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Utils shared by different modes of quantization (eager/graph)

This file is in the process of migration to `torch/ao/quantization`, and
is kept here for compatibility while the migration process is ongoing.
If you are adding a new entry/functionality, please, add it to the
`torch/ao/quantization/utils.py`, while adding an import statement
here.
    )activation_dtypeactivation_is_int8_quantized"activation_is_statically_quantizedcalculate_qmin_qmaxcheck_min_max_validget_combined_dictget_qconfig_dtypesget_qparam_dictget_quant_typeget_swapped_custom_module_classgetattr_from_fqnis_per_channelis_per_tensorweight_dtypeweight_is_quantizedweight_is_statically_quantizedN)__doc__Ztorch.ao.quantization.utilsr   r   r   r   r   r   r   r	   r
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