Merge branch 'master' into origin_master

# Conflicts:
#	coconut/astar.coco
#	coconut/auto_data.coco
#	coconut/convert.coco
#	coconut/omni_converter.coco
#	data_tree/__init__.py
#	data_tree/_series.py
#	data_tree/coconut/astar.py
#	data_tree/coconut/auto_data.py
#	data_tree/coconut/convert.py
#	data_tree/coconut/omni_converter.py
#	data_tree/ops/cache.py
#	data_tree/storage_manager.py
#	data_tree/util.py
#	test/coconut/__init__.py
#	test/test_conversion.py

Author: proboscis

coconut/calc.py

@@ -183,7 +183,7 @@ class ZippedCW(Sourced):
 
 class VizCW(Sourced):
     def __init__(self,src,visualizer:object->"displayable"):
-        self.src = src
+        self.value = src
         self.visualizer = visualizer
     @lazy
     def value(self):

coconut/controllable.coco

@@ -11,6 +11,7 @@ start = str_to_img_def("numpy,float32,HWC,RGB,0_1")
 end = str_to_img_def("torch,uint8,BHWC,RGB,0_255")
 data END from ImageDef
 data DUMMY from ImageDef
+from archpainter.rulebook import legacy_auto as auto
 def dummy_rule(imdef):
     return [(a->a,end,1,"dummy")]
 
@@ -95,7 +96,7 @@ def test_casting():
 
 def test_omni_converter():
     from data_tree.coconut.omni_converter import auto_img,cast_imdef_str_to_imdef,cast_imdef_to_imdef_str
-    from data_tree.coconut.auto_data import AutoData
+    from omni_converter.coconut.auto_data import AutoData
     x = np.ones((100,100,3),dtype="float32")
     auto_x:AutoData = auto_img("numpy,float32,HW,L,0_1")(x)
     assert (auto_x.to("numpy,float32,HW,L,0_255") == 255).all()
@@ -111,12 +112,10 @@ def test_omni_converter():
     #assert format == n_format,f"{format} != {n_format}"
 
 def test_tuple_conversion():
-    from data_tree import auto
     from archpainter.experiments.rgba2xyz_mod.instances import torch_xyz, pix2pix_rgb_batch, TORCH_XYZ_BATCH
     logger.info(auto(("image,RGB,RGB","image,RGB,RGB"))((None,None)).converter(("pix2pix_batch,nc=1", TORCH_XYZ_BATCH)))
 
 def test_rgb_to_yuv():
-    from data_tree import auto
     from archpainter.experiments.rgba2xyz_mod.instances import torch_xyz, pix2pix_rgb_batch, TORCH_XYZ_BATCH
     logger.info(auto("image,RGB,RGB")(None).converter("image,YCbCr,YCbCr"))
 

coconut/monad.coco

@@ -1,3 +1,4 @@
+<<<<<<< HEAD
 
 
 
@@ -29,3 +30,76 @@ def auto_img(codec):
     def _l(img):
         return AutoImage(img, codec,solver)
     return _l
+=======
+from omni_converter.auto_data.auto_v2 import RuledData
+from omni_converter.solver.rules import AutoRuleBook
+
+
+def managed_cache(root_dir):
+    from data_tree.cache import ConditionedFilePathProvider
+    return ConditionedFilePathProvider(root_dir)
+
+
+def series(iterable):
+    from data_tree._series import Series
+    return Series.from_iterable(iterable)
+
+
+def unlist_auto(items):
+    from data_tree.coconut.omni_converter import unlist
+    return unlist(items)
+
+
+# def auto(format) -> Callable[[Any], RuledData]:
+#    return auto_img(format)
+
+
+def resolve_format(value, format_resolution_rule: AutoRuleBook):
+    from omni_converter.auto_data.auto_v2 import AutoData2
+    return AutoData2(value=value, format=value).with_rules(format_resolution_rule).to("format")
+
+
+def ruled(value,
+          rules: AutoRuleBook,
+          format=None,
+          format_resolution_rule: AutoRuleBook = None) -> "RuledData":
+    if format_resolution_rule is None:
+        from omni_converter.auto_data.format_resolution import FORMAT_RESOLUTION_RULES
+        format_resolution_rule = FORMAT_RESOLUTION_RULES
+    if format is None:
+        # try to automatically get format from value given rules
+        format = resolve_format(value, format_resolution_rule)
+    from omni_converter.auto_data.auto_v2 import AutoData2
+    return AutoData2(value=value, format=format).with_rules(rules)
+
+
+class PicklableLogger:
+    def info(self, message):
+        self.logger.info(message)
+
+    def warning(self, message):
+        self.logger.warning(message)
+
+    def error(self, message):
+        self.logger.error(message)
+
+    def debug(self, message):
+        self.logger.debug(message)
+
+    def verbose(self, message):
+        self.logger.verbose(message)
+
+    def __getstate__(self):
+        return None
+
+    def __setstate__(self, state):
+        from loguru import logger
+        self.logger = logger
+
+    def __init__(self):
+        from loguru import logger
+        self.logger = logger
+
+
+logger = PicklableLogger()
+>>>>>>> master