast_1185": { + "sender": "Div_1184", + "receiver": "Cast_1185", + "sender_port": "_1184", + "receiver_port": "_1184" + }, + "Cast_1185_Cast_1186": { + "sender": "Cast_1185", + "receiver": "Cast_1186", + "sender_port": "_1185", + "receiver_port": "_1185" + }, + "Cast_1186_Unsqueeze_1193": { + "sender": "Cast_1186", + "receiver": "Unsqueeze_1193", + "sender_port": "_1186", + "receiver_port": "_1186" + }, + "Constant_1187_Unsqueeze_1191": { + "sender": "Constant_1187", + "receiver": "Unsqueeze_1191", + "sender_port": "_1187", + "receiver_port": "_1187" + }, + "Constant_1188_Unsqueeze_1189": { + "sender": "Constant_1188", + "receiver": "Unsqueeze_1189", + "sender_port": "_1188", + "receiver_port": "_1188" + }, + "Unsqueeze_1189_Concat_1198": { + "sender": "Unsqueeze_1189", + "receiver": "Concat_1198", + "sender_port": "_1189", + "receiver_port": "_1189" + }, + "Constant_1190_Unsqueeze_1191": { + "sender": "Constant_1190", + "receiver": "Unsqueeze_1191", + "sender_port": "_1190", + "receiver_port": "_1190" + }, + "Unsqueeze_1191_Concat_1198": { + "sender": "Unsqueeze_1191", + "receiver": "Concat_1198", + "sender_port": "_1191", + "receiver_port": "_1191" + }, + "Constant_1192_Unsqueeze_1193": { + "sender": "Constant_1192", + "receiver": "Unsqueeze_1193", + "sender_port": "_1192", + "receiver_port": "_1192" + }, + "Unsqueeze_1193_Concat_1198": { + "sender": "Unsqueeze_1193", + "receiver": "Concat_1198", + "sender_port": "_1193", + "receiver_port": "_1193" + }, + "Constant_1194_Unsqueeze_1195": { + "sender": "Constant_1194", + "receiver": "Unsqueeze_1195", + "sender_port": "_1194", + "receiver_port": "_1194" + }, + "Unsqueeze_1195_Concat_1198": { + "sender": "Unsqueeze_1195", + "receiver": "Concat_1198", + "sender_port": "_1195", + "receiver_port": "_1195" + }, + "Constant_1196_Unsqueeze_1197": { + "sender": "Constant_1196", + "receiver": "Unsqueeze_1197", + "sender_port": "_1196", + "receiver_port": "_1196" + }, + "Unsqueeze_1197_Concat_1198": { + "sender": "Unsqueeze_1197", + "receiver": "Concat_1198", + "sender_port": "_1197", + "receiver_port": "_1197" + }, + "Concat_1198_Reshape_1199": { + "sender": "Concat_1198", + "receiver": "Reshape_1199", + "sender_port": "_1198", + "receiver_port": "_1198" + }, + "Reshape_1199_Transpose_1200": { + "sender": "Reshape_1199", + "receiver": "Transpose_1200", + "sender_port": "_1199", + "receiver_port": "_1199" + }, + "Transpose_1200_Reshape_1211": { + "sender": "Transpose_1200", + "receiver": "Reshape_1211", + "sender_port": "_1200", + "receiver_port": "_1200" + }, + "Constant_1201_Unsqueeze_1205": { + "sender": "Constant_1201", + "receiver": "Unsqueeze_1205", + "sender_port": "_1201", + "receiver_port": "_1201" + }, + "Constant_1202_Unsqueeze_1203": { + "sender": "Constant_1202", + "receiver": "Unsqueeze_1203", + "sender_port": "_1202", + "receiver_port": "_1202" + }, + "Unsqueeze_1203_Concat_1210": { + "sender": "Unsqueeze_1203", + "receiver": "Concat_1210", + "sender_port": "_1203", + "receiver_port": "_1203" + }, + "Constant_1204_Unsqueeze_1205": { + "sender": "Constant_1204", + "receiver": "Unsqueeze_1205", + "sender_port": "_1204", + "receiver_port": "_1204" + }, + "Unsqueeze_1205_Concat_1210": { + "sender": "Unsqueeze_1205", + "receiver": "Concat_1210", + "sender_port": "_1205", + "receiver_port": "_1205" + }, + "Constant_1206_Unsqueeze_1207": { + "sender": "Constant_1206", + "receiver": "Unsqueeze_1207", + "sender_port": "_1206", + "receiver_port": "_1206" + }, + "Unsqueeze_1207_Concat_1210": { + "sender": "Unsqueeze_1207", + "receiver": "Concat_1210", + "sender_port": "_1207", + "receiver_port": "_1207" + }, + "Constant_1208_Unsqueeze_1209": { + "sender": "Constant_1208", + "receiver": "Unsqueeze_1209", + "sender_port": "_1208", + "receiver_port": "_1208" + }, + "Unsqueeze_1209_Concat_1210": { + "sender": "Unsqueeze_1209", + "receiver": "Concat_1210", + "sender_port": "_1209", + "receiver_port": "_1209" + }, + "Concat_1210_Reshape_1211": { + "sender": "Concat_1210", + "receiver": "Reshape_1211", + "sender_port": "_1210", + "receiver_port": "_1210" + }, + "Reshape_1211_Shape_1212": { + "sender": "Reshape_1211", + "receiver": "Shape_1212", + "sender_port": "_1211", + "receiver_port": "_1211" + }, + "Reshape_1211_Slice_1222": { + "sender": "Reshape_1211", + "receiver": "Slice_1222", + "sender_port": "_1211", + "receiver_port": "_1211" + }, + "Reshape_1211_Slice_1225": { + "sender": "Reshape_1211", + "receiver": "Slice_1225", + "sender_port": "_1211", + "receiver_port": "_1211" + }, + "Shape_1212_Gather_1214": { + "sender": "Shape_1212", + "receiver": "Gather_1214", + "sender_port": "_1212", + "receiver_port": "_1212" + }, + "Constant_1213_Gather_1214": { + "sender": "Constant_1213", + "receiver": "Gather_1214", + "sender_port": "_1213", + "receiver_port": "_1213" + }, + "Constant_1213_Slice_1222": { + "sender": "Constant_1213", + "receiver": "Slice_1222", + "sender_port": "_1213", + "receiver_port": "_1213" + }, + "Constant_1213_Slice_1225": { + "sender": "Constant_1213", + "receiver": "Slice_1225", + "sender_port": "_1213", + "receiver_port": "_1213" + }, + "Gather_1214_Add_1217": { + "sender": "Gather_1214", + "receiver": "Add_1217", + "sender_port": "_1214", + "receiver_port": "_1214" + }, + "Constant_1215_Slice_1222": { + "sender": "Constant_1215", + "receiver": "Slice_1222", + "sender_port": "_1215", + "receiver_port": "_1215" + }, + "Constant_1216_Add_1217": { + "sender": "Constant_1216", + "receiver": "Add_1217", + "sender_port": "_1216", + "receiver_port": "_1216" + }, + "Add_1217_Div_1219": { + "sender": "Add_1217", + "receiver": "Div_1219", + "sender_port": "_1217", + "receiver_port": "_1217" + }, + "Constant_1218_Div_1219": { + "sender": "Constant_1218", + "receiver": "Div_1219", + "sender_port": "_1218", + "receiver_port": "_1218" + }, + "Div_1219_Mul_1221": { + "sender": "Div_1219", + "receiver": "Mul_1221", + "sender_port": "_1219", + "receiver_port": "_1219" + }, + "Div_1219_Mul_1224": { + "sender": "Div_1219", + "receiver": "Mul_1224", + "sender_port": "_1219", + "receiver_port": "_1219" + }, + "Constant_1220_Mul_1221": { + "sender": "Constant_1220", + "receiver": "Mul_1221", + "sender_port": "_1220", + "receiver_port": "_1220" + }, + "Mul_1221_Slice_1222": { + "sender": "Mul_1221", + "receiver": "Slice_1222", + "sender_port": "_1221", + "receiver_port": "_1221" + }, + "Mul_1221_Slice_1225": { + "sender": "Mul_1221", + "receiver": "Slice_1225", + "sender_port": "_1221", + "receiver_port": "_1221" + }, + "Slice_1222_Concat_1234": { + "sender": "Slice_1222", + "receiver": "Concat_1234", + "sender_port": "_1222", + "receiver_port": "_1222" + }, + "Constant_1223_Mul_1224": { + "sender": "Constant_1223", + "receiver": "Mul_1224", + "sender_port": "_1223", + "receiver_port": "_1223" + }, + "Mul_1224_Slice_1225": { + "sender": "Mul_1224", + "receiver": "Slice_1225", + "sender_port": "_1224", + "receiver_port": "_1224" + }, + "Slice_1225_Conv_1492": { + "sender": "Slice_1225", + "receiver": "Conv_1492", + "sender_port": "_1225", + "receiver_port": "_1225" + }, + "Conv_1492_Relu_1228": { + "sender": "Conv_1492", + "receiver": "Relu_1228", + "sender_port": "_1492", + "receiver_port": "_1492" + }, + "Relu_1228_Conv_1495": { + "sender": "Relu_1228", + "receiver": "Conv_1495", + "sender_port": "_1228", + "receiver_port": "_1228" + }, + "Conv_1495_Conv_1498": { + "sender": "Conv_1495", + "receiver": "Conv_1498", + "sender_port": "_1495", + "receiver_port": "_1495" + }, + "Conv_1498_Relu_1233": { + "sender": "Conv_1498", + "receiver": "Relu_1233", + "sender_port": "_1498", + "receiver_port": "_1498" + }, + "Relu_1233_Concat_1234": { + "sender": "Relu_1233", + "receiver": "Concat_1234", + "sender_port": "_1233", + "receiver_port": "_1233" + }, + "Concat_1234_Shape_1235": { + "sender": "Concat_1234", + "receiver": "Shape_1235", + "sender_port": "_1234", + "receiver_port": "_1234" + }, + "Concat_1234_Shape_1238": { + "sender": "Concat_1234", + "receiver": "Shape_1238", + "sender_port": "_1234", + "receiver_port": "_1234" + }, + "Concat_1234_Shape_1241": { + "sender": "Concat_1234", + "receiver": "Shape_1241", + "sender_port": "_1234", + "receiver_port": "_1234" + }, + "Concat_1234_Shape_1244": { + "sender": "Concat_1234", + "receiver": "Shape_1244", + "sender_port": "_1234", + "receiver_port": "_1234" + }, + "Concat_1234_Reshape_1263": { + "sender": "Concat_1234", + "receiver": "Reshape_1263", + "sender_port": "_1234", + "receiver_port": "_1234" + }, + "Shape_1235_Gather_1237": { + "sender": "Shape_1235", + "receiver": "Gather_1237", + "sender_port": "_1235", + "receiver_port": "_1235" + }, + "Constant_1236_Gather_1237": { + "sender": "Constant_1236", + "receiver": "Gather_1237", + "sender_port": "_1236", + "receiver_port": "_1236" + }, + "Gather_1237_Unsqueeze_1253": { + "sender": "Gather_1237", + "receiver": "Unsqueeze_1253", + "sender_port": "_1237", + "receiver_port": "_1237" + }, + "Gather_1237_Unsqueeze_1267": { + "sender": "Gather_1237", + "receiver": "Unsqueeze_1267", + "sender_port": "_1237", + "receiver_port": "_1237" + }, + "Shape_1238_Gather_1240": { + "sender": "Shape_1238", + "receiver": "Gather_1240", + "sender_port": "_1238", + "receiver_port": "_1238" + }, + "Constant_1239_Gather_1240": { + "sender": "Constant_1239", + "receiver": "Gather_1240", + "sender_port": "_1239", + "receiver_port": "_1239" + }, + "Gather_1240_Div_1248": { + "sender": "Gather_1240", + "receiver": "Div_1248", + "sender_port": "_1240", + "receiver_port": "_1240" + }, + "Shape_1241_Gather_1243": { + "sender": "Shape_1241", + "receiver": "Gather_1243", + "sender_port": "_1241", + "receiver_port": "_1241" + }, + "Constant_1242_Gather_1243": { + "sender": "Constant_1242", + "receiver": "Gather_1243", + "sender_port": "_1242", + "receiver_port": "_1242" + }, + "Gather_1243_Unsqueeze_1259": { + "sender": "Gather_1243", + "receiver": "Unsqueeze_1259", + "sender_port": "_1243", + "receiver_port": "_1243" + }, + "Gather_1243_Unsqueeze_1271": { + "sender": "Gather_1243", + "receiver": "Unsqueeze_1271", + "sender_port": "_1243", + "receiver_port": "_1243" + }, + "Shape_1244_Gather_1246": { + "sender": "Shape_1244", + "receiver": "Gather_1246", + "sender_port": "_1244", + "receiver_port": "_1244" + }, + "Constant_1245_Gather_1246": { + "sender": "Constant_1245", + "receiver": "Gather_1246", + "sender_port": "_1245", + "receiver_port": "_1245" + }, + "Gather_1246_Unsqueeze_1261": { + "sender": "Gather_1246", + "receiver": "Unsqueeze_1261", + "sender_port": "_1246", + "receiver_port": "_1246" + }, + "Gather_1246_Unsqueeze_1273": { + "sender": "Gather_1246", + "receiver": "Unsqueeze_1273", + "sender_port": "_1246", + "receiver_port": "_1246" + }, + "Constant_1247_Div_1248": { + "sender": "Constant_1247", + "receiver": "Div_1248", + "sender_port": "_1247", + "receiver_port": "_1247" + }, + "Div_1248_Cast_1249": { + "sender": "Div_1248", + "receiver": "Cast_1249", + "sender_port": "_1248", + "receiver_port": "_1248" + }, + "Cast_1249_Cast_1250": { + "sender": "Cast_1249", + "receiver": "Cast_1250", + "sender_port": "_1249", + "receiver_port": "_1249" + }, + "Cast_1250_Unsqueeze_1257": { + "sender": "Cast_1250", + "receiver": "Unsqueeze_1257", + "sender_port": "_1250", + "receiver_port": "_1250" + }, + "Constant_1251_Unsqueeze_1255": { + "sender": "Constant_1251", + "receiver": "Unsqueeze_1255", + "sender_port": "_1251", + "receiver_port": "_1251" + }, + "Constant_1252_Unsqueeze_1253": { + "sender": "Constant_1252", + "receiver": "Unsqueeze_1253", + "sender_port": "_1252", + "receiver_port": "_1252" + }, + "Unsqueeze_1253_Concat_1262": { + "sender": "Unsqueeze_1253", + "receiver": "Concat_1262", + "sender_port": "_1253", + "receiver_port": "_1253" + }, + "Constant_1254_Unsqueeze_1255": { + "sender": "Constant_1254", + "receiver": "Unsqueeze_1255", + "sender_port": "_1254", + "receiver_port": "_1254" + }, + "Unsqueeze_1255_Concat_1262": { + "sender": "Unsqueeze_1255", + "receiver": "Concat_1262", + "sender_port": "_1255", + "receiver_port": "_1255" + }, + "Constant_1256_Unsqueeze_1257": { + "sender": "Constant_1256", + "receiver": "Unsqueeze_1257", + "sender_port": "_1256", + "receiver_port": "_1256" + }, + "Unsqueeze_1257_Concat_1262": { + "sender": "Unsqueeze_1257", + "receiver": "Concat_1262", + "sender_port": "_1257", + "receiver_port": "_1257" + }, + "Constant_1258_Unsqueeze_1259": { + "sender": "Constant_1258", + "receiver": "Unsqueeze_1259", + "sender_port": "_1258", + "receiver_port": "_1258" + }, + "Unsqueeze_1259_Concat_1262": { + "sender": "Unsqueeze_1259", + "receiver": "Concat_1262", + "sender_port": "_1259", + "receiver_port": "_1259" + }, + "Constant_1260_Unsqueeze_1261": { + "sender": "Constant_1260", + "receiver": "Unsqueeze_1261", + "sender_port": "_1260", + "receiver_port": "_1260" + }, + "Unsqueeze_1261_Concat_1262": { + "sender": "Unsqueeze_1261", + "receiver": "Concat_1262", + "sender_port": "_1261", + "receiver_port": "_1261" + }, + 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"Conv_1501_Relu_1292": { + "sender": "Conv_1501", + "receiver": "Relu_1292", + "sender_port": "_1501", + "receiver_port": "_1501" + }, + "Relu_1292_Conv_1504": { + "sender": "Relu_1292", + "receiver": "Conv_1504", + "sender_port": "_1292", + "receiver_port": "_1292" + }, + "Conv_1504_Conv_1507": { + "sender": "Conv_1504", + "receiver": "Conv_1507", + "sender_port": "_1504", + "receiver_port": "_1504" + }, + "Conv_1507_Relu_1297": { + "sender": "Conv_1507", + "receiver": "Relu_1297", + "sender_port": "_1507", + "receiver_port": "_1507" + }, + "Relu_1297_Concat_1298": { + "sender": "Relu_1297", + "receiver": "Concat_1298", + "sender_port": "_1297", + "receiver_port": "_1297" + }, + "Concat_1298_Shape_1299": { + "sender": "Concat_1298", + "receiver": "Shape_1299", + "sender_port": "_1298", + "receiver_port": "_1298" + }, + "Concat_1298_Shape_1302": { + "sender": "Concat_1298", + "receiver": "Shape_1302", + "sender_port": "_1298", + "receiver_port": "_1298" + }, + "Concat_1298_Shape_1305": 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"_1339" + }, + "Conv_1510_Relu_1342": { + "sender": "Conv_1510", + "receiver": "Relu_1342", + "sender_port": "_1510", + "receiver_port": "_1510" + }, + "Relu_1342_ReduceMean_1343": { + "sender": "Relu_1342", + "receiver": "ReduceMean_1343", + "sender_port": "_1342", + "receiver_port": "_1342" + }, + "ReduceMean_1343_Gemm_1344": { + "sender": "ReduceMean_1343", + "receiver": "Gemm_1344", + "sender_port": "_1343", + "receiver_port": "_1343" + } + } + } + }, + "onnx_opset_version": 9 + } +} diff --git a/examples/PyTorch/PyTorch_MDF/shufflenet_v2.py b/examples/PyTorch/PyTorch_MDF/shufflenet_v2.py new file mode 100644 index 00000000..d8a77c35 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/shufflenet_v2.py @@ -0,0 +1,35 @@ +import torchvision.models as models +import torch +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +shufflenet_v2 = models.shufflenet_v2_x0_5(pretrained=False) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + shufflenet_v2.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = shufflenet_v2(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=shufflenet_v2, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("shufflenet_v2.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/simple_Convolution.py b/examples/PyTorch/PyTorch_MDF/simple_Convolution.py new file mode 100644 index 00000000..9bab588b --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/simple_Convolution.py @@ -0,0 +1,64 @@ +import numpy as np +import torch +import torch.nn.functional as F +from torch import nn # All neural network modules +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +# Simple CNN +class CNN(nn.Module): + def __init__(self, in_channels=1, num_classes=10): + super().__init__() + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=8, + kernel_size=(3, 3), + ) + self.pool = nn.MaxPool2d(kernel_size=(2, 2), stride=(1, 1)) + + self.fc1 = nn.Linear(8 * 25 * 25, num_classes) + + def forward(self, x): + x = F.relu(self.conv1(x)) + x = self.pool(x) + x = x.reshape(x.shape[0], -1) + x = self.fc1(x) + return x + + +# Hyperparameters +in_channels = 1 +num_classes = 10 + +model = CNN(in_channels=in_channels, num_classes=num_classes) + +print(model) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 1, 28, 28)) + ebv_output = torch.zeros((10,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + model.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = model(x) + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=model, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("simple_convolution.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/simple_convolution.json b/examples/PyTorch/PyTorch_MDF/simple_convolution.json new file mode 100644 index 00000000..7f200fd8 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/simple_convolution.json @@ -0,0 +1,519 @@ +{ + "CNN": { + "format": "ModECI MDF v0.4", + "generating_application": "Python modeci-mdf v0.4.1.1", + "graphs": { + "CNNGraph": { + "nodes": { + "Conv_5": { + "input_ports": { + "input1": { + "shape": [ + 1, + 1, + 28, + 28 + ], + "type": "Tensor" + }, + "conv1_weight": { + "shape": [ + 8, + 1, + 3, + 3 + ], + "type": "Tensor" + }, + "conv1_bias": { + "shape": [ 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torch.nn.functional as F +from torch import nn +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + + +class VGG16(nn.Module): + def __init__(self): + super().