MXNet is an ultra-scalable deep learning framework. This version uses CUDA-8.0.
Project description
MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix the flavours of deep learning programs together to maximize the efficiency and your productivity.
For feature requests on the PyPI package, suggestions, and issue reports, click here. Prerequisites ———— This package supports Linux and Windows platform only, and requires CUDA-8.0 for GPU acceleration. Also checkout other versions: mxnet-cu90, mxnet-cu90mkl, mxnet-cu91mkl, mxnet-cu91, mxnet-cu80mkl, mxnet-cu75mkl, and mxnet-cu75.
To download, check CUDA download. For more instructions, check CUDA Toolkit online documentation.
To install for other platforms (e.g. Raspberry Pi/ARM) or other versions of CUDA, check Installing MXNet for instructions on building from source.
Installation
To install:
pip install mxnet-cu80Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file mxnet_cu80-1.1.0.post0-py2.py3-none-win_amd64.whl.
File metadata
- Download URL: mxnet_cu80-1.1.0.post0-py2.py3-none-win_amd64.whl
- Upload date:
- Size: 351.4 MB
- Tags: Python 2, Python 3, Windows x86-64
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8c1fd1d3770efe7de887f53b825558825e3f5bb7bb9f17988fef0a8a24c1c8bc
|
|
| MD5 |
6bdaa2637a2a566596dfe45ba7108a2b
|
|
| BLAKE2b-256 |
e49864afa63f359491fd4ce179298b56798d0b1abf6aefdceb0cca86dd7bc3b6
|
File details
Details for the file mxnet_cu80-1.1.0.post0-py2.py3-none-manylinux1_x86_64.whl.
File metadata
- Download URL: mxnet_cu80-1.1.0.post0-py2.py3-none-manylinux1_x86_64.whl
- Upload date:
- Size: 253.6 MB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
594e04ee088f40001407e8482594a4ac257c8b071e5eba0c9335a8329112884e
|
|
| MD5 |
45b2c856bf21a6cab7e1b96a451ad777
|
|
| BLAKE2b-256 |
9b15bc0502203c9c102c544dbf1d31f1222a137b7176de4355bfe9e30b44dd22
|
