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![]() * add model files etc for MobileNetV2 * rename files for MobileNetV1 * initial implementation of MobileNetV1 * fix conversion script * cleanup * write docs * tweaks * fix conversion script * extract hidden states * fix test cases * make fixup * fixup it all * rename V1 to V2 * fix checkpoints * fixup * implement first block + weight conversion * add remaining layers * add output stride and dilation * fixup * add tests * add deeplabv3+ head * a bit of fixup * finish deeplab conversion * add link to doc * fix issue with JIT trace in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value. * cleanup * fix order of models * fix rebase error * remove main from doc link * add image processor * remove old feature extractor * fix converter + other issues * fixup * fix unit test * add to onnx tests (but these appear broken now) * add post_process_semantic_segmentation * use google org * remove unused imports * move args * replace weird assert |
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.. | ||
benchmark | ||
deepspeed | ||
extended | ||
fixtures | ||
generation | ||
mixed_int8 | ||
models | ||
onnx | ||
optimization | ||
pipelines | ||
repo_utils | ||
sagemaker | ||
tokenization | ||
trainer | ||
utils | ||
__init__.py | ||
test_configuration_common.py | ||
test_feature_extraction_common.py | ||
test_image_transforms.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 |