Install Pytorch In Anaconda | Prerequisites

• linux-64

  v2.2.0

• osx-64

  v2.2.0

• osx-arm64

  v2.2.0

• win-64

  v2.2.0

conda install

To install this package run one of the following:

conda install pytorch::pytorch


To install this package run one of the following:

• linux-64

  v2.2.0

• osx-64

  v2.2.0

• osx-arm64

  v2.2.0

• win-64

  v2.2.0

conda install

To install this package run one of the following:

conda install pytorch::pytorch


To install this package run one of the following:

Install and configure PyTorch on your machine.

In the previous stage of this tutorial, we discussed the basics of PyTorch and the prerequisites of using it to create a machine learning model. Here, we’ll install it on your machine.

Prerequisites

Before you start the process of installing PyTorch on Ubuntu, ensure your Ubuntu system meets the following requirements:

• Python 3.6 or higher
• If your Ubuntu system or server is GPU supported, ensure you have the CUDA drivers and toolkit installed.

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Common Errors and Solutions

Error 1: “PackagesNotFoundError: The following packages are not available from current channels”

This error occurs when conda can’t find the PyTorch package in any of the channels that it’s searching. One solution is to add the

pytorch

channel to your conda configuration. You can add the channel by running the following command:


conda config --add channels pytorch


After adding the channel, try installing PyTorch again using the command in step 4 of the installation instructions.

Error 2: “ImportError: DLL load failed while importing _C: The specified module could not be found.”

This error occurs when PyTorch can’t find the necessary dynamic link libraries (DLLs) on your system. One solution is to install the Microsoft Visual C++ Redistributable for Visual Studio 2019. You can download it from the official Microsoft website: https://visualstudio.microsoft.com/downloads/#microsoft-visual-c-redistributable-for-visual-studio-2019. Make sure you download and install the appropriate version for your system.

Error 3: “RuntimeError: CUDA error: no kernel image is available for execution on the device”

This error occurs when you’re trying to run PyTorch on a GPU that doesn’t meet the minimum requirements. PyTorch requires a GPU with CUDA compute capability 3.5 or higher. You can check the compute capability of your GPU by running the following command:


nvidia-smi --query-gpu=name,compute_capability --format=csv


If your GPU doesn’t meet the minimum requirements, you can try running PyTorch on a CPU instead by installing the CPU version of PyTorch using the command in step 4 of the installation instructions.

Error 4: “AssertionError: Torch not compiled with CUDA enabled”

This error occurs when you’re trying to run the GPU version of PyTorch on a system without a compatible GPU or with an outdated version of CUDA. One solution is to install an older version of PyTorch that’s compatible with your system. You can find a list of compatible versions on the PyTorch website: https://pytorch.org/get-started/previous-versions/.

Installation

Anaconda

No CUDA/ROCm

To install PyTorch via Anaconda, and do not have a CUDA-capable or ROCm-capable system or do not require CUDA/ROCm (i.e. GPU support), in the above selector, choose OS: Linux, Package: Conda, Language: Python and Compute Platform: CPU. Then, run the command that is presented to you.

With CUDA

To install PyTorch via Anaconda, and you do have a CUDA-capable system, in the above selector, choose OS: Linux, Package: Conda and the CUDA version suited to your machine. Often, the latest CUDA version is better. Then, run the command that is presented to you.

With ROCm

PyTorch via Anaconda is not supported on ROCm currently. Please use pip instead.

pip

No CUDA

To install PyTorch via pip, and do not have a CUDA-capable or ROCm-capable system or do not require CUDA/ROCm (i.e. GPU support), in the above selector, choose OS: Linux, Package: Pip, Language: Python and Compute Platform: CPU. Then, run the command that is presented to you.

With CUDA

To install PyTorch via pip, and do have a CUDA-capable system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the CUDA version suited to your machine. Often, the latest CUDA version is better. Then, run the command that is presented to you.

With ROCm

To install PyTorch via pip, and do have a ROCm-capable system, in the above selector, choose OS: Linux, Package: Pip, Language: Python and the ROCm version supported. Then, run the command that is presented to you.

