class_docstr: Chainer implementation of ctc layer.
  
  Args:
      odim (int): The output dimension.
      eprojs (int | None): Dimension of input vectors from encoder.
      dropout_rate (float): Dropout rate.
class_docstr_tok: ["Chainer","implementation","of","ctc","layer",".","Args",":","odim","(","int",")",":","The","output","dimension",".","eprojs","(","int","|","None",")",":","Dimension","of","input","vectors","from","encoder",".","dropout_rate","(","float",")",":","Dropout","rate","."]
code: def __init__(self, odim, eprojs, dropout_rate):
      super(CTC, self).__init__()
      self.dropout_rate = dropout_rate
      self.loss = None
  
      with self.init_scope():
          self.ctc_lo = L.Linear(eprojs, odim)
  
file_path: espnet/espnet/nets/chainer_backend/ctc.py
imports: import logging
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
label_desc: Use image node_id 1 to create a new CTC object from inherited base classes: chainer with example: obj = CTC(odim, eprojs, dropout_rate)