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/r2.4/api_docs/python/tf/raw_ops/SparseSlice