Verification

To ensure that PyTorch was installed correctly, we can verify the installation by running sample PyTorch code. Here we will construct a randomly initialized tensor.


import torch x = torch.rand(5, 3) print(x)


The output should be something similar to:


tensor([[0.3380, 0.3845, 0.3217], [0.8337, 0.9050, 0.2650], [0.2979, 0.7141, 0.9069], [0.1449, 0.1132, 0.1375], [0.4675, 0.3947, 0.1426]])


Additionally, to check if your GPU driver and CUDA/ROCm is enabled and accessible by PyTorch, run the following commands to return whether or not the GPU driver is enabled (the ROCm build of PyTorch uses the same semantics at the python API level (https://github.com/pytorch/pytorch/blob/master/docs/source/notes/hip.rst#hip-interfaces-reuse-the-cuda-interfaces), so the below commands should also work for ROCm):


import torch torch.cuda.is_available()


How to install PyTorch on Ubuntu?

There are a few ways to install PyTorch on Ubuntu, including building from the source, but this guide will show you how to install PyTorch using Pip as well as how to install PyTorch using Anaconda. Also, PyTorch provides both CPU (Central Processing Unit) and GPU (Graphics Processing Unit) options, so if your system doesn’t have GPU support, you can install PyTorch with CPU support only.

Pip: install PyTorch

You can install PyTorch on Ubuntu using Pip (Python’s native package manager) in the following steps:

Step 1 – Update system packages

First, update the system packages to ensure that you’re using the latest packages.


sudo apt update


Step 2 – Install Python3-venv

Next, you need to install Python3-venv, which you can use to create an isolated Python environment for your project so you don’t have to install Python packages globally, thereby preventing possible compatibility issues.


sudo apt install python3-venv -y


Step 3 – Set up the environment

Now create and navigate to a new directory that will be used to store the virtual environment files and settings. Here “pytorch_env” is the name of the directory; you can use a different name if you want.


mkdir pytorch_env cd pytorch_env


Next, run the following commands to create and activate the virtual environment.


python3 -m venv pytorch_env source pytorch_env/bin/activate


Once the virtual environment has been activated, you should see your command prompt change to show the name of the virtual environment. With this activated, you can install Python packages or scripts associated with this virtual environment rather than the system-wide Python avoiding conflicts with projects requiring different package versions.

Step 4 – Install PyTorch using Pip

Now with your virtual environment activated, you can go on to install PyTorch on your Ubuntu system.

With CPU support only:

To install PyTorch with CPU support only, run:


pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu


With GPU support (install CUDA with PyTorch) (CUDA):

To install PyTorch with GPU support run:


pip3 install torch torchvision torchaudio


Step 5 – Verify the installation

You can run the following command to verify that PyTorch has been installed:


python import torch print(torch.__version__)


The command above will start the Python interpreter, import the PyTorch library and print the version of PyTorch that is currently installed.

Conda: install PyTorch

Another way you can install PyTorch is by using an open-source platform called Anaconda. You can install PyTorch using Conda in the following steps:

Step 1 – Update system packages

As usual, you want to make sure that your system packages are up to date.


sudo apt update


Step 2 – Install Anaconda

Next, you need to install Anaconda, and you can do that in the following steps.

First, you need to install Curl. This will be used to download the Anaconda installer script.


sudo apt install curl -y


Next, as a best practice, you want to isolate the installation process. Navigate to “tmp” directory, you can create or use a different directory for this if you want.


cd /tmp


Next, download the Anaconda installer script using Curl by running the command:


curl --output anaconda.sh https://repo.anaconda.com/archive/Anaconda3-2023.07-2-Linux-x86_64.sh


The command above will download the Anaconda installer script and save it as a file called “anaconda.sh”. You can always get the URL for the latest version of the script on their site.

Now verify the integrity of the downloaded file using:


sha256sum anaconda.sh


You want to confirm that the sha256sum checksum value matches that on the official site.

After verifying the downloading script, you can go on to run the Anaconda installer script and start the installation process by running:


bash anaconda.sh


After the installation process is complete, you need to update the current shell session to ensure that the Anaconda environment and its commands are available for use in the current terminal session. Do this by running:


source ~/.bashrc


It will also activate Anaconda, as you can see in the change in the prompt to “base,” which is the default environment created by Anaconda during the installation. Subsequently, you can use the

conda activate

command to activate Anaconda.

You can verify that Anaconda has been installed using the

conda --version

command

Step 3 – Install PyTorch using Anaconda

Now with Anaconda installed and activated, you can use it to install PyTorch.

With CPU support only:


conda install pytorch torchvision torchaudio cpuonly -c pytorch


With GPU support (install PyTorch with CUDA):


conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia


Step 4 – Verify the installation

Run the following command to verify that PyTorch has been installed:


python import torch print(torch.__version__)


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Prerequisites

Supported Windows Distributions

PyTorch is supported on the following Windows distributions:

• Windows 7 and greater; Windows 10 or greater recommended.
• Windows Server 2008 r2 and greater

The install instructions here will generally apply to all supported Windows distributions. The specific examples shown will be run on a Windows 10 Enterprise machine

Python

Currently, PyTorch on Windows only supports Python 3.8-3.11; Python 2.x is not supported.

