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[Quality] Make style (#3341)
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3
setup.py
3
setup.py
@@ -111,6 +111,7 @@ _deps = [
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"torch>=1.4",
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"torchvision",
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"transformers>=4.25.1",
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"urllib3<=2.0.0",
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]
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# this is a lookup table with items like:
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@@ -181,7 +182,7 @@ extras = {}
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extras = {}
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extras["quality"] = deps_list("black", "isort", "ruff", "hf-doc-builder")
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extras["quality"] = deps_list("urllib3", "black", "isort", "ruff", "hf-doc-builder")
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extras["docs"] = deps_list("hf-doc-builder")
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extras["training"] = deps_list("accelerate", "datasets", "protobuf", "tensorboard", "Jinja2")
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extras["test"] = deps_list(
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@@ -35,4 +35,5 @@ deps = {
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"torch": "torch>=1.4",
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"torchvision": "torchvision",
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"transformers": "transformers>=4.25.1",
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"urllib3": "urllib3<=2.0.0",
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}
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@@ -762,7 +762,7 @@ class IFImg2ImgSuperResolutionPipeline(DiffusionPipeline):
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image = [np.array(i).astype(np.float32) / 255.0 for i in image]
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image = np.stack(image, axis=0) # to np
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torch.from_numpy(image.transpose(0, 3, 1, 2))
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image = torch.from_numpy(image.transpose(0, 3, 1, 2))
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elif isinstance(image[0], np.ndarray):
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image = np.stack(image, axis=0) # to np
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if image.ndim == 5:
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@@ -798,7 +798,7 @@ class IFInpaintingSuperResolutionPipeline(DiffusionPipeline):
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image = [np.array(i).astype(np.float32) / 255.0 for i in image]
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image = np.stack(image, axis=0) # to np
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torch.from_numpy(image.transpose(0, 3, 1, 2))
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image = torch.from_numpy(image.transpose(0, 3, 1, 2))
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elif isinstance(image[0], np.ndarray):
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image = np.stack(image, axis=0) # to np
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if image.ndim == 5:
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