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alexsu52
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Feb 7, 2025
| weight_port_ids = [3] | ||
| bias_port_id = 4 | ||
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| if is_experimental_torch_tracing_enabled(): |
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I'm confuse that the same function from the PyTorch has different signature depends on the trace method. Maybe this is different function and you should reuse the approach from #3237.
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Patched function traced only torch.nn.functional.batch_norm (that inside call torch.batch_norm, that have differ signature), that works only because in models most other used batchnorm as module nn.BatchNorm2d, that call used torch.nn.functional.batch_norm.
In experimental traced only torch.batch_norm.
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Yes, I can handle this case in my PR
nncf/experimental/torch2/function_hook/nncf_graph/nncf_graph_builder.py
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tests/torch2/function_hook/quantization/test_fast_bias_correction.py
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daniil-lyakhov
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Feb 10, 2025
alexsu52
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Feb 11, 2025
| weight_port_ids = [3] | ||
| bias_port_id = 4 | ||
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| if is_experimental_torch_tracing_enabled(): |
alexsu52
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Feb 13, 2025
shumaari
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Feb 17, 2025
### Changes - Impanated FBC for experimental tracing - Save graph to GraphModelWrapper, to using graph like for NNCFNetwork - Add ConstantLayerAttributes to constant node - Check is_experimental_torch_tracing_enabled inside patch_torch_operators, to support [optimum-intel ](https://github.com/huggingface/optimum-intel/blob/f601b8b1fda4477ed9f9e4293cf3c9d5cec4ad1b/optimum/intel/openvino/__init__.py#L49) ### Related tickets 152996 --------- Co-authored-by: Alexander Dokuchaev <adokucha@ad.local>
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152996