base code for pytorch distributed, add cyclegan

data/transform.py

@@ -0,0 +1,34 @@
+from torchvision import transforms
+from torchvision.datasets.folder import default_loader
+
+from .registry import TRANSFORM
+
+# from https://pytorch.org/docs/stable/_modules/torchvision/transforms/transforms.html
+_VALID_TORCHVISION_TRANSFORMS = ["ToTensor", "ToPILImage", "Normalize", "Resize",
+                                 "Scale", "CenterCrop", "Pad", "Lambda", "RandomApply", "RandomChoice", "RandomOrder",
+                                 "RandomCrop", "RandomHorizontalFlip", "RandomVerticalFlip", "RandomResizedCrop",
+                                 "RandomSizedCrop", "FiveCrop", "TenCrop", "LinearTransformation", "ColorJitter",
+                                 "RandomRotation", "RandomAffine", "Grayscale", "RandomGrayscale", "RandomPerspective",
+                                 "RandomErasing"]
+
+for vtt in _VALID_TORCHVISION_TRANSFORMS:
+    TRANSFORM.register_module(module=getattr(transforms, vtt))
+
+
+@TRANSFORM.register_module()
+class Load:
+    def __init__(self, loader=default_loader):
+        self.loader = loader
+
+    def __call__(self, image_path):
+        return self.loader(image_path)
+
+    def __repr__(self):
+        return self.__class__.__name__ + "()"
+
+
+def transform_pipeline(pipeline_description):
+    if len(pipeline_description) == 0:
+        return lambda x: x
+    transform_list = [TRANSFORM.build_with(pd) for pd in pipeline_description]
+    return transforms.Compose(transform_list)