Improve parsing of PyTorch functional layers arguments #923
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….layer_norm and substract
….layer_norm and substract
haihabi
reviewed
Jan 14, 2024
tests/pytorch_tests/model_tests/feature_models/layer_norm_net_test.py
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….layer_norm and substract
….layer_norm and substract
….layer_norm and substract
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| # If function inputs and arguments requires specific order, sort it before the call | ||
| elif isinstance(n, FunctionalNode) and n.op_call_args_order and not (len(n.op_call_args_order) > len(input_tensors + op_call_args)): | ||
| args = [(input_tensors + op_call_args)[ind] for ind in n.op_call_args_order] |
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maybe add and example of an operation for each one in the comments so it will be more clear?
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| # Copyright 2024 Sony Semiconductor Israel, Inc. All rights reserved. | |||
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should this be a feature model test or a layer test? If layer there is a library for layer tests maybe add it there
..._compression_toolkit/core/pytorch/graph_substitutions/substitutions/functional_layer_norm.py
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..._compression_toolkit/core/pytorch/graph_substitutions/substitutions/functional_layer_norm.py
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lior-dikstein
approved these changes
Jan 18, 2024
….layer_norm and substract
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Pull Request Description:
Support PyTorch nn.functional.layer_norm and add a relevant test.
Checklist before requesting a review: