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# ConvReLU2d

class torch.ao.nn.intrinsic.qat.ConvReLU2d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros', qconfig=None)

  A ConvReLU2d module is a fused module of Conv2d and ReLU, attached with FakeQuantize modules for weight for quantization aware training.

  We combined the interface of `Conv2d` and `BatchNorm2d`.

  Variables:

    weight_fake_quant – fake quant module for weight

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