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fix tf conversion in new v6 models #5153

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glenn-jocher merged 2 commits into from
Oct 12, 2021
Merged

fix tf conversion in new v6 models #5153

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4126c9b
fix `tf` conversion in new v6 (#5147)
YoniChechik Oct 12, 2021
7f72359
sort imports
glenn-jocher Oct 12, 2021
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20 changes: 18 additions & 2 deletions models/tf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@
import torch.nn as nn
from tensorflow import keras

from models.common import Conv, Bottleneck, SPP, DWConv, Focus, BottleneckCSP, Concat, autopad, C3
from models.common import Bottleneck, BottleneckCSP, Concat, Conv, C3, DWConv, Focus, SPP, SPPF, autopad
from models.experimental import CrossConv, MixConv2d, attempt_load
from models.yolo import Detect
from utils.general import make_divisible, print_args, set_logging
Expand Down Expand Up @@ -183,6 +183,22 @@ def call(self, inputs):
return self.cv2(tf.concat([x] + [m(x) for m in self.m], 3))


class TFSPPF(keras.layers.Layer):
# Spatial pyramid pooling-Fast layer
def __init__(self, c1, c2, k=5, w=None):
super(TFSPPF, self).__init__()
c_ = c1 // 2 # hidden channels
self.cv1 = TFConv(c1, c_, 1, 1, w=w.cv1)
self.cv2 = TFConv(c_ * 4, c2, 1, 1, w=w.cv2)
self.m = keras.layers.MaxPool2D(pool_size=k, strides=1, padding='SAME')

def call(self, inputs):
x = self.cv1(inputs)
y1 = self.m(x)
y2 = self.m(y1)
return self.cv2(tf.concat([x, y1, y2, self.m(y2)], 3))


class TFDetect(keras.layers.Layer):
def __init__(self, nc=80, anchors=(), ch=(), imgsz=(640, 640), w=None): # detection layer
super(TFDetect, self).__init__()
Expand Down Expand Up @@ -272,7 +288,7 @@ def parse_model(d, ch, model, imgsz): # model_dict, input_channels(3)
pass

n = max(round(n * gd), 1) if n > 1 else n # depth gain
if m in [nn.Conv2d, Conv, Bottleneck, SPP, DWConv, MixConv2d, Focus, CrossConv, BottleneckCSP, C3]:
if m in [nn.Conv2d, Conv, Bottleneck, SPP, SPPF, DWConv, MixConv2d, Focus, CrossConv, BottleneckCSP, C3]:
c1, c2 = ch[f], args[0]
c2 = make_divisible(c2 * gw, 8) if c2 != no else c2

Expand Down