code: def __init__(
      self,
      in_dim,
      out_dim,
      n_layers=3,
      kernel_size=3,
      stride=2,
      layerdrop=0.0,
      layernorm=False,
      proj=False,
  ):
      super().__init__()
      self.proj, self.proj_ln = None, None
      self.post_proj, self.post_proj_ln = None, None
      if proj:
          self.proj = nn.Sequential(
              nn.Linear(in_dim, in_dim * 4),
              nn.ReLU(),
              nn.Linear(in_dim * 4, in_dim),
          )
          self.proj_ln = LayerNorm(in_dim)
          self.post_proj = nn.Sequential(
              nn.Linear(out_dim, out_dim * 4),
              nn.ReLU(),
              nn.Linear(out_dim * 4, out_dim),
          )
          self.post_proj_ln = LayerNorm(out_dim)
  
      self.layers = nn.ModuleList(
          nn.Conv1d(
              in_dim if i == 0 else out_dim,
              out_dim * 2,
              kernel_size,
              stride=stride,
              padding=kernel_size // 2,
          )
          for i in range(n_layers)
      )
      self.stride = stride
      self.layerdrop = layerdrop
      self.layernorm = LayerNorm(in_dim) if layernorm else None
  
imports: import copy
  import logging
  from typing import Dict, List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.data.data_utils import lengths_to_padding_mask
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqLanguageModel, register_model, register_model_architecture
  from fairseq.models.speech_to_speech.modules.ctc_decoder import CTCDecoder
  from fairseq.models.speech_to_text.hub_interface import S2THubInterface
  from fairseq.models.transformer import Embedding, TransformerDecoder, TransformerModelBase
  from fairseq.models.wav2vec import Wav2VecEncoder
  from fairseq.modules.layer_norm import LayerNorm
label_desc: Use image node_id 1 to create a new Conv1dAdaptor object from inherited base classes: nn with example: obj = Conv1dAdaptor(in_dim, out_dim, n_layers, kernel_size, stride, layerdrop, layernorm, proj)