local-sfmx

Name	local-sfmx JSON
Version	0.0.4 JSON
	download
home_page	https://github.com/kyegomez/LocalSoftmax
Summary	local-sftmx - Pytorch
upload_time	2023-09-29 04:13:56
maintainer
docs_url	None
author	Kye Gomez
requires_python	>=3.6,<4.0
license	MIT
keywords	artificial intelligence deep learning optimizers prompt engineering
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            [![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# LocalSoftmax
Local Softmax parallelize the softmax computation by splitting the tensor into smaller sub-tensors and applying the softmax function on each of these smaller tensors independently. In other words, we want to compute a "local" softmax on each chunk of the tensor, instead of on the entire tensor.

# Appreciation
* Lucidrains
* Agorians



# Install
`pip install local-sftmx`


## Usage
```python
import torch
from local_sfmx import local_softmax

tensor = torch.rand(10, 5)
result = local_softmax(tensor, 2)
print(result)
```

# Algorithm
function LocalSoftmax(tensor, num_chunks):
    split tensors into `num_chunks` smaller tensors
    for each smaller tensor:
        apply standard softmax
    concatenate the results
    return concatenated tensor

# License
MIT


            

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