As it is not installed by default on Windows, there are multiple ways to install Python:

If you use Anaconda to install PyTorch, it will install a sandboxed version of Python that will be used for running PyTorch applications.

If you decide to use Chocolatey, and haven’t installed Chocolatey yet, ensure that you are running your command prompt as an administrator.

For a Chocolatey-based install, run the following command in an administrative command prompt:


choco install python


Package Manager

To install the PyTorch binaries, you will need to use at least one of two supported package managers: Anaconda and pip. Anaconda is the recommended package manager as it will provide you all of the PyTorch dependencies in one, sandboxed install, including Python and

pip.


Anaconda

To install Anaconda, you will use the 64-bit graphical installer for PyTorch 3.x. Click on the installer link and select

Run

. Anaconda will download and the installer prompt will be presented to you. The default options are generally sane.

pip

If you installed Python by any of the recommended ways above, pip will have already been installed for you.

Introduction

PyTorch has become increasingly popular over the years due to its ease of use, dynamic computation graph, and efficiency, making it a top choice for implementing deep learning models. If you want to explore this tool and learn how to install PyTorch on Ubuntu, this guide will help!

In this tutorial, we will walk you through the process of installing PyTorch on your Ubuntu system using Pip or Anaconda to help you get started to take advantage of this tool.

Conclusion

At this point, you should have PyTorch installed on your system. This guide showed how to install PyTorch on Ubuntu using Pip and Anaconda. You also learned that PyTorch has options you can download based on the computation resources available on your system. With the installation of PyTorch out of the way, you can move in to explore its capabilities and experience its efficiency.

How to Install PyTorch in Anaconda with Conda or Pip

PyTorch is an open-source machine learning framework that allows developers to build and train neural networks. It is widely used in the data science community due to its flexibility and ease of use. PyTorch can be installed using Anaconda, a popular distribution of the Python programming language that is widely used in data science.

In this blog post, we will explore two methods for installing PyTorch in Anaconda: using Conda and using Pip. We will discuss the advantages and disadvantages of each method, as well as the steps required to install PyTorch using each method.

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Phản hồi

Gửi và xem ý kiến phản hồi dành cho

I am trying to install pytorch in Anaconda to work with Python 3.5 in Windows. Following the instructions in pytorch.org I introduced the following code in Anaconda:


pip3 install torch torchvision


But the following error came in:


Command "python setup.py egg_info" failed with error code 1 in C:\Users\sluis\AppData\Local\Temp\pip-install-qmrvz7b9\torch\


By searching on the web I found out that it may be because of

setuptools

being out of date but I checked and have it updated. I also tried:


conda install -c peterjc123 pytorch cuda80


But the following error arise:


The following specifications were found to be in conflict: - pytorch Use "conda info " to see the dependencies for each package.

I also tried to load the pytorch’s tar.bz2 file which I download in the following website:

anaconda.org/peterjc123/pytorch/files

And then just do:


$ conda install filename.tar.bz2


But I got the following error:


Error: HTTPError: 404 Client Error: None for url: file:///C|/Users/sluis/pytorch-0.3.1-py36_cuda80_cudnn6he774522_2.tar.bz2: file:///C|/Users/sluis/pytorch-0.3.1-py36_cuda80_cudnn6he774522_2.tar.bz2


I am quite new to this programming world so I don’t really know how to dig more on the errors. Anyone knows how to get pytorch installed?

Edit: As suggested in the comments I tried:


conda install pytorch torchivsion -c pytorch


And I got the following error:


Error: Packages missing in current win-64 channels: - pytorch - torchvision


I did:


anaconda search -t conda torchvision


And tried to install

dericlk/torchvision

using the following command:


conda install -c derickl torchvision


But I am getting the same error:


Error: Package missing in current win-64 channels: - torchvision


I couldn’t find any

torchvision

packages for win-64.


conda list

is giving me the following:


