How to install pytorch in windows?

Question

I am trying to install pytorch on windows and there is one which is available for it but shows an error.

conda install -c peterjc123 pytorch=0.1.12


        

Answer 1

Below is the working configuration:

Python 3.8

Pytorch version 1.5.1

Windows 10

pytorch installation command:

conda install pytorch torchvision cudatoolkit=9.2 -c pytorch -c defaults -c numba/label/dev

Answer 2

Update June 2019: pytorch has a dedicated conda channel now and can be installed easily with anaconda. The command generated at pytorch will require dependencies before it can be executed successfully. For example I chose stable pytorch 1.1 build with python 3.6 and Cuda 10.0. The command generated by pytorch page was as follows:

conda install pytorch torchvision cudatoolkit=10.0 -c pytorch

But it will not work if you have created a new conda environment like me. The step by step process for setting up pytorch is as follows:

• First install the cudatoolkit as follows:

conda install -c anaconda cudatoolkit=10.0

• Then install the mkl_fft as follows:

conda install -c anaconda mkl_fft

• Assuming you will face no more dependency issues. Use the following command to setup pytorch:

conda install -c pytorch pytorch

This worked for me. But I had setup my new conda environment with scikit-learn and jupyter notebook before starting the pytorch setup. So if any dependency problem arise, it would be a good idea to install both scikit-learn and jupyter notebook as well.

Answer 3

Try running:

conda install -c pytorch pytorch

The command will update/install: conda, cudatoolkit, pytorch.

Answer 4

Try this

1. cd C:\Program files\Anaconda3\condabin
2. conda install pytorch-cpu torchvision-cpu -c pytorch

https://pytorch.org/get-started/locally/#anaconda

Answer 5

You may want to consider using Docker for Windows. This would enable you to install pytorch as you would on Linux. Although, I believe that DfW has limited CUDA support, so you may want to explore a different option if you plan on using CUDA.

Answer 6

The trick is to go to the PyTorch website and select the things you need: