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/TensorFlow 1.15

tf.train.maybe_batch

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

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.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/train/maybe_batch