tensorflow::ops::SparseSlice

#include <sparse_ops.h>

Slice a SparseTensor based on the start and size.

Summary

For example, if the input is 

input_tensor = shape = [2, 7]
[    a   d e  ]
[b c          ]

Graphically the output tensors are: 

sparse_slice([0, 0], [2, 4]) = shape = [2, 4]
[    a  ]
[b c    ]

sparse_slice([0, 4], [2, 3]) = shape = [2, 3]
[ d e  ]
[      ]

Args:

  • scope: A Scope object
  • indices: 2-D tensor represents the indices of the sparse tensor.
  • values: 1-D tensor represents the values of the sparse tensor.
  • shape: 1-D. tensor represents the shape of the sparse tensor.
  • start: 1-D. tensor represents the start of the slice.
  • size: 1-D. tensor represents the size of the slice. output indices: A list of 1-D tensors represents the indices of the output sparse tensors.

Returns:

  • Output output_indices
  • Output output_values: A list of 1-D tensors represents the values of the output sparse tensors.
  • Output output_shape: A list of 1-D tensors represents the shape of the output sparse tensors.

Constructors and Destructors
SparseSlice(const ::tensorflow::Scope & scope, ::tensorflow::Input indices, ::tensorflow::Input values, ::tensorflow::Input shape, ::tensorflow::Input start, ::tensorflow::Input size)

Public attributes
operation
output_indices
output_shape
output_values

Public attributes

operation

Operation operation

output_indices

::tensorflow::Output output_indices

output_shape

::tensorflow::Output output_shape

output_values

::tensorflow::Output output_values

Public functions

SparseSlice

 SparseSlice(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input indices,
  ::tensorflow::Input values,
  ::tensorflow::Input shape,
  ::tensorflow::Input start,
  ::tensorflow::Input size
)