ConvBn3d

class torch.nn.intrinsic.qat.ConvBn3d(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 ConvBn3d module is a module fused from Conv3d and BatchNorm3d, attached with FakeQuantize modules for weight, used in quantization aware training.

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

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

Variables:

• freeze_bn –

• weight_fake_quant – fake quant module for weight