class_docstr: Residual block wrapper for black box layer.
  
  The SequenceResidualBlock class implements a generic
  (batch, length, d_input) -> (batch, length, d_input) transformation
  
  Args:
      d_input: Input feature dimension
      i_layer: Layer index, only needs to be passed into certain residuals like Decay
      dropout: Dropout for black box module
      tie_dropout: Tie dropout mask across sequence like nn.Dropout1d/nn.Dropout2d
      transposed: Transpose inputs so each layer receives (batch, dim, length)
      layer: Config for black box module
      residual: Config for residual function
      norm: Config for normalization layer
      pool: Config for pooling layer per stage
      drop_path: Drop ratio for stochastic depth
class_docstr_tok: ["Residual","block","wrapper","for","black","box","layer",".","The","SequenceResidualBlock","class","implements","a","generic","(","batch",",","length",",","d_input",")","-",">","(","batch",",","length",",","d_input",")","transformation","Args",":","d_input",":","Input","feature","dimension","i_layer",":","Layer","index",",","only","needs","to","be","passed","into","certain","residuals","like","Decay","dropout",":","Dropout","for","black","box","module","tie_dropout",":","Tie","dropout","mask","across","sequence","like","nn.Dropout1d\/nn.Dropout2d","transposed",":","Transpose","inputs","so","each","layer","receives","(","batch",",","dim",",","length",")","layer",":","Config","for","black","box","module","residual",":","Config","for","residual","function","norm",":","Config","for","normalization","layer","pool",":","Config","for","pooling","layer","per","stage","drop_path",":","Drop","ratio","for","stochastic","depth"]
code: def d_state(self):
      return self.layer.d_state
  
file_path: espnet/espnet2/asr/state_spaces/block.py
imports: from functools import partial
  from torch import nn
  import espnet2.asr.state_spaces.utils
  from espnet2.asr.state_spaces import registry
  from espnet2.asr.state_spaces.base import SequenceModule
  from espnet2.asr.state_spaces.components import DropoutNd, Normalization, StochasticDepth
  from espnet2.asr.state_spaces.pool import registry
  from espnet2.asr.state_spaces.residual import registry
label_desc: Use image node_id 3 for calling the SequenceResidualBlock obj's underlying member method code with example usage: obj.d_state() and returns: self