class_docstr: Conv1dResNet
class_docstr_tok: ["Conv1dResNet"]
docstr: __init__.
  :param relu_type: str, Activation function used in an audio front-end.
  :param a_upsample_ratio: int, The ratio related to the             temporal resolution of output features of the frontend.             a_upsample_ratio=1 produce features with a fps of 25.
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code: def __init__(self, relu_type="swish", a_upsample_ratio=1):
      """__init__.
          :param relu_type: str, Activation function used in an audio front-end.
          :param a_upsample_ratio: int, The ratio related to the \
              temporal resolution of output features of the frontend. \
              a_upsample_ratio=1 produce features with a fps of 25.
          """
  
      super(Conv1dResNet, self).__init__()
      self.a_upsample_ratio = a_upsample_ratio
      self.trunk = ResNet1D(
          BasicBlock1D,
          [2, 2, 2, 2],
          relu_type=relu_type,
          a_upsample_ratio=a_upsample_ratio,
      )
  
file_path: audio/examples/avsr/models/resnet1d.py
imports: import torch.nn
label_desc: Use image node_id 1 to create a new Conv1dResNet object from inherited base classes: nn with example: obj = Conv1dResNet(relu_type, a_upsample_ratio)