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# Sparse NDArray API
``` eval_rst
.. currentmodule:: mxnet.ndarray.sparse
```
## Overview
This document lists the routines of the * n * -dimensional sparse array package:
``` eval_rst
.. autosummary::
:nosignatures:
mxnet.ndarray.sparse
```
The `CSRNDArray` and `RowSparseNDArray` API, defined in the `ndarray.sparse` package, provides
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imperative sparse tensor operations on **CPU ** .
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An `CSRNDArray` inherits from `NDArray` , and represents a two-dimensional, fixed-size array in compressed sparse row format.
``` python
>> > x = mx . nd . array ( [ [ 1 , 0 ] , [ 0 , 0 ] , [ 2 , 3 ] ] )
>> > csr = x . tostype ( ' csr ' )
>> > type ( csr )
< class ' mxnet . ndarray . sparse . CSRNDArray ' >
>> > csr . shape
( 3 , 2 )
>> > csr . data . asnumpy ( )
array ( [ 1. 2. 3. ] , dtype = float32 )
>> > csr . indices . asnumpy ( )
array ( [ 0 , 0 , 1 ] )
>> > csr . indptr . asnumpy ( )
array ( [ 0 , 1 , 1 , 3 ] )
>> > csr . stype
' csr '
```
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A detailed tutorial is available at
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[CSRNDArray - NDArray in Compressed Sparse Row Storage Format ](https://mxnet.incubator.apache.org/versions/master/tutorials/sparse/csr.html ).
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<br>
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An `RowSparseNDArray` inherits from `NDArray` , and represents a multi-dimensional, fixed-size array in row sparse format.
``` python
>> > x = mx . nd . array ( [ [ 1 , 0 ] , [ 0 , 0 ] , [ 2 , 3 ] ] )
>> > row_sparse = x . tostype ( ' row_sparse ' )
>> > type ( row_sparse )
< class ' mxnet . ndarray . sparse . RowSparseNDArray ' >
>> > row_sparse . data . asnumpy ( )
array ( [ [ 1. 0. ] ,
[ 2. 3. ] ] , dtype = float32 )
>> > row_sparse . indices . asnumpy ( )
array ( [ 0 , 2 ] )
>> > row_sparse . stype
' row_sparse '
```
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A detailed tutorial is available at
[RowSparseNDArray - NDArray for Sparse Gradient Updates ](https://mxnet.incubator.apache.org/versions/master/tutorials/sparse/row_sparse.html ).
<br><br>
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``` eval_rst
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.. note:: ``mxnet.ndarray.sparse.RowSparseNDArray`` and ``mxnet.ndarray.sparse.CSRNDArray`` DO NOT support the ``mxnet.gluon`` high-level interface yet.
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.. note:: ``mxnet.ndarray.sparse`` is similar to ``mxnet.ndarray`` in some aspects. But the differences are not negligible. For instance:
- Only a subset of operators in ``mxnet.ndarray`` have specialized implementations in ``mxnet.ndarray.sparse``.
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Operators such as Convolution and broadcasting do not have sparse implementations yet.
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- The storage types (``stype``) of sparse operators' outputs depend on the storage types of inputs.
By default the operators not available in ``mxnet.ndarray.sparse`` infer "default" (dense) storage type for outputs.
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Please refer to the [API Reference](#api-reference) section for further details on specific operators.
- GPU support for ``mxnet.ndarray.sparse`` is experimental. Only a few sparse operators are supported on GPU such as ``sparse.dot``.
.. note:: ``mxnet.ndarray.sparse.CSRNDArray`` is similar to ``scipy.sparse.csr_matrix`` in some aspects. But they differ in a few aspects:
- In MXNet the column indices (``CSRNDArray.indices``) for a given row are expected to be **sorted in ascending order**.
Duplicate column entries for the same row are not allowed.
- ``CSRNDArray.data``, ``CSRNDArray.indices`` and ``CSRNDArray.indptr`` always create deep copies, while it's not the case in ``scipy.sparse.csr_matrix``.
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```
In the rest of this document, we first overview the methods provided by the
`ndarray.sparse.CSRNDArray` class and the `ndarray.sparse.RowSparseNDArray` class,
and then list other routines provided by the `ndarray.sparse` package.
The `ndarray.sparse` package provides several classes:
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray
RowSparseNDArray
```
We summarize the interface for each class in the following sections.
