original_docstring: 
          given two tensors, pad with zeros so that all dimensions are equal except the axis to concatentate on, and the concatenate
          pad_left is a list of dimensions to pad the left side on. Other dimensions will recieve right sided padding
          
docstring: given two tensors, pad with zeros so that all dimensions are equal except the axis to concatentate on, and the concatenate
  pad_left is a list of dimensions to pad the left side on. Other dimensions will recieve right sided padding
docstring_tokens: given two tensors pad with zeros so that all dimensions are equal except the axis to concatentate on and the concatenate pad_left is a list of dimensions to pad the left side on . Other dimensions will recieve right sided padding
code: def _pad_and_concatenate(a, b, axis, pad_left=[]):
          '''
          given two tensors, pad with zeros so that all dimensions are equal except the axis to concatentate on, and the concatenate
          pad_left is a list of dimensions to pad the left side on. Other dimensions will recieve right sided padding
          '''
          if b is None:
              return a
          # for each axis that is not to be concatenated on, pad the smaller of the two tensors with zeros so that both have equal sizes
          for i in range(len(a.shape)):
              if i == axis:
                  continue
              if i in pad_left:
                  a, b = Network._pad_to_match_dimensions(a, b, i, pad_left=True)
              else:
                  a, b = Network._pad_to_match_dimensions(a, b, i)
  
          # concatenate and return the padded matrices
          return np.concatenate((a, b), axis=axis)
code_tokens: def _pad_and_concatenate ( a , b , axis , pad_left = [ ] ) : if b is None : return a for i in range ( len ( a . shape ) ) : if i == axis : continue if i in pad_left : a , b = Network . _pad_to_match_dimensions ( a , b , i , pad_left = True ) else : a , b = Network . _pad_to_match_dimensions ( a , b , i ) return np . concatenate ( ( a , b ) , axis = axis )
short_docstring: given two tensors, pad with zeros so that all dimensions are equal except the axis to concatentate on, and the concatenate
  pad_left is a list of dimensions to pad the left side on.
short_docstring_tokens: given two tensors pad with zeros so that all dimensions are equal except the axis to concatentate on and the concatenate pad_left is a list of dimensions to pad the left side on .
comment: '''
          given two tensors, pad with zeros so that all dimensions are equal except the axis to concatentate on, and the concatenate
          pad_left is a list of dimensions to pad the left side on. Other dimensions will recieve right sided padding
          '''$SEP$# for each axis that is not to be concatenated on, pad the smaller of the two tensors with zeros so that both have equal sizes$SEP$# concatenate and return the padded matrices