tf.compat.v2.io.serialize_many_sparse
Serialize N
-minibatch SparseTensor
into an [N, 3]
Tensor
.
tf.compat.v2.io.serialize_many_sparse( sp_input, out_type=tf.dtypes.string, name=None )
The SparseTensor
must have rank R
greater than 1, and the first dimension is treated as the minibatch dimension. Elements of the SparseTensor
must be sorted in increasing order of this first dimension. The serialized SparseTensor
objects going into each row of the output Tensor
will have rank R-1
.
The minibatch size N
is extracted from sparse_shape[0]
.
Args | |
---|---|
sp_input | The input rank R SparseTensor . |
out_type | The dtype to use for serialization. |
name | A name prefix for the returned tensors (optional). |
Returns | |
---|---|
A matrix (2-D Tensor ) with N rows and 3 columns. Each column represents serialized SparseTensor 's indices, values, and shape (respectively). |
Raises | |
---|---|
TypeError | If sp_input is not a SparseTensor . |
© 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/r1.15/api_docs/python/tf/compat/v2/io/serialize_many_sparse