PyTorch v1.0.0 stable was released on 8 December 2018 after being announced 7 months earlier.
I want get a version optimised for the hardware that my IPython kernel is r
With version 1.0.0, PyTorch changed the download URL format from:
https://download.pytorch.org/whl/cu92/torch-1.0.0-cp36-cp36m-linux_x86_64.whl
to
https://download.pytorch.org/whl/cu90/torch-1.0.0-cp36-cp36m-linux_x86_64.whl
(The change is in the CUDA version part, where cu92
changes to cu90
.)
To programmatically generate that URL, I used the following code:
from os.path import exists
from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag
platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())
cuda_output = !ldconfig -p|grep cudart.so|sed -e 's/.*\.\([0-9]*\)\.\([0-9]*\)$/cu\10/'
accelerator = cuda_output[0] if exists('/dev/nvidia0') else 'cpu'
torch_url=f"http://download.pytorch.org/whl/{accelerator}/torch-{version}-{platform}-linux_x86_64.whl"
version='1.0.0'
!pip install -U {torch_url} torchvision
You can then change the version
variable as desired as newer versions are released.
For version 1.1.0, this works
!pip install -q torch==1.1.0 torchvision
try the following code snippet (it works equally for the runtime with or without gpu)
!pip install -q torch==1.0.0 torchvision
to check the version
import torch
print(torch.__version__)
here you have the version 1.0.0
UPDATE
!pip install torch
Works fine now, as the most stable version is 1.0.0
It worked for me you can try
!pip install torch
!pip install torchvision
!pip install mxnet-cu101
You can now just
import torch
No need for additional installation.
Here is a code to install pytorch. You can change it to whatever version you want.
!pip3 install http://download.pytorch.org/whl/cu92/torch-1.0.0-cp36-cp36m-linux_x86_64.whl