parameters: (tensorParameter)
return_statement: return orderedWeights
docstring: Returns an numpy array from a trainable parameter
         Note that ELL's ordering is row, column, channel.
         CNTK has them in filter, channel, row, column order.
docstring_summary: Returns an numpy array from a trainable parameter
         Note that ELL's ordering is row, column, channel.
         CNTK has them in filter, channel, row, column order.
docstring_tokens: Returns an numpy array from a trainable parameter Note that ELL s ordering is row column channel . CNTK has them in filter channel row column order .
function: def get_vector_from_cntk_trainable_parameter(tensorParameter):
      """Returns an numpy array from a trainable parameter
         Note that ELL's ordering is row, column, channel.
         CNTK has them in filter, channel, row, column order.
      """
      tensorValue = tensorParameter.value
  
      orderedWeights = np.zeros(tensorValue.size, dtype=np.float)
      i = 0
      for columnValue in tensorValue:
          orderedWeights[i] = columnValue
          i += 1
      return orderedWeights
function_tokens: def get_vector_from_cntk_trainable_parameter ( tensorParameter ) : tensorValue = tensorParameter . value orderedWeights = np . zeros ( tensorValue . size , dtype = np . float ) i = 0 for columnValue in tensorValue : orderedWeights [ i ] = columnValue i += 1 return orderedWeights