parameters: (self)
return_statement: return self._params_dict
docstring: An OrderedDict (bottom to top, i.e., input to output) of network
      parameters indexed by name; each is a list of multiple blobs (e.g.,
      weights and biases)
docstring_summary: An OrderedDict (bottom to top, i.e., input to output) of network
      parameters indexed by name; each is a list of multiple blobs (e.g.,
      weights and biases)
docstring_tokens: An OrderedDict ( bottom to top i . e . input to output ) of network parameters indexed by name ; each is a list of multiple blobs ( e . g . weights and biases )
function: def _Net_params(self):
      """
      An OrderedDict (bottom to top, i.e., input to output) of network
      parameters indexed by name; each is a list of multiple blobs (e.g.,
      weights and biases)
      """
      if not hasattr(self, '_params_dict'):
          self._params_dict = OrderedDict([(name, lr.blobs)
                                          for name, lr in zip(
                                              self._layer_names, self.layers)
                                          if len(lr.blobs) > 0])
      return self._params_dict
function_tokens: def _Net_params ( self ) : if not hasattr ( self , '_params_dict' ) : self . _params_dict = OrderedDict ( [ ( name , lr . blobs ) for name , lr in zip ( self . _layer_names , self . layers ) if len ( lr . blobs ) > 0 ] ) return self . _params_dict