def _get_weights(self, var_name, shape, init=tl.initializers.random_normal()): """ Get trainable variables. """ weight = get_variable_with_initializer(scope_name=self.name, var_name=var_name, shape=shape, init=init) if self._weights is None: self._weights = list() self._weights.append(weight) # Add into the weight collection return weight
def _get_weights(self, var_name, shape, init=tl.initializers.random_normal(), trainable=True): """ Get trainable variables. """ weight = get_variable_with_initializer(scope_name=self.name, var_name=var_name, shape=shape, init=init) if trainable is True: if self._trainable_weights is None: self._trainable_weights = list() self._trainable_weights.append(weight) else: if self._nontrainable_weights is None: self._nontrainable_weights = list() self._nontrainable_weights.append(weight) return weight
def _get_weights(self, var_name, shape, init=tl.initializers.random_normal()): weight = get_variable_with_initializer(scope_name=self.name, var_name=var_name, shape=shape, init=init) if self._weights is None: self._weights = list() self._weights.append(weight) # Add into the weight collection # self.__setattr__(var_name, weight) # FIXME: prefer to remove this line, the weights should be manually defined as members of the Layer return weight