tf.compat.v1.train.maybe_batch

Conditionally creates batches of tensors based on keep_input. (deprecated)

tf.compat.v1.train.maybe_batch(
    tensors,
    keep_input,
    batch_size,
    num_threads=1,
    capacity=32,
    enqueue_many=False,
    shapes=None,
    dynamic_pad=False,
    allow_smaller_final_batch=False,
    shared_name=None,
    name=None
)

See docstring in batch for more details.

Args
`tensors`	The list or dictionary 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`	The new batch size pulled from the queue.
`num_threads`	The number of threads enqueuing `tensors`. The batching will be nondeterministic if `num_threads > 1`.
`capacity`	An integer. The maximum number of elements in the queue.
`enqueue_many`	Whether each tensor in `tensors` is a single example.
`shapes`	(Optional) The shapes for each example. Defaults to the inferred shapes for `tensors`.
`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.

Returns
A list or dictionary of tensors with the same types as `tensors`.

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

tf.compat.v1.train.maybe_batch

Args

Returns

Raises