__init__() + self.conv1_1 = nn.Conv2d( + in_channels=3, out_channels=64, kernel_size=3, padding=1 + ) + self.conv1_2 = nn.Conv2d( + in_channels=64, out_channels=64, kernel_size=3, padding=1 + ) + + self.conv2_1 = nn.Conv2d( + in_channels=64, out_channels=128, kernel_size=3, padding=1 + ) + self.conv2_2 = nn.Conv2d( + in_channels=128, out_channels=128, kernel_size=3, padding=1 + ) + + self.conv3_1 = nn.Conv2d( + in_channels=128, out_channels=256, kernel_size=3, padding=1 + ) + self.conv3_2 = nn.Conv2d( + in_channels=256, out_channels=256, kernel_size=3, padding=1 + ) + self.conv3_3 = nn.Conv2d( + in_channels=256, out_channels=256, kernel_size=3, padding=1 + ) + + self.conv4_1 = nn.Conv2d( + in_channels=256, out_channels=512, kernel_size=3, padding=1 + ) + self.conv4_2 = nn.Conv2d( + in_channels=512, out_channels=512, kernel_size=3, padding=1 + ) + self.conv4_3 = nn.Conv2d( + in_channels=512, out_channels=512, kernel_size=3, padding=1 + ) + + self.conv5_1 = nn.Conv2d( + in_channels=512, out_channels=512, kernel_size=3, padding=1 + ) + self.conv5_2 = nn.Conv2d( + in_channels=512, out_channels=512, kernel_size=3, padding=1 + ) + self.conv5_3 = nn.Conv2d( + in_channels=512, out_channels=512, kernel_size=3, padding=1 + ) + + self.maxpool = nn.MaxPool2d(kernel_size=2, stride=2) + + self.fc1 = nn.Linear(25088, 4096) + self.fc2 = nn.Linear(4096, 4096) + self.fc3 = nn.Linear(4096, 10) + + def forward(self, x): + x = F.relu(self.conv1_1(x)) + x = F.relu(self.conv1_2(x)) + x = self.maxpool(x) + x = F.relu(self.conv2_1(x)) + x = F.relu(self.conv2_2(x)) + x = self.maxpool(x) + x = F.relu(self.conv3_1(x)) + x = F.relu(self.conv3_2(x)) + x = F.relu(self.conv3_3(x)) + x = self.maxpool(x) + x = F.relu(self.conv4_1(x)) + x = F.relu(self.conv4_2(x)) + x = F.relu(self.conv4_3(x)) + x = self.maxpool(x) + x = F.relu(self.conv5_1(x)) + x = F.relu(self.conv5_2(x)) + x = F.relu(self.conv5_3(x)) + x = self.maxpool(x) + x = x.reshape(x.shape[0], -1) + x = F.relu(self.fc1(x)) + x = F.dropout(x, 0.5) # dropout was included to combat overfitting + x = F.relu(self.fc2(x)) + x = F.dropout(x, 0.5) + x = self.fc3(x) + return x + + +# Hyperparameters +in_channels = 3 +num_classes = 1 + +model = VGG16() + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + model.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = model(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=model, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("vgg16.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/PyTorch_MDF/vgg19.json b/examples/PyTorch/PyTorch_MDF/vgg19.json new file mode 100644 index 00000000..0dca763e --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/vgg19.json @@ -0,0 +1,2345 @@ +{ + "VGG": { + "format": "ModECI MDF v0.4", + "generating_application": "Python modeci-mdf v0.4.2", + "graphs": { + "VGGGraph": { + "nodes": { + "Conv_39": { + "input_ports": { + "input1": { + "shape": [ + 1, + 3, + 224, + 224 + ], + "type": "float32" + }, + "features_0_weight": { + "shape": [ + 64, + 3, + 3, + 3 + ], + "type": "float32" + }, + "features_0_bias": { + "shape": [ + 64 + ], + "type": "float32" + } + }, + "parameters": { + "dilations": { + "value": [ + 1, + 1 + ] + }, + "group": { + "value": 1 + }, + "kernel_shape": { + "value": [ + 3, + 3 + ] + }, + "pads": { + "value": [ + 1, + 1, + 1, + 1 + ] + }, + "strides": { + "value": [ + 1, + 1 + ] + }, + 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"value": 0 + }, + "kernel_shape": { + "value": [ + 2, + 2 + ] + }, + "pads": { + "value": [ + 0, + 0, + 0, + 0 + ] + }, + "strides": { + "value": [ + 2, + 2 + ] + }, + "onnx_MaxPool_1": { + "function": "onnx::MaxPool", + "args": { + "X": "_74" + } + } + }, + "output_ports": { + "_75": { + "value": "onnx_MaxPool_1[0]" + } + } + }, + "AveragePool_76": { + "input_ports": { + "_75": { + "shape": [ + 1, + 512, + 7, + 7 + ], + "type": "float32" + } + }, + "parameters": { + "kernel_shape": { + "value": [ + 1, + 1 + ] + }, + "strides": { + "value": [ + 1, + 1 + ] + }, + "onnx_AveragePool_1": { + "function": "onnx::AveragePool", + "args": { + "X": "_75" + } + } + }, + "output_ports": { + "_76": { + "value": "onnx_AveragePool_1" + } + } + }, + "Flatten_77": { + "input_ports": { + "_76": { + "shape": [ + 1, + 512, + 7, + 7 + ], + "type": "float32" + } + }, + "parameters": { + "axis": { + "value": 1 + }, + "onnx_Flatten_1": { + "function": "onnx::Flatten", + "args": { + "input": "_76" + } + } + }, + "output_ports": { + "_77": { + "value": "onnx_Flatten_1" + } + } + }, + "Gemm_78": { + "input_ports": { + "_77": { + "shape": [ + 1, + 25088 + ], + "type": "float32" + }, + "classifier_0_weight": { + "shape": [ + 4096, + 25088 + ], + "type": "float32" + }, + "classifier_0_bias": { + "shape": [ + 4096 + ], + "type": "float32" + } + }, + "parameters": { + "alpha": { + "value": 1.0 + }, + "beta": { + "value": 1.0 + }, + "transB": { + "value": 1 + }, + "onnx_Gemm_1": { + "function": "onnx::Gemm", + "args": { + "A": "_77", + "B": "classifier_0_weight", + "C": "classifier_0_bias" + } + } + }, + "output_ports": { + "_78": { + "value": "onnx_Gemm_1" + } + } + }, + "Relu_79": { + "input_ports": { + "_78": { + "shape": [ + 1, + 4096 + ], + "type": "float32" + } + }, + "parameters": { + "onnx_Relu_1": { + "function": "onnx::Relu", + "args": { + "X": "_78" + } + } + }, + "output_ports": { + "_79": { + "value": "onnx_Relu_1" + } + } + }, + "Gemm_80": { + "input_ports": { + "_79": { + "shape": [ + 1, + 4096 + ], + "type": "float32" + }, + "classifier_3_weight": { + "shape": [ + 4096, + 4096 + ], + "type": "float32" + }, + "classifier_3_bias": { + "shape": [ + 4096 + ], + "type": "float32" + } + }, + "parameters": { + "alpha": { + "value": 1.0 + }, + "beta": { + "value": 1.0 + }, + "transB": { + "value": 1 + }, + "onnx_Gemm_1": { + "function": "onnx::Gemm", + "args": { + "A": "_79", + "B": "classifier_3_weight", + "C": "classifier_3_bias" + } + } + }, + "output_ports": { + "_80": { + "value": "onnx_Gemm_1" + } + } + }, + "Relu_81": { + "input_ports": { + "_80": { + "shape": [ + 1, + 4096 + ], + "type": "float32" + } + }, + "parameters": { + "onnx_Relu_1": { + "function": "onnx::Relu", + "args": { + "X": "_80" + } + } + }, + "output_ports": { + "_81": { + "value": "onnx_Relu_1" + } + } + }, + "Gemm_82": { + "input_ports": { + "_81": { + "shape": [ + 1, + 4096 + ], + "type": "float32" + }, + "classifier_6_weight": { + "shape": [ + 1000, + 4096 + ], + "type": "float32" + }, + "classifier_6_bias": { + "shape": [ + 1000 + ], + "type": "float32" + } + }, + "parameters": { + "alpha": { + "value": 1.0 + }, + "beta": { + "value": 1.0 + }, + "transB": { + "value": 1 + }, + "onnx_Gemm_1": { + "function": "onnx::Gemm", + "args": { + "A": "_81", + "B": "classifier_6_weight", + "C": "classifier_6_bias" + } + } + }, + "output_ports": { + "_82": { + "value": "onnx_Gemm_1" + } + } + } + }, + "edges": { + "Conv_39_Relu_40": { + "sender": "Conv_39", + "receiver": "Relu_40", + "sender_port": "_39", + "receiver_port": "_39" + }, + "Relu_40_Conv_41": { + "sender": "Relu_40", + "receiver": "Conv_41", + "sender_port": "_40", + "receiver_port": "_40" + }, + "Conv_41_Relu_42": { + "sender": "Conv_41", + "receiver": "Relu_42", + "sender_port": "_41", + "receiver_port": "_41" + }, + "Relu_42_MaxPool_43": { + "sender": "Relu_42", + "receiver": "MaxPool_43", + "sender_port": "_42", + "receiver_port": "_42" + }, + "MaxPool_43_Conv_44": { + "sender": "MaxPool_43", + "receiver": "Conv_44", + "sender_port": "_43", + "receiver_port": "_43" + }, + "Conv_44_Relu_45": { + "sender": "Conv_44", + "receiver": "Relu_45", + "sender_port": "_44", + "receiver_port": "_44" + }, + "Relu_45_Conv_46": { + "sender": "Relu_45", + "receiver": "Conv_46", + "sender_port": "_45", + "receiver_port": "_45" + }, + "Conv_46_Relu_47": { + "sender": "Conv_46", + "receiver": "Relu_47", + "sender_port": "_46", + "receiver_port": "_46" + }, + "Relu_47_MaxPool_48": { + "sender": "Relu_47", + "receiver": "MaxPool_48", + "sender_port": "_47", + "receiver_port": "_47" + }, + "MaxPool_48_Conv_49": { + "sender": "MaxPool_48", + "receiver": "Conv_49", + "sender_port": "_48", + "receiver_port": "_48" + }, + "Conv_49_Relu_50": { + "sender": "Conv_49", + "receiver": "Relu_50