tf.compat.v1.train.LooperThread

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.

Args
`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.

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

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

TensorFlow

tf.compat / v1 / v1.train.LooperThread

Args

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Raises

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.compat / v1 / v1.train.LooperThread

Args

Returns

Raises