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28 lines
1.4 KiB
Python
28 lines
1.4 KiB
Python
# 🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
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# This file was automatically generated from examples/modular-transformers/modular_new_imgproc_model.py.
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# Do NOT edit this file manually as any edits will be overwritten by the generation of
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# the file from the modular. If any change should be done, please apply the change to the
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# modular_new_imgproc_model.py file directly. One of our CI enforces this.
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# 🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
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import torch
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from ...image_processing_backends import TorchvisionBackend
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from ...image_utils import OPENAI_CLIP_MEAN, OPENAI_CLIP_STD, PILImageResampling
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from ...utils import auto_docstring
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@auto_docstring
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class ImgprocModelImageProcessor(TorchvisionBackend):
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resample = PILImageResampling.BICUBIC
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image_mean = OPENAI_CLIP_MEAN
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image_std = OPENAI_CLIP_STD
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size = {"height": 384, "width": 384}
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default_to_square = True
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do_resize = True
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do_rescale = True
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do_normalize = True
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do_convert_rgb = True
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def new_image_processing_method(self, pixel_values: torch.FloatTensor):
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return pixel_values / 2
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