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 running on.
How do I get this version on Google Colab?
Google Colab supports the installation and import of all the major machine learning libraries such as Numpy, TensorFlow, PyTorch, Scikitlearn, Matplotlib, Seaborn, Pandas, etc.
You can check the imported version of PyTorch using print(torch. __version__) , if that's what you are looking for.
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
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.
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