Method add_operators

caffe2/python/layers/layers.py:424–453

Adds layer trainig or initialization operators to the passed in net. init_net can be None and can be called independently from add_init_params

(self, net, init_net=None, context=InstantiationContext.TRAINING)

            return self.model.net.NextScopedBlob(name)

    def add_operators(self, net, init_net=None, context=InstantiationContext.TRAINING):
        """
        Adds layer trainig or initialization operators to the passed in net.
        init_net can be None and can be called independently from add_init_params
        """
        # Namescope below should warranty that all intermediate blobs will be
        # assiciated with the layer that produces them
        with scope.NameScope(self.name):
            if context not in {
                InstantiationContext.PREDICTION,
                InstantiationContext.EVAL,
                InstantiationContext.ACCUMULATE_PRED,
            }:
                assert init_net, "Only prediction and eval context don't need init_net"
            if init_net:
                self.add_init_params(init_net)
            if context == InstantiationContext.TRAINING:
                self.add_train_ops(net)
            elif context == InstantiationContext.EVAL:
                self.add_eval_ops(net)
            elif context == InstantiationContext.ACCUMULATE_PRED:
                self.add_ops_to_accumulate_pred(net)
            else:
                self.add_ops(net)

            if (
                context in {InstantiationContext.TRAINING, InstantiationContext.EVAL}
                and self._export_params_for_metrics
            ):
                self.add_param_copy_operators(net)

    def add_ops(self, net):
        # Predict layer implementation.