tf.raw_ops.SparseSlice

Slice a SparseTensor based on the start and size.

tf.raw_ops.SparseSlice(
    indices, values, shape, start, size, name=None
)

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:

  • indices: A Tensor of type int64. 2-D tensor represents the indices of the sparse tensor.
  • values: A Tensor. 1-D tensor represents the values of the sparse tensor.
  • shape: A Tensor of type int64. 1-D. tensor represents the shape of the sparse tensor.
  • start: A Tensor of type int64. 1-D. tensor represents the start of the slice.
  • size: A Tensor of type int64. 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.
  • name: A name for the operation (optional).

Returns:

A tuple of Tensor objects (output_indices, output_values, output_shape).

  • output_indices: A Tensor of type int64.
  • output_values: A Tensor. Has the same type as values.
  • output_shape: A Tensor of type int64.