Jetware - package: PyTorch

Package

pytorch-0.4.0--python-3.6.3--cuda-9.1.85--cudnn-7.0.5--openblas-0.2.19

Module

pytorch

Version

0.4.0

Flavor

python-3.6.3--cuda-9.1.85--cudnn-7.0.5--openblas-0.2.19

Other branches

1.0.0, 0.4.1, 0.3.1, 0.1.11

Other flavors

python-3.6.3--openblas-0.2.19, python-2.7.14--cuda-8.0.61--cudnn-7.0.3--openblas-0.2.19, python-3.5.4--cuda-8.0.61--cudnn-6.0.21--openblas-0.2.19, python-3.5.4--cuda-9.1.85--cudnn-7.0.5--openblas-0.2.19, python-3.5.4--openblas-0.2.19, python-3.5.4--cuda-9.0.176--cudnn-7.0.3--openblas-0.2.19, python-3.6.3--mkl-2018.2.199, python-3.6.3--cuda-8.0.61--cudnn-7.0.3--openblas-0.2.19, python-3.5.4--mkl-2018.2.199, python-3.6.3--cuda-8.0.61--cudnn-6.0.21--openblas-0.2.19

Ruolo

pytorch

Descrizione

PyTorch, an open source machine learning library for Python.

Sito web

http://pytorch.org

Requires

libc, cuda_runtime, gcc-libstdcxx, gcc-libgcc_s, gcc-libgomp, gcc-libgfortran, openmpi, hiredis, nccl2, python_typing, python_setuptools, python_wheel, python_pyyaml, python_numpy, python_cffi, python:3.6.3, cuda:9.1.85, cudnn:7.0.5, openblas:0.2.19

Costruttori (1)

Machine Learning Education

The runtime environment constructor for the machine learning and deep learning tutorials and courses.

Appliances (2)

aise / PyTorch 0.4 Python 3.6 CUDA 9.1 Production

A pre-configured and fully integrated software stack with PyTorch, an open source software library for machine learning, and the Python programming language. The stack is designed for short and long-running high-performance tasks and is optimized for running on NVidia GPU.

pytorch:0.4.0, python:3.6.3, cuda:9.1.85.3, cudnn:7.1.3, cuda_only-nvidia_drivers:396.24, development_preset:1

aise / PyTorch 0.4 Python 3.6 CUDA 9.1 Notebook

A pre-configured and fully integrated minimal runtime environment with PyTorch, an open source machine learning library for Python, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. The stack is optimized for running on NVidia GPU.

pytorch:0.4.0, python:3.6.3, jupyter_notebook:1.0.0, cuda:9.1.85.3, cudnn:7.1.3, cuda_only-nvidia_drivers:396.24, development_preset:1