VhddlmZmZmZddlZerddlmZdgZGddejjjjZ y))Optional TYPE_CHECKINGUnionN)QConfigLinearc|eZdZdZ d dededededdeeeee jfd eed dffd Z xZ S) rah A linear module attached with FakeQuantize modules for weight, used for dynamic quantization aware training. We adopt the same interface as `torch.nn.Linear`, please see https://pytorch.org/docs/stable/nn.html#torch.nn.Linear for documentation. Similar to `torch.nn.Linear`, with FakeQuantize modules initialized to default. N in_features out_featuresbiasqconfigrdevicedtypereturnct|||||||tjjj j |s tdy)NzqDynamic QAT requires a memoryless observer.This means a MovingAverage observer with averaging constant equal to 1)super__init__torchao quantizationr _activation_is_memoryless ValueError)selfr r r r r r __class__s V/home/dcms/DCMS/lib/python3.12/site-packages/torch/ao/nn/qat/dynamic/modules/linear.pyrzLinear.__init__sS lD'65Qxx$$,,FFwO[ P)TNNN) __name__ __module__ __qualname____doc__intboolrrstrrr r __classcell__)rs@rrr s  '+:>#  )$  sC567 } r) typingrrrrtorch.ao.quantization.qconfigr__all__rnnqatrrrr*s=11 5 *UXX[[__ # #r