class_docstr: Conv1dResNet
class_docstr_tok: ["Conv1dResNet"]
docstr: forward.
  :param xs_pad: torch.Tensor, batch of padded input sequences (B, Tmax, idim)
docstr_tok: ["forward",".",":","param","xs_pad",":","torch.Tensor",",","batch","of","padded","input","sequences","(","B",",","Tmax",",","idim",")"]
code: def forward(self, xs_pad):
      """forward.
      :param xs_pad: torch.Tensor, batch of padded input sequences (B, Tmax, idim)
      """
      B, T, C = xs_pad.size()
      xs_pad = xs_pad[:, : T // 640 * 640, :]
      xs_pad = xs_pad.transpose(1, 2)
      xs_pad = self.trunk(xs_pad)
      # -- from B x C x T to B x T x C
      xs_pad = xs_pad.transpose(1, 2)
      return xs_pad
  
file_path: audio/examples/avsr/models/resnet1d.py
imports: import torch.nn
label_desc: Use image node_id 2 for calling the Conv1dResNet obj's underlying member method code with example usage: obj.forward(xs_pad) and returns: xs_pad