Adds an example for resnet50 in half precision.#307
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IanNod
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Jan 5, 2024
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Please add a test for this
| # extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-18") | ||
| model = resnet50(weights="DEFAULT") | ||
| float_model = model.eval().float() | ||
| model = model.eval().half() |
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Is there a reason we are only doing f16 instead of having an option/flag for whatever precision you want?
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Also renames the examples/resnet-18 directory to examples/resnet to avoid creating another directory. This might not be ideal, as the resnet50 example uses the torchvision model and the resnet18 script uses the
microsoft/resnet-18transformers model.