Method build_non_lr_iter

caffe2/python/optimizer.py:186–214

(
        self,
        net,
        param_init_net,
        iter_val=0,
    )

        return lr, iteration

    def build_non_lr_iter(
        self,
        net,
        param_init_net,
        iter_val=0,
    ):
        assert (
            self._use_dedicated_lr_iteration_counter
        ), "This method should be only called when dedicated learning rate iteration counter is used."

        iteration = utils.BuildUniqueMutexIter(param_init_net, net, iter_val=iter_val)
        logger.info(f"Created iteration counter for non learning rate purposes: {iteration}")

        # We need to create a dummy learning rate operator to enforce that
        # iteration counter blob being placed in the trainer nodes. Otherwise,
        # the Automatic Device Placement (ADP) algorithm for Hierachical
        # Training (HT) will encounter issues to distribute blobs across group
        # parameter servers. Note that this learning rate operator will not be
        # used for any other purpose.
        learning_rate_blob = self.make_unique_blob_name("iter_placement_hint")
        if not net.BlobIsDefined(learning_rate_blob):
            net.LearningRate(
                [iteration],
                learning_rate_blob,
                base_lr=1.0,
                policy="fixed",
            )

        return iteration

    def add_lr_multiplier(self, lr_multiplier):
        """