TensorArray
tensorflow C++ API
An array of Tensors of given size.
Summary
Write data via Write and read via Read or Pack.
Arguments:
- scope: A Scope object
- size: The size of the array.
- dtype: The type of the elements on the tensor_array.
Optional attributes (seeAttrs):
- element_shape: The expected shape of an element, if known. Used to validate the shapes of TensorArray elements. If this shape is not fully specified, gathering zero-size TensorArrays is an error.
- dynamic_size: A boolean that determines whether writes to the TensorArray are allowed to grow the size. By default, this is not allowed.
- clear_after_read: If true (default), Tensors in the TensorArray are cleared after being read. This disables multiple read semantics but allows early release of memory.
- tensor_array_name: Overrides the name used for the temporary tensor_array resource. Default value is the name of the `TensorArray' op (which is guaranteed unique).
Returns:
- Output handle: The handle to the TensorArray.
- Output flow: A scalar used to control gradient flow.
Constructor
- TensorArray(const ::tensorflow::Scope & scope, ::tensorflow::Input size, DataType dtype, const TensorArray::Attrs & attrs).
Public attributes
- tensorflow::Output flow.
- tensorflow::Output handle.
TensorArray 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.)
- size : connect Input node or input array size.
- DataType dtype : input DataType. ex) DT_DOUBLE;
- TensorArray::Attrs attrs : input attrs data. ex) element_shape_ = ; dynamic_size_ = false; clear_after_read_ = true; tensor_array_name_ =;
Return:
- Output flow: Output object of TensorArray class object.
- Output handle: Output handle of TensorArray class object.
Result:
- std::vector(Tensor) product_result : Returned object of executed result by calling session.
Using Method
