docstr: Perform average pool along column of a 2-D matrix based on col_seq.
  
  Args:
    input_matrix: A 2-D matrix.
    col_seq: Cumulative pooling sequence along column.
    overlapping: Whether or not use overlapping when pooling.
  
  Returns:
    A 2-D matrix, with
      * num_rows = input_matrix.num_rows
      * num_cols = len(col_seq)-1.
code: def _AvgPoolAlongCols(self, input_matrix, col_seq, overlapping):
      """Perform average pool along column of a 2-D matrix based on col_seq.
  
      Args:
        input_matrix: A 2-D matrix.
        col_seq: Cumulative pooling sequence along column.
        overlapping: Whether or not use overlapping when pooling.
  
      Returns:
        A 2-D matrix, with
          * num_rows = input_matrix.num_rows
          * num_cols = len(col_seq)-1.
      """
      input_matrix = input_matrix.transpose()
      output_matrix = self._AvgPoolAlongRows(
          input_matrix, col_seq, overlapping
      )
      return output_matrix.transpose()
  
imports: import math
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the FractionalAvgTest obj's underlying member method code with example usage: obj._AvgPoolAlongCols(input_matrix, col_seq, overlapping) and returns: output_matrix