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* Update methods to optionally rescale This is necessary to allow for casting our images / videos to numpy arrays within the feature extractors' call. We want to do this to make sure the behaviour is as expected when flags like are False. If some transformations aren't applied, then the output type can't be unexpected e.g. a list of PIL images instead of numpy arrays. * Cast images to numpy arrays in call to enable consistent behaviour with different configs * Remove accidental clip changes * Update tests to reflect the scaling logic We write a generic function to handle rescaling of our arrays. In order for the API to be intuitive, we take some factor c and rescale the image values by that. This means, the rescaling done in normalize and to_numpy_array are now done with array * (1/255) instead of array / 255. This leads to small differences in the resulting image. When testing, this was in the order of 1e-8, and so deemed OK |
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| benchmark | ||
| deepspeed | ||
| extended | ||
| fixtures | ||
| generation | ||
| mixed_int8 | ||
| models | ||
| onnx | ||
| optimization | ||
| pipelines | ||
| sagemaker | ||
| tokenization | ||
| trainer | ||
| utils | ||
| __init__.py | ||
| test_configuration_common.py | ||
| test_feature_extraction_common.py | ||
| test_modeling_common.py | ||
| test_modeling_flax_common.py | ||
| test_modeling_tf_common.py | ||
| test_sequence_feature_extraction_common.py | ||
| test_tokenization_common.py | ||