# packages in environment at C:\Users\aaaa\AppData\Local\Continuum\Anaconda3\envs\torchenv2: # mkl-include 2018.0.2 1 anaconda certifi 2016.2.28 py35_0 cffi 1.10.0 py35_0 cmake 3.6.3 vc14_0 [vc14] openmp 2018.0.0 intel_8 intel mkl 2017.0.3 0 numpy 1.13.1 py35_0 pip 10.0.0 pip 9.0.1 py35_1 pycparser 2.18 py35_0 python 3.5.4 0 pyyaml 3.12 py35_0 setuptools 36.4.0 py35_1 typing 3.6.2 py35_0 vc 14 0 vs2015_runtime 14.0.25420 0 wheel 0.29.0 py35_0 wincertstore 0.2 py35_0 zlib 1.2.11 vc14_0 [vc14]

=======

Although, Python and PyTorch can be installed directly from the R console, before start running

rTorch

, I would recommend installing PyTorch first in a new Python or Python-Anaconda environment. Then, testing if PyTorch and Torchvision packages are imported alright. The advantage of doing it this way is that you define in advanced the base Python or Anaconda version to install. Although the same can be done from rTorch you will need to get familiar passing parameters through one its functions.

If you opt to install PyTorch from R, rTorch has functions that could help you install PyTorch from the R console.

This function is public and can be invoked with

rTorch::install_pytorch()

.

This function will allow you to indicate (i) the Python version; (ii) the PyTorch version; (iii) the name of the conda environment; (iv) which channel (

stable

or

nightly

); (v) if you require CUDA (GPU) computation; (vi) additional packages such as

matplotlib

,

pandas

; (vii) more.


install_pytorch( method = c("conda", "virtualenv", "auto"), conda = "auto", version = "default", envname = "r-torch", extra_packages = NULL, restart_session = TRUE, conda_python_version = "3.6", pip = FALSE, channel = "stable", cuda_version = NULL, dry_run = FALSE, ... )


If you prefer do it manually, use this example:

Create a conda environment with

conda create -n my-torch python=3.7 -y


Activate the new environment with

conda activate my-torch


Inside the new environment, install PyTorch and related packages with:


conda install python=3.6 pytorch torchvision matplotlib pandas -c pytorch


Note: If you you don’t specify a version,


conda

will install the latest PyTorch. As of this writing (August-September 2020), the latest PyTorch version is 1.6.

Alternatively, you could create and install a conda environment a specific PyTorch version with:


conda create -n my-torch python=3.6 pytorch=1.3 torchvision matplotlib pandas -c pytorch -y



conda

will resolve the dependencies and versions of the other packages automatically, or let you know your options.

Note.

matplotlib

and

pandas

are not really necessary, but I was asked if

matplotlib

or

pandas

would work in PyTorch. Then, I decided to put them for testing and experimentation. They both work.

In rTorch there is an automatic detection of Python built in in the package that will ask you to install

Miniconda

first if you don’t have any Python installed in your machine. For instance, in

macOS

, Miniconda will be installed under

PREFIX=/Users/user_name/Library/r-miniconda

.

After Miniconda is installed, you could proceed to install the flavor or PyTorch you want, and the packages you want, with a command like this:


rTorch:::install_conda(package="pytorch=1.4", envname="r-torch", conda="auto", conda_python_version = "3.6", pip=FALSE, channel="pytorch", extra_packages=c("torchvision", "cpuonly", "matplotlib", "pandas"))


The command above will install the stable PyTorch 1.4 version on Python 3.6, including three additional packages:

torchvision

,

cpuonly

,

matplotlib

and

pandas.


NOTE. My experience with


Miniconda

is spotty and not 100% reliable, specially in macOS. I would strongly recommend using full conda for your PyTorch installation.

This tutorial explains the steps to install PyTorch on Windows.

PyTorch is a free and open source machine learning library developed by Facebook’s AI Research lab. It is built on the Torch library and is mainly used for tasks like computer vision and natural language processing (NLP).

Why Install PyTorch using Conda?

Installing PyTorch using pip on Windows can be challenging due to compatibility issues with the operating system. Additionally, PyTorch requires several dependencies, including CUDA and cuDNN for GPU support, which can be difficult to install using pip.

Conda is a package manager that simplifies the installation process by managing dependencies and resolving conflicts between packages. It provides an easy-to-use interface for installing and managing packages, making it an ideal choice for installing PyTorch on Windows.

Building from source

For the majority of PyTorch users, installing from a pre-built binary via a package manager will provide the best experience. However, there are times when you may want to install the bleeding edge PyTorch code, whether for testing or actual development on the PyTorch core. To install the latest PyTorch code, you will need to build PyTorch from source.

