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# ConvBnReLU2d

class torch.ao.nn.intrinsic.qat.ConvBnReLU2d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=None, padding_mode='zeros', eps=1e-05, momentum=0.1, freeze_bn=False, qconfig=None)

  A ConvBnReLU2d module is a module fused from Conv2d, BatchNorm2d and ReLU, attached with FakeQuantize modules for weight, used in quantization aware training.

  We combined the interface of `torch.nn.Conv2d` and `torch.nn.BatchNorm2d` and `torch.nn.ReLU`.

  Similar to torch.nn.Conv2d, with FakeQuantize modules initialized to default.

  Variables:

    weight_fake_quant – fake quant module for weight

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