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[DOC] Large tensors documentation update #20860

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[DOC] Large tensors documentation update #20860

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DominikaJedynak Dec 27, 2021
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DominikaJedynak Jan 19, 2022
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DominikaJedynak Feb 8, 2022
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18 changes: 8 additions & 10 deletions docs/static_site/src/pages/api/faq/large_tensor_support.md
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Expand Up @@ -26,10 +26,9 @@ permalink: /api/faq/large_tensor_support
# Using MXNet with Large Tensor Support

## What is large tensor support?
When creating a network that uses large amounts of data, as in a deep graph problem, you may need large tensor support. This is a relatively new feature as tensors are indexed in MXNet using INT32 indices by default. Now MXNet build with Large Tensor supports INT64 indices.
When creating a network that uses large amounts of data, as in a deep graph problem, you may need large tensor support. This means tensors are indexed using INT64, instead of INT32 indices.

It is MXNet built with an additional flag *USE_INT64_TENSOR_SIZE=1*
in CMAKE it is built using *USE_INT64_TENSOR_SIZE:“ON”*
This feature is enabled when MXNet is built with a flag *USE_INT64_TENSOR_SIZE=1*, which is now a default setting. You can also make MXNet use INT32 indices by changing this flag.

## When do you need it?
1. When you are creating NDArrays of size larger than 2^31 elements.
Expand Down Expand Up @@ -71,8 +70,8 @@ The following are the cases for large tensor usage where you must specify `dtype
* _randint():_

```python
low_large_value = 2*32*
*high_large_value = 2*34
low_large_value = 2**32
high_large_value = 2**34
# dtype is explicitly specified since default type is int32 for randint
a = nd.random.randint(low_large_value, high_large_value, dtype=np.int64)
```
Expand Down Expand Up @@ -141,16 +140,15 @@ Backward pass is partially supported and not completely tested, so it is conside

Not supported:

* GPU and oneDNN.
* GPU.
* Windows, ARM or any operating system other than Ubuntu
* Any permutation of MXNet wheel that contains oneDNN.
* Other language bindings like Scala, Java, R, and Julia.


## Other known Issues:
Randint operator is flaky: https://github.com/apache/incubator-mxnet/issues/16172
dgemm operations using BLAS libraries currently don’t support int64.
linspace() is not supported.
* Randint operator is flaky: https://github.com/apache/incubator-mxnet/issues/16172.
* dgemm operations using BLAS libraries currently don’t support int64.
* linspace() is not supported.

```python
a = mx.sym.Variable('a')
Expand Down