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enuSpace-tensorflow Manual

TensorArrayConcat

tensorflow C++ API

tensorflow::ops::TensorArrayConcat

Concat the elements from the TensorArray into value.

Summary

TakesTelements of shapes

``` (n0 x d0 x d1 x …), (n1 x d0 x d1 x …), …, (n(T-1) x d0 x d1 x …) ```

and concatenates them into a Tensor of shape:

(n0 + n1 + ... + n(T-1) x d0 x d1 x ...)

All elements must have the same shape (excepting the first dimension).

Arguments:

  • scope: A Scope object
  • handle: The handle to a TensorArray.
  • flow_in: A float scalar that enforces proper chaining of operations.
  • dtype: The type of the elem that is returned.

Optional attributes (seeAttrs):

  • element_shape_except0: The expected shape of an element, if known, excluding the first dimension. Used to validate the shapes of TensorArray elements. If this shape is not fully specified, concatenating zero-size TensorArrays is an error.

Returns:

  • Output value: All of the elements in the TensorArray , concatenated along the first axis.
  • Output lengths: A vector of the row sizes of the original T elements in the value output. In the example above, this would be the values:(n1, n2, ..., n(T-1)).

Constructor

  • TensorArrayConcat(const ::tensorflow::Scope & scope, ::tensorflow::Input handle, ::tensorflow::Input flow_in, DataType dtype, const TensorArrayConcat::Attrs & attrs).

Public attributes

  • tensorflow::Output lengths.
  • tensorflow::Output value.

TensorArrayConcat 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.)
  • handle : connect Input node.
  • flow_in : connect Input node.
  • DataType dtype : input datatype. ex) DT_DOUBLE
  • TensorArrayConcat::Attrs attrs : input attrs array. ex) element_shape_except0_ ={2}

Return:

  • Output value : Output object of TensorArrayConcat class object.
  • Output lengths : Output object of TensorArrayConcat class object.

Result:

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

Using Method