tf.raw_ops.SerializeManySparse
Stay organized with collections
Save and categorize content based on your preferences.
Serialize an N-minibatch SparseTensor into an [N, 3] Tensor object.
tf.raw_ops.SerializeManySparse(
sparse_indices,
sparse_values,
sparse_shape,
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 serialized_sparse will have
rank R-1.
The minibatch size N is extracted from sparse_shape[0].
Args |
|---|
sparse_indices
|
A Tensor of type int64.
2-D. The indices of the minibatch SparseTensor.
|
sparse_values
|
A Tensor.
1-D. The values of the minibatch SparseTensor.
|
sparse_shape
|
A Tensor of type int64.
1-D. The shape of the minibatch SparseTensor.
|
out_type
|
An optional tf.DType from: tf.string, tf.variant. Defaults to tf.string.
The dtype to use for serialization; the supported types are string
(default) and variant.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of type out_type.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.SerializeManySparse\n\n\u003cbr /\u003e\n\nSerialize an `N`-minibatch `SparseTensor` into an `[N, 3]` `Tensor` object.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.SerializeManySparse`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SerializeManySparse)\n\n\u003cbr /\u003e\n\n tf.raw_ops.SerializeManySparse(\n sparse_indices,\n sparse_values,\n sparse_shape,\n out_type=../../tf/dtypes#string,\n name=None\n )\n\nThe `SparseTensor` must have rank `R` greater than 1, and the first dimension\nis treated as the minibatch dimension. Elements of the `SparseTensor`\nmust be sorted in increasing order of this first dimension. The serialized\n`SparseTensor` objects going into each row of `serialized_sparse` will have\nrank `R-1`.\n\nThe minibatch size `N` is extracted from `sparse_shape[0]`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `sparse_indices` | A `Tensor` of type `int64`. 2-D. The `indices` of the minibatch `SparseTensor`. |\n| `sparse_values` | A `Tensor`. 1-D. The `values` of the minibatch `SparseTensor`. |\n| `sparse_shape` | A `Tensor` of type `int64`. 1-D. The `shape` of the minibatch `SparseTensor`. |\n| `out_type` | An optional [`tf.DType`](../../tf/dtypes/DType) from: `tf.string, tf.variant`. Defaults to [`tf.string`](../../tf#string). The `dtype` to use for serialization; the supported types are `string` (default) and `variant`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `out_type`. ||\n\n\u003cbr /\u003e"]]
