tf.compat.v1.train.maybe_batch_join

Runs a list of tensors to conditionally fill a queue to create batches. (deprecated)

tf.compat.v1.train.maybe_batch_join(
    tensors_list,
    keep_input,
    batch_size,
    capacity=32,
    enqueue_many=False,
    shapes=None,
    dynamic_pad=False,
    allow_smaller_final_batch=False,
    shared_name=None,
    name=None
)

See docstring in batch_join for more details.

tensors_list A list of tuples or dictionaries of tensors to enqueue.
keep_input A bool Tensor. This tensor controls whether the input is added to the queue or not. If it is a scalar and evaluates True, then tensors are all added to the queue. If it is a vector and enqueue_many is True, then each example is added to the queue only if the corresponding value in keep_input is True. This tensor essentially acts as a filtering mechanism.
batch_size An integer. The new batch size pulled from the queue.
capacity An integer. The maximum number of elements in the queue.
enqueue_many Whether each tensor in tensor_list_list is a single example.
shapes (Optional) The shapes for each example. Defaults to the inferred shapes for tensor_list_list[i].
dynamic_pad Boolean. Allow variable dimensions in input shapes. The given dimensions are padded upon dequeue so that tensors within a batch have the same shapes.
allow_smaller_final_batch (Optional) Boolean. If True, allow the final batch to be smaller if there are insufficient items left in the queue.
shared_name (Optional) If set, this queue will be shared under the given name across multiple sessions.
name (Optional) A name for the operations.

A list or dictionary of tensors with the same number and types as tensors_list[i].

ValueError If the shapes are not specified, and cannot be inferred from the elements of tensor_list_list.