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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/SparseSlice