## The `CSRNDArray` class
### Array attributes
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.shape
CSRNDArray.context
CSRNDArray.dtype
CSRNDArray.stype
CSRNDArray.data
CSRNDArray.indices
CSRNDArray.indptr
```
### Array conversion
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.copy
CSRNDArray.copyto
CSRNDArray.as_in_context
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CSRNDArray.asscipy
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CSRNDArray.asnumpy
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CSRNDArray.asscalar
CSRNDArray.astype
CSRNDArray.tostype
```
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### Array inspection
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.check_format
```
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### Array creation
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.zeros_like
```
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### Array reduction
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.sum
CSRNDArray.mean
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CSRNDArray.norm
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```
### Powers
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.square
```
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### Indexing
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.__getitem__
CSRNDArray.__setitem__
CSRNDArray.slice
```
### Lazy evaluation
``` eval_rst
.. autosummary::
:nosignatures:
CSRNDArray.wait_to_read
```
## The `RowSparseNDArray` class
### Array attributes
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.shape
RowSparseNDArray.context
RowSparseNDArray.dtype
RowSparseNDArray.stype
RowSparseNDArray.data
RowSparseNDArray.indices
```
### Array conversion
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.copy
RowSparseNDArray.copyto
RowSparseNDArray.as_in_context
RowSparseNDArray.asnumpy
RowSparseNDArray.asscalar
RowSparseNDArray.astype
RowSparseNDArray.tostype
```
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### Array inspection
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.check_format
```
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### Array creation
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.zeros_like
```
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### Array reduction
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.norm
```
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### Array rounding
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.round
RowSparseNDArray.rint
RowSparseNDArray.fix
RowSparseNDArray.floor
RowSparseNDArray.ceil
RowSparseNDArray.trunc
```
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### Trigonometric functions
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.sin
RowSparseNDArray.tan
RowSparseNDArray.arcsin
RowSparseNDArray.arctan
RowSparseNDArray.degrees
RowSparseNDArray.radians
```
### Hyperbolic functions
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.sinh
RowSparseNDArray.tanh
RowSparseNDArray.arcsinh
RowSparseNDArray.arctanh
```
### Exponents and logarithms
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.expm1
RowSparseNDArray.log1p
```
### Powers
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.sqrt
RowSparseNDArray.square
```
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### Indexing
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.__getitem__
RowSparseNDArray.__setitem__
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RowSparseNDArray.retain
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```
### Lazy evaluation
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.wait_to_read
```
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### Miscellaneous
``` eval_rst
.. autosummary::
:nosignatures:
RowSparseNDArray.clip
RowSparseNDArray.sign
```
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## Array creation routines
``` eval_rst
.. autosummary::
:nosignatures:
array
empty
zeros
zeros_like
csr_matrix
row_sparse_array
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mxnet.ndarray.load
mxnet.ndarray.save
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```
## Array manipulation routines
### Changing array storage type
``` eval_rst
.. autosummary::
:nosignatures:
cast_storage
```
### Indexing routines
``` eval_rst
.. autosummary::
:nosignatures:
slice
retain
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where
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```
## Mathematical functions
### Arithmetic operations
``` eval_rst
.. autosummary::
:nosignatures:
elemwise_add
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elemwise_sub
elemwise_mul
negative
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dot
add_n
```
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### Trigonometric functions
``` eval_rst
.. autosummary::
:nosignatures:
sin
tan
arcsin
arctan
degrees
radians
```
### Hyperbolic functions
``` eval_rst
.. autosummary::
:nosignatures:
sinh
tanh
arcsinh
arctanh
```
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### Reduce functions
``` eval_rst
.. autosummary::
:nosignatures:
sum
mean
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norm
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```
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### Rounding
``` eval_rst
.. autosummary::
:nosignatures:
round
rint
fix
floor
ceil
trunc
```
### Exponents and logarithms
``` eval_rst
.. autosummary::
:nosignatures:
expm1
log1p
```
### Powers
``` eval_rst
.. autosummary::
:nosignatures:
sqrt
square
```
### Miscellaneous
``` eval_rst
.. autosummary::
:nosignatures:
abs
sign
```
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## Neural network
### Updater
``` eval_rst
.. autosummary::
:nosignatures:
sgd_update
sgd_mom_update
adam_update
ftrl_update
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adagrad_update
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```
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### More
``` eval_rst
.. autosummary::
:nosignatures:
make_loss
stop_gradient
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mxnet.ndarray.contrib.SparseEmbedding
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LinearRegressionOutput
LogisticRegressionOutput
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```
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## API Reference
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<script type="text/javascript" src='../../../_static/js/auto_module_index.js'></script>
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``` eval_rst
.. autoclass:: mxnet.ndarray.sparse.CSRNDArray
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:members: shape, context, dtype, stype, data, indices, indptr, copy, copyto, as_in_context, asscipy, asnumpy, asscalar, astype, tostype, slice, wait_to_read, zeros_like, __neg__, sum, mean, norm, square, __getitem__, __setitem__, check_format
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.. autoclass:: mxnet.ndarray.sparse.RowSparseNDArray
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:members: shape, context, dtype, stype, data, indices, copy, copyto, as_in_context, asnumpy, asscalar, astype, tostype, wait_to_read, zeros_like, round, rint, fix, floor, ceil, trunc, sin, tan, arcsin, arctan, degrees, radians, sinh, tanh, arcsinh, arctanh, expm1, log1p, sqrt, square, __negative__, norm, __getitem__, __setitem__, check_format, retain, clip, sign
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.. automodule:: mxnet.ndarray.sparse
:members:
:special-members:
:exclude-members: BaseSparseNDArray, RowSparseNDArray, CSRNDArray
.. automodule:: mxnet.ndarray.sparse
:members: array, zeros, empty
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.. automodule:: mxnet.ndarray
:members: load, save
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```
<script>auto_index("api-reference");</script>
