tf.compat.v1.train.shuffle_batch

Produces a slice of each Tensor in tensor_list. (deprecated)

tf.compat.v1.train.slice_input_producer(
    tensor_list, num_epochs=None, shuffle=True, seed=None, capacity=32,
    shared_name=None, name=None
)

Implemented using a Queue -- a QueueRunner for the Queue is added to the current Graph's QUEUE_RUNNER collection.

Args
`tensor_list`	A list of `Tensor` objects. Every `Tensor` in `tensor_list` must have the same size in the first dimension.
`num_epochs`	An integer (optional). If specified, `slice_input_producer` produces each slice `num_epochs` times before generating an `OutOfRange` error. If not specified, `slice_input_producer` can cycle through the slices an unlimited number of times.
`shuffle`	Boolean. If true, the integers are randomly shuffled within each epoch.
`seed`	An integer (optional). Seed used if shuffle == True.
`capacity`	An integer. Sets the queue capacity.
`shared_name`	(optional). If set, this queue will be shared under the given name across multiple sessions.
`name`	A name for the operations (optional).

Returns
A list of tensors, one for each element of `tensor_list`. If the tensor in `tensor_list` has shape `[N, a, b, .., z]`, then the corresponding output tensor will have shape `[a, b, ..., z]`.

Raises
`ValueError`	if `slice_input_producer` produces nothing from `tensor_list`.

Eager Compatibility

Input pipelines based on Queues are not supported when eager execution is enabled. Please use the tf.data API to ingest data under eager execution.

TensorFlow

tf.compat / v1 / v1.train.shuffle_batch_join

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Eager Compatibility

TensorFlow

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tf.compat / v1 / v1.train.shuffle_batch_join

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Eager Compatibility