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enuSpace-tensorflow Manual

RandomShuffleQueue

tensorflow C++ API

tensorflow::ops::RandomShuffleQueue

A queue that randomizes the order of elements.

Summary

Arguments:

  • scope: A Scope object
  • component_types: The type of each component in a value.

Optional attributes (seeAttrs):

  • shapes: The shape of each component in a value. The length of this attr must be either 0 or the same as the length of component_types. If the length of this attr is 0, the shapes of queue elements are not constrained, and only one element may be dequeued at a time.
  • capacity: The upper bound on the number of elements in this queue. Negative numbers mean no limit.
  • min_after_dequeue: Dequeue will block unless there would be this many elements after the dequeue or the queue is closed. This ensures a minimum level of mixing of elements.
  • seed: If either seed or seed2 is set to be non-zero, the random number generator is seeded by the given seed. Otherwise, a random seed is used.
  • seed2: A second seed to avoid seed collision.
  • container: If non-empty, this queue is placed in the given container. Otherwise, a default container is used.
  • shared_name: If non-empty, this queue will be shared under the given name across multiple sessions.

Returns:

  • Output : The handle to the queue.

Constructor

  • RandomShuffleQueue(const ::tensorflow::Scope & scope, const DataTypeSlice & component_types, const RandomShuffleQueue::Attrs & attrs).

Public attributes

  • tensorflow::Output handle.

RandomShuffleQueue block

Source link : https://github.com/EXPNUNI/enuSpace-Tensorflow/blob/master/enuSpaceTensorflow/tf_data_flow_ops.cpp

Argument:

  • Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)

  • component_types: Input DataType List in accordance with each input.

  • RandomShuffleQueue::Attrs attrs : input attrs data. ex) shapes_ = {2,4}; capacity = -1; container = ; shared_name = ;

Return:

  • Output handle: Output object of RandomShuffleQueue class object.

Result:

  • std::vector(Tensor) product_result : Returned object of executed result by calling session.

Using Method