", + "sender_port": "_49", + "receiver_port": "_49" + }, + "Relu_50_Conv_51": { + "sender": "Relu_50", + "receiver": "Conv_51", + "sender_port": "_50", + "receiver_port": "_50" + }, + "Conv_51_Relu_52": { + "sender": "Conv_51", + "receiver": "Relu_52", + "sender_port": "_51", + "receiver_port": "_51" + }, + "Relu_52_Conv_53": { + "sender": "Relu_52", + "receiver": "Conv_53", + "sender_port": "_52", + "receiver_port": "_52" + }, + "Conv_53_Relu_54": { + "sender": "Conv_53", + "receiver": "Relu_54", + "sender_port": "_53", + "receiver_port": "_53" + }, + "Relu_54_Conv_55": { + "sender": "Relu_54", + "receiver": "Conv_55", + "sender_port": "_54", + "receiver_port": "_54" + }, + "Conv_55_Relu_56": { + "sender": "Conv_55", + "receiver": "Relu_56", + "sender_port": "_55", + "receiver_port": "_55" + }, + "Relu_56_MaxPool_57": { + "sender": "Relu_56", + "receiver": "MaxPool_57", + "sender_port": "_56", + "receiver_port": "_56" + }, + "MaxPool_57_Conv_58": { + "sender": "MaxPool_57", + "receiver": "Conv_58", + "sender_port": "_57", + "receiver_port": "_57" + }, + "Conv_58_Relu_59": { + "sender": "Conv_58", + "receiver": "Relu_59", + "sender_port": "_58", + "receiver_port": "_58" + }, + "Relu_59_Conv_60": { + "sender": "Relu_59", + "receiver": "Conv_60", + "sender_port": "_59", + "receiver_port": "_59" + }, + "Conv_60_Relu_61": { + "sender": "Conv_60", + "receiver": "Relu_61", + "sender_port": "_60", + "receiver_port": "_60" + }, + "Relu_61_Conv_62": { + "sender": "Relu_61", + "receiver": "Conv_62", + "sender_port": "_61", + "receiver_port": "_61" + }, + "Conv_62_Relu_63": { + "sender": "Conv_62", + "receiver": "Relu_63", + "sender_port": "_62", + "receiver_port": "_62" + }, + "Relu_63_Conv_64": { + "sender": "Relu_63", + "receiver": "Conv_64", + "sender_port": "_63", + "receiver_port": "_63" + }, + "Conv_64_Relu_65": { + "sender": "Conv_64", + "receiver": "Relu_65", + "sender_port": "_64", + "receiver_port": "_64" + }, + "Relu_65_MaxPool_66": { + "sender": "Relu_65", + "receiver": "MaxPool_66", + "sender_port": "_65", + "receiver_port": "_65" + }, + "MaxPool_66_Conv_67": { + "sender": "MaxPool_66", + "receiver": "Conv_67", + "sender_port": "_66", + "receiver_port": "_66" + }, + "Conv_67_Relu_68": { + "sender": "Conv_67", + "receiver": "Relu_68", + "sender_port": "_67", + "receiver_port": "_67" + }, + "Relu_68_Conv_69": { + "sender": "Relu_68", + "receiver": "Conv_69", + "sender_port": "_68", + "receiver_port": "_68" + }, + "Conv_69_Relu_70": { + "sender": "Conv_69", + "receiver": "Relu_70", + "sender_port": "_69", + "receiver_port": "_69" + }, + "Relu_70_Conv_71": { + "sender": "Relu_70", + "receiver": "Conv_71", + "sender_port": "_70", + "receiver_port": "_70" + }, + "Conv_71_Relu_72": { + "sender": "Conv_71", + "receiver": "Relu_72", + "sender_port": "_71", + "receiver_port": "_71" + }, + "Relu_72_Conv_73": { + "sender": "Relu_72", + "receiver": "Conv_73", + "sender_port": "_72", + "receiver_port": "_72" + }, + "Conv_73_Relu_74": { + "sender": "Conv_73", + "receiver": "Relu_74", + "sender_port": "_73", + "receiver_port": "_73" + }, + "Relu_74_MaxPool_75": { + "sender": "Relu_74", + "receiver": "MaxPool_75", + "sender_port": "_74", + "receiver_port": "_74" + }, + "MaxPool_75_AveragePool_76": { + "sender": "MaxPool_75", + "receiver": "AveragePool_76", + "sender_port": "_75", + "receiver_port": "_75" + }, + "AveragePool_76_Flatten_77": { + "sender": "AveragePool_76", + "receiver": "Flatten_77", + "sender_port": "_76", + "receiver_port": "_76" + }, + "Flatten_77_Gemm_78": { + "sender": "Flatten_77", + "receiver": "Gemm_78", + "sender_port": "_77", + "receiver_port": "_77" + }, + "Gemm_78_Relu_79": { + "sender": "Gemm_78", + "receiver": "Relu_79", + "sender_port": "_78", + "receiver_port": "_78" + }, + "Relu_79_Gemm_80": { + "sender": "Relu_79", + "receiver": "Gemm_80", + "sender_port": "_79", + "receiver_port": "_79" + }, + "Gemm_80_Relu_81": { + "sender": "Gemm_80", + "receiver": "Relu_81", + "sender_port": "_80", + "receiver_port": "_80" + }, + "Relu_81_Gemm_82": { + "sender": "Relu_81", + "receiver": "Gemm_82", + "sender_port": "_81", + "receiver_port": "_81" + } + } + } + }, + "onnx_opset_version": 9 + } +} diff --git a/examples/PyTorch/PyTorch_MDF/vgg19.py b/examples/PyTorch/PyTorch_MDF/vgg19.py new file mode 100644 index 00000000..a6527527 --- /dev/null +++ b/examples/PyTorch/PyTorch_MDF/vgg19.py @@ -0,0 +1,35 @@ +import torchvision.models as models +import torch +from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +vgg19 = models.vgg19(pretrained=False) + + +def main(): + # changed import call + from modeci_mdf.execution_engine import EvaluableGraph + + # Create some test inputs for the model + x = torch.zeros((1, 3, 224, 224)) + ebv_output = torch.zeros((1,)) + + # Turn on eval mode for model to get rid of any randomization due to things like BatchNorm or Dropout + vgg19.eval() + + # Run the model once to get some ground truth outpot (from PyTorch) + output = vgg19(x).detach().numpy() + + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=vgg19, + args=(x), + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + # Output the model to JSON + mdf_model.to_json_file("vgg19.json") + + +if __name__ == "__main__": + main() diff --git a/examples/PyTorch/regenerate.sh b/examples/PyTorch/regenerate.sh old mode 100755 new mode 100644 diff --git a/setup.py b/setup.py index 83767b00..1eff8fdd 100644 --- a/setup.py +++ b/setup.py @@ -27,7 +27,9 @@ "Jinja2<3.1", "torchviz", "netron", - "torch<=1.11.0", + "torch>=1.11.0", + "torchvision", + "h5py", ], "dev": [], } diff --git a/src/modeci_mdf/execution_engine.py b/src/modeci_mdf/execution_engine.py index 2f55cdd8..7fb2a741 100644 --- a/src/modeci_mdf/execution_engine.py +++ b/src/modeci_mdf/execution_engine.py @@ -160,7 +160,7 @@ def evaluate_onnx_expr( for k, v in kwargs_for_onnx.items() if ( (k in onnx_arguments or has_variadic) - and "onnx::" not in k # filter Evaluable__ class names + and "onnx_" not in k # filter Evaluable__ class names ) } diff --git a/src/modeci_mdf/functions/onnx.py b/src/modeci_mdf/functions/onnx.py index 0ff9a711..e6bc4dc4 100644 --- a/src/modeci_mdf/functions/onnx.py +++ b/src/modeci_mdf/functions/onnx.py @@ -28,7 +28,7 @@ # Use the same ONNX opset version that torch is using for defaults now # from torch.onnx.symbolic_helper import _default_onnx_opset_version as onnx_opset_version -onnx_opset_version = 13 +onnx_opset_version = 15 __all__ = [ "predict_with_onnxruntime", @@ -329,11 +329,29 @@ def onnx_wrapper(*args, **kwargs): for kw in kwargs: if kw not in schema.attributes: raise ValueError( - f"Passed unkown attribute ({kw}) to ONNX op {schema.name}, supported attributes: {list(schema.attributes)}" + f"Passed unknown attribute ({kw}) to ONNX op {schema.name}, supported attributes: {list(schema.attributes)}" ) + # For some reason ONNX models are getting shape arguments that are 2D when they need to be 1D + if schema.name == "Reshape": + inputs_dict["shape"] = inputs_dict["shape"].flatten() + output_names = [out.name for out in schema.outputs] + # We need to handle BatchNormalization differently, it has 1 required output plus 2 optional outputs + # that are only allowed if training mode is set to 1. + if schema.name == "BatchNormalization" and kwargs["training_mode"] == 0: + output_names = ["Y"] + + out_dict = run_onnx_op( + op_name=schema.name, + inputs=inputs_dict, + output_names=output_names, + **kwargs, + ) + + return tuple(out_dict.values()) + out_dict = run_onnx_op( op_name=schema.name, inputs=inputs_dict, output_names=output_names, **kwargs ) diff --git a/src/modeci_mdf/interfaces/pytorch/exporter.py b/src/modeci_mdf/interfaces/pytorch/exporter.py index 2abe39d0..7a622c27 100644 --- a/src/modeci_mdf/interfaces/pytorch/exporter.py +++ b/src/modeci_mdf/interfaces/pytorch/exporter.py @@ -2,17 +2,11 @@ Functions for converting from MDF models to PyTorch """ import collections -import os -import sys -import h5py -import importlib -from collections import defaultdict -from inspect import getmembers, signature, getsource, isclass -import modeci_mdf import numpy as np import torch -from typing import Union, Dict, Any, Tuple, List, Callable -import torch.nn as nn + +from typing import Dict, Any, List + from modeci_mdf.functions.standard import mdf_functions from modeci_mdf.utils import load_mdf from modeci_mdf.execution_engine import EvaluableGraph diff --git a/src/modeci_mdf/interfaces/pytorch/importer.py b/src/modeci_mdf/interfaces/pytorch/importer.py index 454b9dc1..557a7a48 100644 --- a/src/modeci_mdf/interfaces/pytorch/importer.py +++ b/src/modeci_mdf/interfaces/pytorch/importer.py @@ -40,7 +40,7 @@ def make_node_id(node: torch.Node) -> str: def make_func_id(node: torch.Node) -> str: """Helper function to get a unique name (used in MDF as id) for a TorchScript node's op/function.""" - return f"{node.kind()}_1" + return node.kind().replace("::", "_") + "_1" def make_model_graph_name( @@ -103,7 +103,7 @@ def process_torch_schema( def process_onnx_schema( - node: torch.Node, port_mapper: "PortMapper" + node: torch.Node, consts: Dict, port_mapper: "PortMapper" ) -> Tuple[Dict[str, str], Dict[str, Any]]: """ Retrieve the argument names and attributes (parameters in MDF) for this Operation. @@ -124,7 +124,9 @@ def process_onnx_schema( # If this is an ONNX op, we need to get the schema from ONNX if "onnx::" in node.kind(): try: - schema = onnx.defs.get_schema(node.kind().split("::")[-1]) + schema = onnx.defs.get_schema( + node.kind().split("::")[-1], modeci_onnx_opset_version + ) schema_args = {} if len(schema.inputs) > 0: @@ -154,11 +156,18 @@ def process_onnx_schema( else: raise ValueError(f"Cannot process ONNX schema for non ONNX node: {node}") - # ONNX attributes are equivalent to MDF parameters really + # Any inputs that are from constant nodes should be parameters in MDF parameters = { - aname: convert_to_serializable(node[aname]) for aname in node.attributeNames() + port_mapper.id_to_port(inp): consts[inp] + for i, inp in enumerate(inputs) + if inp in consts } + # ONNX attributes are equivalent to MDF parameters + parameters.update( + {aname: convert_to_serializable(node[aname]) for aname in node.attributeNames()} + ) + return schema_args, parameters @@ -177,6 +186,10 @@ def get_graph_constants(graph: torch.Graph) -> Dict[str, Any]: for o in n.outputs(): consts[o.unique()] = convert_to_serializable(o.toIValue()) + # Get the ONNX constant nodes too + for n in graph.findAllNodes("onnx::Constant"): + consts[list(n.outputs())[0].unique()] = n["value"].numpy() + return consts @@ -203,6 +216,9 @@ def id_to_port(self, id: str): # Remove :: from ids, these cause issues with parsing in the execution engine new_name = new_name.replace("::", "_") + # Renive aby "-" from names, these cause issues with parsing in the execution engine + new_name = new_name.replace("-", "_") + # If the first character is a digit, precede with an underscore so this can never be interpreted # as number down the line. if new_name[0].isdigit(): @@ -278,9 +294,13 @@ def torchnode_to_mdfnode( """ op = node.kind() + # Lookup the schema. For some reason we cannot just call node.schema(), it returns "(no schema)", huh? + # We need to do this the hard way. + schema = onnx.defs.get_schema(op.replace("onnx::", ""), modeci_onnx_opset_version) + # Exclude constants (as nodes) from the MDF graph. We will instead insert them as parameters to the nodes that # they project to. - if op == "prim::Constant": + if op in ("prim::Constant", "onnx::Constant"): return None # If we are dealing with a loop node, we need to recursively create a sub-graph for the loop body @@ -300,7 +320,7 @@ def torchnode_to_mdfnode( # Get the argument names and parameter names and values for this Node's operation if "onnx::" in op: - arguments, parameters = process_onnx_schema(node, port_mapper) + arguments, parameters = process_onnx_schema(node, consts, port_mapper) else: arguments, parameters = process_torch_schema(node, consts, port_mapper) @@ -309,9 +329,28 @@ def torchnode_to_mdfnode( mdf_node.parameters.append(Parameter(id=p, value=parameters[p])) # Add any output ports - for o in outputs: + subscript = lambda x: "" if len(schema.outputs) <= 1 else f"[{x}]" + for out_num, o in enumerate(outputs): + + # Try to get the shape and type of the out port + out_type = node.outputsAt(out_num).type() + try: + out_dtype = str(out_type.dtype()).replace("torch.", "") + except RuntimeError: + out_dtype = str(out_type.getElementType()) + + try: + shape = tuple(out_type.sizes()) if out_type.sizes() else None + except RuntimeError: + shape = None + mdf_node.output_ports.append( - OutputPort(id=port_mapper.id_to_port(o), value=make_func_id(node)) + OutputPort( + id=port_mapper.id_to_port(o), + value=make_func_id(node) + subscript(out_num), + shape=shape, + type=out_dtype, + ) ) # Add any input ports to the node, exclude inputs from constant nodes, these are parameters now @@ -321,13 +360,18 @@ def torchnode_to_mdfnode( # Try to get the shape and type of the input port inp_type = node.inputsAt(inp_i).type() + try: + inp_dtype = str(inp_type.dtype()).replace("torch.", "") + except RuntimeError: + inp_dtype = str(inp_type.getElementType()) + try: shape = tuple(inp_type.sizes()) if inp_type.sizes() else None except RuntimeError: shape = None mdf_node.input_ports.append( - InputPort(id=ip_name, shape=shape, type=str(inp_type)) + InputPort(id=ip_name, shape=shape, type=inp_dtype) ) # Add Parameter @@ -420,7 +464,7 @@ def pytorch_to_mdf( Args: model: The model to translate into MDF. args: The input arguments for this model. If a nn.Module is passed then the model will be traced with these - inputs. If a ScriptModule is passed, they are still needed to deterimine input shapes. + inputs. If a ScriptModule is passed, they are still needed to determine input shapes. trace: Force the use of tracing to compile the model. The default is to use torch.jit.script use_onnx_ops: Use ONNX ops when possible, fallback to ATEN ops when not available. Default is True. If False, use only ATEN ops. @@ -429,6 +473,10 @@ def pytorch_to_mdf( The translated MDF model """ + # Special case for common case of passing a single Tensor + if isinstance(args, (torch.Tensor, int, float, bool)): + args = (args,) + # Get the graph and nodes from the TorchScript model try: # If the graph attribute is available, we are dealing with a already jitted model (ScriptModule, ScriptFunciton, @@ -454,17 +502,23 @@ def pytorch_to_mdf( # Call out to a part of the ONNX exporter that simiplifies the graph before ONNX export. from torch.onnx.utils import _model_to_graph from torch.onnx import TrainingMode - from torch.onnx.symbolic_helper import ( - _export_onnx_opset_version, - _set_opset_version, - ) + from torch.onnx.symbolic_helper import _set_opset_version + + try: + from torch.onnx.symbolic_helper import _export_onnx_opset_version + except ImportError: + + # This is need for PyTorch 1.12 + from torch.onnx._globals import GLOBALS + + _export_onnx_opset_version = GLOBALS.export_onnx_opset_version previous_opset_version = _export_onnx_opset_version _set_opset_version(modeci_onnx_opset_version) graph, params_dict, torch_out = _model_to_graph( model=jit_model if graph else model, args=args, - do_constant_folding=True, + do_constant_folding=False, training=TrainingMode.EVAL, operator_export_type=operator_export_type, dynamic_axes={}, diff --git a/tests/interfaces/pytorch/conftest.py b/tests/interfaces/pytorch/conftest.py new file mode 100644 index 00000000..1cf497dd --- /dev/null +++ b/tests/interfaces/pytorch/conftest.py @@ -0,0 +1,461 @@ +import pytest + +try: + import torch + import torch.nn as nn + import torch.nn.functional as F + import torchvision.models as models + + # Make PyTorch deterministic for testing. + torch.use_deterministic_algorithms(True) + torch.backends.cudnn.deterministic = True + torch.manual_seed(0) + + from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + +except ModuleNotFoundError: + pytest.mark.skip( + "Skipping PyTorch interface tests because pytorch is not installed." + ) + + +@pytest.fixture +def simple_convolution_pytorch(): + class CNN(nn.Module): + def __init__(self, in_channels=1, num_classes=10): + super().__init__() + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=8, + kernel_size=(3, 3), + ) + self.pool = nn.MaxPool2d(kernel_size=(2, 2), stride=(1, 1)) + + self.fc1 = nn.Linear(8 * 25 * 25, num_classes) + + def forward(self, x): + x = F.relu(self.conv1(x)) + x = self.pool(x) + x = x.reshape(x.shape[0], -1) + x = self.fc1(x) + return x + + # Hyperparameters + in_channels = 1 + num_classes = 10 + + model = CNN(in_channels=in_channels, num_classes=num_classes) + return model + + +@pytest.fixture +def convolution_pytorch(): + class CNN(nn.Module): + def __init__(self, in_channels=1, num_classes=10): + super().