tf.train.slice_input_producer(
tensor_list,
num_epochs=None,
shuffle=True,
seed=None,
capacity=32,
shared_name=None,
name=None
)
Defined in tensorflow/python/training/input.py.
Produces a slice of each Tensor in tensor_list. (deprecated)
Implemented using a Queue -- a QueueRunner for the Queue
is added to the current Graph's QUEUE_RUNNER collection.
Args:
tensor_list: A list ofTensorobjects. EveryTensorintensor_listmust have the same size in the first dimension.num_epochs: An integer (optional). If specified,slice_input_producerproduces each slicenum_epochstimes before generating anOutOfRangeerror. If not specified,slice_input_producercan 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: ifslice_input_producerproduces nothing fromtensor_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.