tf.train.slice_input_producer

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.

See the guides: Inputs and Readers > Input pipeline, Reading data > Preloaded data

Produces a slice of each Tensor in tensor_list.

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.