__init__() + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=8, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + ) + self.pool = nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2)) + self.conv2 = nn.Conv2d( + in_channels=8, + out_channels=16, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + ) + self.fc1 = nn.Linear(16 * 7 * 7, num_classes) + + def forward(self, x): + x = F.relu(self.conv1(x)) + x = self.pool(x) + x = F.relu(self.conv2(x)) + x = self.pool(x) + x = x.reshape(x.shape[0], -1) + x = self.fc1(x) + return x + + # Hyperparameters + in_channels = 1 + num_classes = 10 + + model = CNN(in_channels=in_channels, num_classes=num_classes) + return model + + +@pytest.fixture +def inception_model_pytorch(): + """The InceptionBlocks model the WebGME folks provided as a test case for deepforge.""" + + class InceptionBlocks(nn.Module): + def __init__(self): + super().__init__() + + self.asymmetric_pad = nn.ZeroPad2d((0, 1, 0, 1)) + self.conv2d = nn.Conv2d( + in_channels=5, out_channels=64, kernel_size=(5, 5), padding=2, bias=True + ) + self.prelu = nn.PReLU(init=0.0) + self.averagepooling2d = nn.AvgPool2d((2, 2), stride=2, padding=0) + self.conv2d2 = nn.Conv2d( + in_channels=64, + out_channels=48, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu2 = nn.PReLU(init=0.0) + self.conv2d3 = nn.Conv2d( + in_channels=48, + out_channels=64, + kernel_size=(3, 3), + padding=1, + bias=True, + ) + self.prelu3 = nn.PReLU(init=0.0) + self.conv2d4 = nn.Conv2d( + in_channels=64, + out_channels=48, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu4 = nn.PReLU(init=0.0) + self.averagepooling2d2 = nn.AvgPool2d((2, 2), stride=1) + self.conv2d5 = nn.Conv2d( + in_channels=64, + out_channels=64, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu5 = nn.PReLU(init=0.0) + self.conv2d6 = nn.Conv2d( + in_channels=64, + out_channels=48, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu6 = nn.PReLU(init=0.0) + self.conv2d7 = nn.Conv2d( + in_channels=48, + out_channels=64, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu7 = nn.PReLU(init=0.0) + self.conv2d8 = nn.Conv2d( + in_channels=240, + out_channels=64, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.conv2d9 = nn.Conv2d( + in_channels=240, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.conv2d10 = nn.Conv2d( + in_channels=240, + out_channels=64, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu8 = nn.PReLU(init=0.0) + self.conv2d11 = nn.Conv2d( + in_channels=64, + out_channels=92, + kernel_size=(5, 5), + padding=2, + bias=True, + ) + self.prelu9 = nn.PReLU(init=0.0) + self.prelu10 = nn.PReLU(init=0.0) + self.averagepooling2d3 = nn.AvgPool2d((2, 2), stride=1, padding=0) + self.conv2d12 = nn.Conv2d( + in_channels=240, + out_channels=64, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu11 = nn.PReLU(init=0.0) + self.conv2d13 = nn.Conv2d( + in_channels=64, + out_channels=92, + kernel_size=(3, 3), + padding=1, + bias=True, + ) + self.prelu12 = nn.PReLU(init=0.0) + self.prelu13 = nn.PReLU(init=0.0) + self.averagepooling2d4 = nn.AvgPool2d((2, 2), stride=2, padding=0) + self.conv2d14 = nn.Conv2d( + in_channels=340, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu14 = nn.PReLU(init=0.0) + self.conv2d15 = nn.Conv2d( + in_channels=92, + out_channels=128, + kernel_size=(5, 5), + padding=2, + bias=True, + ) + self.prelu15 = nn.PReLU(init=0.0) + self.conv2d16 = nn.Conv2d( + in_channels=340, + out_channels=128, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu16 = nn.PReLU(init=0.0) + self.conv2d17 = nn.Conv2d( + in_channels=340, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu17 = nn.PReLU(init=0.0) + self.averagepooling2d5 = nn.AvgPool2d((2, 2), stride=1, padding=0) + self.conv2d18 = nn.Conv2d( + in_channels=340, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu18 = nn.PReLU(init=0.0) + self.conv2d19 = nn.Conv2d( + in_channels=92, + out_channels=128, + kernel_size=(3, 3), + padding=1, + bias=True, + ) + self.prelu19 = nn.PReLU(init=0.0) + self.conv2d20 = nn.Conv2d( + in_channels=476, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu20 = nn.PReLU(init=0.0) + self.conv2d21 = nn.Conv2d( + in_channels=92, + out_channels=128, + kernel_size=(3, 3), + padding=1, + bias=True, + ) + self.prelu21 = nn.PReLU(init=0.0) + self.conv2d22 = nn.Conv2d( + in_channels=476, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu22 = nn.PReLU(init=0.0) + self.averagepooling2d6 = nn.AvgPool2d((2, 2), stride=1, padding=0) + self.conv2d23 = nn.Conv2d( + in_channels=476, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu23 = nn.PReLU(init=0.0) + self.conv2d24 = nn.Conv2d( + in_channels=92, + out_channels=128, + kernel_size=(5, 5), + padding=2, + bias=True, + ) + self.prelu24 = nn.PReLU(init=0.0) + self.conv2d25 = nn.Conv2d( + in_channels=476, + out_channels=128, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu25 = nn.PReLU(init=0.0) + self.averagepooling2d7 = nn.AvgPool2d((2, 2), stride=2, padding=0) + self.conv2d26 = nn.Conv2d( + in_channels=476, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu26 = nn.PReLU(init=0.0) + self.averagepooling2d8 = nn.AvgPool2d((2, 2), stride=1, padding=0) + self.conv2d27 = nn.Conv2d( + in_channels=476, + out_channels=92, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu27 = nn.PReLU(init=0.0) + self.conv2d28 = nn.Conv2d( + in_channels=92, + out_channels=128, + kernel_size=(3, 3), + padding=1, + bias=True, + ) + self.prelu28 = nn.PReLU(init=0.0) + self.conv2d29 = nn.Conv2d( + in_channels=476, + out_channels=128, + kernel_size=(1, 1), + padding=0, + bias=True, + ) + self.prelu29 = nn.PReLU(init=0.0) + self.dense = nn.Linear(22273, 1096, bias=True) + self.prelu30 = nn.PReLU(init=0.0) + self.dense2 = nn.Linear(1096, 1096, bias=True) + self.prelu31 = nn.PReLU(init=0.0) + self.dense3 = nn.Linear(1096, 180, bias=True) + + def forward(self, galaxy_images_output, ebv_output): + conv2d_output = self.conv2d(galaxy_images_output) + prelu_output = self.prelu(conv2d_output) + averagepooling2d_output = self.averagepooling2d(prelu_output) + conv2d_output2 = self.conv2d2(averagepooling2d_output) + prelu_output2 = self.prelu2(conv2d_output2) + conv2d_output3 = self.conv2d3(prelu_output2) + prelu_output3 = self.prelu3(conv2d_output3) + conv2d_output4 = self.conv2d4(averagepooling2d_output) + prelu_output4 = self.prelu4(conv2d_output4) + prelu_output4 = self.asymmetric_pad(prelu_output4) + averagepooling2d_output2 = self.averagepooling2d2(prelu_output4) + conv2d_output5 = self.conv2d5(averagepooling2d_output) + prelu_output5 = self.prelu5(conv2d_output5) + conv2d_output6 = self.conv2d6(averagepooling2d_output) + prelu_output6 = self.prelu6(conv2d_output6) + conv2d_output7 = self.conv2d7(prelu_output6) + prelu_output7 = self.prelu7(conv2d_output7) + concatenate_output = torch.cat( + (prelu_output5, prelu_output3, prelu_output7, averagepooling2d_output2), + dim=1, + ) + conv2d_output8 = self.conv2d8(concatenate_output) + conv2d_output9 = self.conv2d9(concatenate_output) + conv2d_output10 = self.conv2d10(concatenate_output) + prelu_output8 = self.prelu8(conv2d_output10) + conv2d_output11 = self.conv2d11(prelu_output8) + prelu_output9 = self.prelu9(conv2d_output11) + prelu_output10 = self.prelu10(conv2d_output8) + prelu_output10 = self.asymmetric_pad(prelu_output10) + averagepooling2d_output3 = self.averagepooling2d3(prelu_output10) + conv2d_output12 = self.conv2d12(concatenate_output) + prelu_output11 = self.prelu11(conv2d_output12) + conv2d_output13 = self.conv2d13(prelu_output11) + prelu_output12 = self.prelu12(conv2d_output13) + prelu_output13 = self.prelu13(conv2d_output9) + concatenate_output2 = torch.cat( + ( + prelu_output13, + prelu_output12, + prelu_output9, + averagepooling2d_output3, + ), + dim=1, + ) + averagepooling2d_output4 = self.averagepooling2d4(concatenate_output2) + conv2d_output14 = self.conv2d14(averagepooling2d_output4) + prelu_output14 = self.prelu14(conv2d_output14) + conv2d_output15 = self.conv2d15(prelu_output14) + prelu_output15 = self.prelu15(conv2d_output15) + conv2d_output16 = self.conv2d16(averagepooling2d_output4) + prelu_output16 = self.prelu16(conv2d_output16) + conv2d_output17 = self.conv2d17(averagepooling2d_output4) + prelu_output17 = self.prelu17(conv2d_output17) + prelu_output17 = self.asymmetric_pad(prelu_output17) + averagepooling2d_output5 = self.averagepooling2d5(prelu_output17) + conv2d_output18 = self.conv2d18(averagepooling2d_output4) + prelu_output18 = self.prelu18(conv2d_output18) + conv2d_output19 = self.conv2d19(prelu_output18) + prelu_output19 = self.prelu19(conv2d_output19) + concatenate_output3 = torch.cat( + ( + prelu_output16, + prelu_output19, + prelu_output15, + averagepooling2d_output5, + ), + dim=1, + ) + conv2d_output20 = self.conv2d20(concatenate_output3) + prelu_output20 = self.prelu20(conv2d_output20) + conv2d_output21 = self.conv2d21(prelu_output20) + prelu_output21 = self.prelu21(conv2d_output21) + conv2d_output22 = self.conv2d22(concatenate_output3) + prelu_output22 = self.prelu22(conv2d_output22) + prelu_output22 = self.asymmetric_pad(prelu_output22) + averagepooling2d_output6 = self.averagepooling2d6(prelu_output22) + conv2d_output23 = self.conv2d23(concatenate_output3) + prelu_output23 = self.prelu23(conv2d_output23) + conv2d_output24 = self.conv2d24(prelu_output23) + prelu_output24 = self.prelu24(conv2d_output24) + conv2d_output25 = self.conv2d25(concatenate_output3) + prelu_output25 = self.prelu25(conv2d_output25) + concatenate_output4 = torch.cat( + ( + prelu_output25, + prelu_output21, + prelu_output24, + averagepooling2d_output6, + ), + dim=1, + ) + averagepooling2d_output7 = self.averagepooling2d7(concatenate_output4) + conv2d_output26 = self.conv2d26(averagepooling2d_output7) + prelu_output26 = self.prelu26(conv2d_output26) + prelu_output26 = self.asymmetric_pad(prelu_output26) + averagepooling2d_output8 = self.averagepooling2d8(prelu_output26) + conv2d_output27 = self.conv2d27(averagepooling2d_output7) + prelu_output27 = self.prelu27(conv2d_output27) + conv2d_output28 = self.conv2d28(prelu_output27) + prelu_output28 = self.prelu28(conv2d_output28) + conv2d_output29 = self.conv2d29(averagepooling2d_output7) + prelu_output29 = self.prelu29(conv2d_output29) + concatenate_output5 = torch.cat( + (prelu_output29, prelu_output28, averagepooling2d_output8), dim=1 + ) + flatten_output = torch.flatten(concatenate_output5) + concatenate_output6 = torch.cat((flatten_output, ebv_output), dim=0) + dense_output = self.dense(concatenate_output6) + prelu_output30 = self.prelu30(dense_output) + dense_output2 = self.dense2(prelu_output30) + prelu_output31 = self.prelu31(dense_output2) + dense_output3 = self.dense3(prelu_output31) + + return dense_output3 + + torch.manual_seed(0) + model = InceptionBlocks() + model.eval() + + return model diff --git a/tests/interfaces/pytorch/test_import.py b/tests/interfaces/pytorch/test_import.py index 122d2284..493881dc 100644 --- a/tests/interfaces/pytorch/test_import.py +++ b/tests/interfaces/pytorch/test_import.py @@ -1,407 +1,140 @@ +""" +Tests for importing of PyTorch models into MDF. These tests use a lot of fixtures for models setup in ./conftest.py +""" import pytest +import inspect import numpy as np -try: - import torch - import torch.nn as nn - - torch.use_deterministic_algorithms(True) - torch.backends.cudnn.deterministic = True +from modeci_mdf.mdf import Model +from modeci_mdf.execution_engine import EvaluableGraph +try: from modeci_mdf.interfaces.pytorch import pytorch_to_mdf + import torch + import torchvision.models as models + except ModuleNotFoundError: + models = None pytest.mark.skip( "Skipping PyTorch interface tests because pytorch is not installed." ) -from modeci_mdf.execution_engine import EvaluableGraph -from modeci_mdf.utils import load_mdf_json +def _get_torchvision_models(): + """ + Get all the backbone models in torch vision, suprised there is no function to do this in torchvision. + """ + + if models is None: + return [] + + models_to_test = [] + model_classes = set() + for model_name, model in models.__dict__.items(): + try: + params = inspect.signature(model).parameters + + # Get the model class that this construction function returns. To cut down on tests, + # lets only test one version of each model. + return_type = inspect.signature(model).return_annotation + + if ( + "weights" in params + or "pretrained" in params + and return_type not in model_classes + ): + models_to_test.append(model) + if return_type: + model_classes.add(return_type) + + except TypeError: + continue + + # New API for specifying pretrained=False is weights=None. pretrained keyword + # will be removed soon. This handles that for all models depending on PyTorch + # version. + is_new_weights_api = "weights" in inspect.signature(models.resnet18).parameters + model_weights_spec = ( + {"weights": None} if is_new_weights_api else {"pretrained": False} + ) + pytest_params = [] + for model in models_to_test: + t = (model, model(**model_weights_spec)) + if model.__name__ == "inception_v3": + pytest_params.append( + pytest.param( + *t, + marks=pytest.mark.xfail( + reason="Inception-V3 is failing to match currently." + ), + ) + ) + else: + pytest_params.append(t) + + return pytest_params + + +def _run_and_check_model(model, input=None): + """ + Helper function that runs a complete set of tests on a model + - Runs the model in PyTorch to get expected output. + - Converts model to MDF and runs in Python execution engine. + - Compares the results. + """ + + # Create some test inputs for the model + if input is None: + input = torch.rand((1, 3, 224, 224)) + + # Get rid of randomization due to Dropout + model.eval() -@pytest.fixture -def inception_model_pytorch(): - """The InceptionBlocks model the WebGME folks provided as a test case for deepforge.""" + with torch.no_grad(): + # Run the model once to get some ground truth output (from PyTorch) + output = model(input).detach().numpy() - class InceptionBlocks(nn.Module): - def __init__(self): - super().__init__() + # Convert to MDF + mdf_model, params_dict = pytorch_to_mdf( + model=model, + args=input, + trace=True, + ) + # Get the graph + mdf_graph = mdf_model.graphs[0] + params_dict["input1"] = input.numpy() - self.asymmetric_pad = nn.ZeroPad2d((0, 1, 0, 1)) - self.conv2d = nn.Conv2d( - in_channels=5, out_channels=64, kernel_size=(5, 5), padding=2, bias=True - ) - self.prelu = nn.PReLU(init=0.0) - self.averagepooling2d = nn.AvgPool2d((2, 2), stride=2, padding=0) - self.conv2d2 = nn.Conv2d( - in_channels=64, - out_channels=48, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu2 = nn.PReLU(init=0.0) - self.conv2d3 = nn.Conv2d( - in_channels=48, - out_channels=64, - kernel_size=(3, 3), - padding=1, - bias=True, - ) - self.prelu3 = nn.PReLU(init=0.0) - self.conv2d4 = nn.Conv2d( - in_channels=64, - out_channels=48, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu4 = nn.PReLU(init=0.0) - self.averagepooling2d2 = nn.AvgPool2d((2, 2), stride=1) - self.conv2d5 = nn.Conv2d( - in_channels=64, - out_channels=64, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu5 = nn.PReLU(init=0.0) - self.conv2d6 = nn.Conv2d( - in_channels=64, - out_channels=48, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu6 = nn.PReLU(init=0.0) - self.conv2d7 = nn.Conv2d( - in_channels=48, - out_channels=64, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu7 = nn.PReLU(init=0.0) - self.conv2d8 = nn.Conv2d( - in_channels=240, - out_channels=64, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.conv2d9 = nn.Conv2d( - in_channels=240, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.conv2d10 = nn.Conv2d( - in_channels=240, - out_channels=64, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu8 = nn.PReLU(init=0.0) - self.conv2d11 = nn.Conv2d( - in_channels=64, - out_channels=92, - kernel_size=(5, 5), - padding=2, - bias=True, - ) - self.prelu9 = nn.PReLU(init=0.0) - self.prelu10 = nn.PReLU(init=0.0) - self.averagepooling2d3 = nn.AvgPool2d((2, 2), stride=1, padding=0) - self.conv2d12 = nn.Conv2d( - in_channels=240, - out_channels=64, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu11 = nn.PReLU(init=0.0) - self.conv2d13 = nn.Conv2d( - in_channels=64, - out_channels=92, - kernel_size=(3, 3), - padding=1, - bias=True, - ) - self.prelu12 = nn.PReLU(init=0.0) - self.prelu13 = nn.PReLU(init=0.0) - self.averagepooling2d4 = nn.AvgPool2d((2, 2), stride=2, padding=0) - self.conv2d14 = nn.Conv2d( - in_channels=340, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu14 = nn.PReLU(init=0.0) - self.conv2d15 = nn.Conv2d( - in_channels=92, - out_channels=128, - kernel_size=(5, 5), - padding=2, - bias=True, - ) - self.prelu15 = nn.PReLU(init=0.0) - self.conv2d16 = nn.Conv2d( - in_channels=340, - out_channels=128, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu16 = nn.PReLU(init=0.0) - self.conv2d17 = nn.Conv2d( - in_channels=340, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu17 = nn.PReLU(init=0.0) - self.averagepooling2d5 = nn.AvgPool2d((2, 2), stride=1, padding=0) - self.conv2d18 = nn.Conv2d( - in_channels=340, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu18 = nn.PReLU(init=0.0) - self.conv2d19 = nn.Conv2d( - in_channels=92, - out_channels=128, - kernel_size=(3, 3), - padding=1, - bias=True, - ) - self.prelu19 = nn.PReLU(init=0.0) - self.conv2d20 = nn.Conv2d( - in_channels=476, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu20 = nn.PReLU(init=0.0) - self.conv2d21 = nn.Conv2d( - in_channels=92, - out_channels=128, - kernel_size=(3, 3), - padding=1, - bias=True, - ) - self.prelu21 = nn.PReLU(init=0.0) - self.conv2d22 = nn.Conv2d( - in_channels=476, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu22 = nn.PReLU(init=0.0) - self.averagepooling2d6 = nn.AvgPool2d((2, 2), stride=1, padding=0) - self.conv2d23 = nn.Conv2d( - in_channels=476, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu23 = nn.PReLU(init=0.0) - self.conv2d24 = nn.Conv2d( - in_channels=92, - out_channels=128, - kernel_size=(5, 5), - padding=2, - bias=True, - ) - self.prelu24 = nn.PReLU(init=0.0) - self.conv2d25 = nn.Conv2d( - in_channels=476, - out_channels=128, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu25 = nn.PReLU(init=0.0) - self.averagepooling2d7 = nn.AvgPool2d((2, 2), stride=2, padding=0) - self.conv2d26 = nn.Conv2d( - in_channels=476, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu26 = nn.PReLU(init=0.0) - self.averagepooling2d8 = nn.AvgPool2d((2, 2), stride=1, padding=0) - self.conv2d27 = nn.Conv2d( - in_channels=476, - out_channels=92, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu27 = nn.PReLU(init=0.0) - self.conv2d28 = nn.Conv2d( - in_channels=92, - out_channels=128, - kernel_size=(3, 3), - padding=1, - bias=True, - ) - self.prelu28 = nn.PReLU(init=0.0) - self.conv2d29 = nn.Conv2d( - in_channels=476, - out_channels=128, - kernel_size=(1, 1), - padding=0, - bias=True, - ) - self.prelu29 = nn.PReLU(init=0.0) - self.dense = nn.Linear(22273, 1096, bias=True) - self.prelu30 = nn.PReLU(init=0.0) - self.dense2 = nn.Linear(1096, 1096, bias=True) - self.prelu31 = nn.PReLU(init=0.0) - self.dense3 = nn.Linear(1096, 180, bias=True) - - def forward(self, galaxy_images_output, ebv_output): - conv2d_output = self.conv2d(galaxy_images_output) - prelu_output = self.prelu(conv2d_output) - averagepooling2d_output = self.averagepooling2d(prelu_output) - conv2d_output2 = self.conv2d2(averagepooling2d_output) - prelu_output2 = self.prelu2(conv2d_output2) - conv2d_output3 = self.conv2d3(prelu_output2) - prelu_output3 = self.prelu3(conv2d_output3) - conv2d_output4 = self.conv2d4(averagepooling2d_output) - prelu_output4 = self.prelu4(conv2d_output4) - prelu_output4 = self.asymmetric_pad(prelu_output4) - averagepooling2d_output2 = self.averagepooling2d2(prelu_output4) - conv2d_output5 = self.conv2d5(averagepooling2d_output) - prelu_output5 = self.prelu5(conv2d_output5) - conv2d_output6 = self.conv2d6(averagepooling2d_output) - prelu_output6 = self.prelu6(conv2d_output6) - conv2d_output7 = self.conv2d7(prelu_output6) - prelu_output7 = self.prelu7(conv2d_output7) - concatenate_output = torch.cat( - (prelu_output5, prelu_output3, prelu_output7, averagepooling2d_output2), - dim=1, - ) - conv2d_output8 = self.conv2d8(concatenate_output) - conv2d_output9 = self.conv2d9(concatenate_output) - conv2d_output10 = self.conv2d10(concatenate_output) - prelu_output8 = self.prelu8(conv2d_output10) - conv2d_output11 = self.conv2d11(prelu_output8) - prelu_output9 = self.prelu9(conv2d_output11) - prelu_output10 = self.prelu10(conv2d_output8) - prelu_output10 = self.asymmetric_pad(prelu_output10) - averagepooling2d_output3 = self.averagepooling2d3(prelu_output10) - conv2d_output12 = self.conv2d12(concatenate_output) - prelu_output11 = self.prelu11(conv2d_output12) - conv2d_output13 = self.conv2d13(prelu_output11) - prelu_output12 = self.prelu12(conv2d_output13) - prelu_output13 = self.prelu13(conv2d_output9) - concatenate_output2 = torch.cat( - ( - prelu_output13, - prelu_output12, - prelu_output9, - averagepooling2d_output3, - ), - dim=1, - ) - averagepooling2d_output4 = self.averagepooling2d4(concatenate_output2) - conv2d_output14 = self.conv2d14(averagepooling2d_output4) - prelu_output14 = self.prelu14(conv2d_output14) - conv2d_output15 = self.conv2d15(prelu_output14) - prelu_output15 = self.prelu15(conv2d_output15) - conv2d_output16 = self.conv2d16(averagepooling2d_output4) - prelu_output16 = self.prelu16(conv2d_output16) - conv2d_output17 = self.conv2d17(averagepooling2d_output4) - prelu_output17 = self.prelu17(conv2d_output17) - prelu_output17 = self.asymmetric_pad(prelu_output17) - averagepooling2d_output5 = self.averagepooling2d5(prelu_output17) - conv2d_output18 = self.conv2d18(averagepooling2d_output4) - prelu_output18 = self.prelu18(conv2d_output18) - conv2d_output19 = self.conv2d19(prelu_output18) - prelu_output19 = self.prelu19(conv2d_output19) - concatenate_output3 = torch.cat( - ( - prelu_output16, - prelu_output19, - prelu_output15, - averagepooling2d_output5, - ), - dim=1, - ) - conv2d_output20 = self.conv2d20(concatenate_output3) - prelu_output20 = self.prelu20(conv2d_output20) - conv2d_output21 = self.conv2d21(prelu_output20) - prelu_output21 = self.prelu21(conv2d_output21) - conv2d_output22 = self.conv2d22(concatenate_output3) - prelu_output22 = self.prelu22(conv2d_output22) - prelu_output22 = self.asymmetric_pad(prelu_output22) - averagepooling2d_output6 = self.averagepooling2d6(prelu_output22) - conv2d_output23 = self.conv2d23(concatenate_output3) - prelu_output23 = self.prelu23(conv2d_output23) - conv2d_output24 = self.conv2d24(prelu_output23) - prelu_output24 = self.prelu24(conv2d_output24) - conv2d_output25 = self.conv2d25(concatenate_output3) - prelu_output25 = self.prelu25(conv2d_output25) - concatenate_output4 = torch.cat( - ( - prelu_output25, - prelu_output21, - prelu_output24, - averagepooling2d_output6, - ), - dim=1, - ) - averagepooling2d_output7 = self.averagepooling2d7(concatenate_output4) - conv2d_output26 = self.conv2d26(averagepooling2d_output7) - prelu_output26 = self.prelu26(conv2d_output26) - prelu_output26 = self.asymmetric_pad(prelu_output26) - averagepooling2d_output8 = self.averagepooling2d8(prelu_output26) - conv2d_output27 = self.conv2d27(averagepooling2d_output7) - prelu_output27 = self.prelu27(conv2d_output27) - conv2d_output28 = self.conv2d28(prelu_output27) - prelu_output28 = self.prelu28(conv2d_output28) - conv2d_output29 = self.conv2d29(averagepooling2d_output7) - prelu_output29 = self.prelu29(conv2d_output29) - concatenate_output5 = torch.cat( - (prelu_output29, prelu_output28, averagepooling2d_output8), dim=1 - ) - flatten_output = torch.flatten(concatenate_output5) - concatenate_output6 = torch.cat((flatten_output, ebv_output), dim=0) - dense_output = self.dense(concatenate_output6) - prelu_output30 = self.prelu30(dense_output) - dense_output2 = self.dense2(prelu_output30) - prelu_output31 = self.prelu31(dense_output2) - dense_output3 = self.dense3(prelu_output31) - - return dense_output3 - - torch.manual_seed(0) - model = InceptionBlocks() - model.eval() + eg = EvaluableGraph(graph=mdf_graph, verbose=False) - return model + eg.evaluate(initializer=params_dict) + + output_mdf = eg.output_enodes[0].get_output() + assert np.allclose( + output, + output_mdf, + atol=1e-05, + ), f"Output from PyTorch and MDF do not match. MaxAbsError={np.max(np.abs(output - output_mdf))}" + + # Convert to JSON and back + mdf_model2 = Model.from_json(mdf_model.to_json()) -def _check_model(mdf_model): - """A helper function to JIT compile a function or torch.nn.Module into Torchscript and convert to MDF and check it""" +@pytest.mark.parametrize("model_init, model", _get_torchvision_models()) +def test_torchvision_models(model_init, model): + """Test importing the PyTorch model into MDF, executing in execution engine""" + _run_and_check_model(model) - # Generate JSON - mdf_model.to_json_file("test.json") - # Load the JSON - load_mdf_json("test.json") +def test_simple_convolution(simple_convolution_pytorch): + """Test a simple convolution neural network model""" + _run_and_check_model(simple_convolution_pytorch, torch.zeros((1, 1, 28, 28))) + + +def test_convolution(convolution_pytorch): + """Test a convolution neural network with more layers""" + _run_and_check_model(convolution_pytorch, torch.zeros((1, 1, 28, 28))) def test_simple_module(): @@ -417,7 +150,7 @@ def forward(self, x, y): use_onnx_ops=True, ) - _check_model(mdf_model) + mdf_model2 = Model.from_json(mdf_model.to_json()) def test_simple_function(): @@ -432,7 +165,7 @@ def simple(x, y): use_onnx_ops=True, ) - _check_model(mdf_model) + mdf_model2 = Model.from_json(mdf_model.to_json()) def test_inception(inception_model_pytorch): @@ -468,6 +201,4 @@ def test_inception(inception_model_pytorch): output_mdf, ) - -if __name__ == "__main__": - test_simple_module() + mdf_model2 = Model.from_json(mdf_model.to_json())