Method _bootstrap_ops

caffe2/python/layers/fc_with_bootstrap.py:212–238

This method contains all the bootstrapping logic used to bootstrap the features. Only used by the train_net. Args: net: the caffe2 net to insert bootstrapping operators copied_cur_layer: the blob representing the current features

(self, net, copied_cur_layer, indices, iteration)

            return indices

    def _bootstrap_ops(self, net, copied_cur_layer, indices, iteration):
        """
            This method contains all the bootstrapping logic used to bootstrap
            the features. Only used by the train_net.

            Args:
                net: the caffe2 net to insert bootstrapping operators

                copied_cur_layer: the blob representing the current features.
                    Note, this layer should have a stop_gradient on it.

            Returns:
                bootstrapped_features: blob of bootstrapped version of cur_layer
                    with same dimensions
        """

        # draw features based upon the bootstrapped indices
        bootstrapped_features = net.Gather(
            [copied_cur_layer, indices],
            net.NextScopedBlob("bootstrapped_features_{}".format(iteration)),
        )

        bootstrapped_features = schema.Scalar(
            (np.float32, self.input_dims), bootstrapped_features
        )

        return bootstrapped_features

    def _insert_fc_ops(self, net, features, params, outputs, version):
        """