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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
)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version.
Instructions for updating:
Queue-based input pipelines have been replaced by tf.data
. Use tf.data.Dataset.interleave(...).filter(...).batch(batch_size)
(or padded_batch(...)
if dynamic_pad=True
).
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
.