ConvBnReLU3d

class torch.ao.nn.intrinsic.qat.modules.conv_fused.ConvBnReLU3d(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 ConvBnReLU3d module is a module fused from Conv3d, BatchNorm3d and ReLU, attached with FakeQuantize modules for weight, used in quantization aware training.

We combined the interface of torch.nn.Conv3d and torch.nn.BatchNorm3d and torch.nn.ReLU.

Similar to torch.nn.Conv3d, with FakeQuantize modules initialized to default.

Variables:

weight_fake_quant – fake quant module for weight

forward(input)

Performs forward pass through fused Conv3d, BatchNorm3d, and ReLU.

classmethod from_float(mod, use_precomputed_fake_quant=False)

Creates a QAT module from a floating point module.