ConvBn1d
class torch.ao.nn.intrinsic.qat.ConvBn1d(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 ConvBn1d module is a module fused from Conv1d and BatchNorm1d,
   attached with FakeQuantize modules for weight, used in quantization
   aware training.
We combined the interface of "torch.nn.Conv1d" and
   "torch.nn.BatchNorm1d".
Similar to "torch.nn.Conv1d", with FakeQuantize modules initialized
   to default.
Variables:
      * freeze_bn --
  * **weight_fake_quant** -- fake quant module for weight
