def add_training_inputs(model, roidb=None):
    """Create network input ops and blobs used for training. To be called
    *after* model_builder.create().
    """
    # Implementation notes:
    #   Typically, one would create the input ops and then the rest of the net.
    #   However, creating the input ops depends on loading the dataset, which
    #   can take a few minutes for COCO.
    #   We prefer to avoid waiting so debugging can fail fast.
    #   Thus, we create the net *without input ops* prior to loading the
    #   dataset, and then add the input ops after loading the dataset.
    #   Since we defer input op creation, we need to do a little bit of surgery
    #   to place the input ops at the start of the network op list.
    assert model.train, 'Training inputs can only be added to a trainable model'
    if roidb is not None:
        # To make debugging easier you can set cfg.DATA_LOADER.NUM_THREADS = 1
        model.roi_data_loader = RoIDataLoader(
            roidb,
            num_loaders=cfg.DATA_LOADER.NUM_THREADS,
            minibatch_queue_size=cfg.DATA_LOADER.MINIBATCH_QUEUE_SIZE,
            blobs_queue_capacity=cfg.DATA_LOADER.BLOBS_QUEUE_CAPACITY
        )
    orig_num_op = len(model.net._net.op)
    blob_names = roi_data_minibatch.get_minibatch_blob_names(is_training=True)
    for gpu_id in range(cfg.NUM_GPUS):
        with c2_utils.NamedCudaScope(gpu_id):
            for blob_name in blob_names:
                workspace.CreateBlob(core.ScopedName(blob_name))
            model.net.DequeueBlobs(
                model.roi_data_loader._blobs_queue_name, blob_names
            )
    # A little op surgery to move input ops to the start of the net
    diff = len(model.net._net.op) - orig_num_op
    new_op = model.net._net.op[-diff:] + model.net._net.op[:-diff]
    del model.net._net.op[:]
    model.net._net.op.extend(new_op)
Create network input ops and blobs used for training. To be called
    *after* model_builder.create().
    
detectron/modeling/model_builder.py