Prerequisites

1. Install Anaconda or Pip
2. If you need to build PyTorch with GPU support a. for NVIDIA GPUs, install CUDA, if your machine has a CUDA-enabled GPU. b. for AMD GPUs, install ROCm, if your machine has a ROCm-enabled GPU
3. Follow the steps described here: https://github.com/pytorch/pytorch#from-source

You can verify the installation as described above.

Installing on Windows

PyTorch can be installed and used on various Windows distributions. Depending on your system and compute requirements, your experience with PyTorch on Windows may vary in terms of processing time. It is recommended, but not required, that your Windows system has an NVIDIA GPU in order to harness the full power of PyTorch’s CUDA support.

Method 2: Installing PyTorch with Pip

Pip is another popular package manager that is widely used in the Python community. It allows developers to easily install and manage Python packages and dependencies. Installing PyTorch with Pip is also straightforward and can be done in a few simple steps.

1. Open the Anaconda Prompt or Terminal.

2. Create a new conda environment for PyTorch using the following command:

   
conda create --name pytorch_env


   This will create a new environment called

   
pytorch_env

   .

3. Activate the new environment using the following command:

   
conda activate pytorch_env


4. Install PyTorch using the following command:

   
pip install torch torchvision torchaudio


   This will install the latest version of PyTorch, as well as the torchvision and torchaudio packages.

5. Verify the installation by running the following Python code:

   
import torch print(torch.__version__)


   If PyTorch is installed correctly, it should print the version number of PyTorch.

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Prerequisites

Supported Linux Distributions

PyTorch is supported on Linux distributions that use glibc >= v2.17, which include the following:

• Arch Linux, minimum version 2012-07-15
• CentOS, minimum version 7.3-1611
• Debian, minimum version 8.0
• Fedora, minimum version 24
• Mint, minimum version 14
• OpenSUSE, minimum version 42.1
• PCLinuxOS, minimum version 2014.7
• Slackware, minimum version 14.2
• Ubuntu, minimum version 13.04

The install instructions here will generally apply to all supported Linux distributions. An example difference is that your distribution may support


yum

instead of

apt

. The specific examples shown were run on an Ubuntu 18.04 machine.

Python

Python 3.8-3.11 is generally installed by default on any of our supported Linux distributions, which meets our recommendation.

Tip: By default, you will have to use the command


python3

to run Python. If you want to use just the command

python

, instead of

python3

, you can symlink

python

to the

python3

binary.

However, if you want to install another version, there are multiple ways:

• APT
• Python website

If you decide to use APT, you can run the following command to install it:


sudo apt install python


If you use Anaconda to install PyTorch, it will install a sandboxed version of Python that will be used for running PyTorch applications.

Package Manager

To install the PyTorch binaries, you will need to use one of two supported package managers: Anaconda or pip. Anaconda is the recommended package manager as it will provide you all of the PyTorch dependencies in one, sandboxed install, including Python.

Anaconda

To install Anaconda, you will use the command-line installer. Right-click on the 64-bit installer link, select

Copy Link Location

, and then use the following commands:


# The version of Anaconda may be different depending on when you are installing` curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh sh Miniconda3-latest-Linux-x86_64.sh # and follow the prompts. The defaults are generally good.`


You may have to open a new terminal or re-source your


~/.bashrc

to get access to the

conda

command.

pip

Python 3

While Python 3.x is installed by default on Linux,

pip

is not installed by default.


sudo apt install python3-pip


Tip: If you want to use just the command


pip

, instead of

pip3

, you can symlink

pip

to the

pip3

binary.

Prerequisites

Make sure your computer satisfies the following requirements before installing PyTorch

• Windows 10 or higher (recommended)
• Python 3.8 or higher
• CUDA for GPU support (optional)

The first step is to check that your Python version is Python 3.8 or higher. To do this, open the command prompt using the Windows key + R shortcut, type “cmd” and then enter the following command.

python –version

Method 2: Installing PyTorch with Pip

Pip is another popular package manager that is widely used in the Python community. It allows developers to easily install and manage Python packages and dependencies. Installing PyTorch with Pip is also straightforward and can be done in a few simple steps.

1. Open the Anaconda Prompt or Terminal.

2. Create a new conda environment for PyTorch using the following command:

   
conda create --name pytorch_env


   This will create a new environment called

   
pytorch_env

   .

3. Activate the new environment using the following command:

   
conda activate pytorch_env


4. Install PyTorch using the following command:

   
pip install torch torchvision torchaudio


   This will install the latest version of PyTorch, as well as the torchvision and torchaudio packages.

5. Verify the installation by running the following Python code:

   
import torch print(torch.__version__)


   If PyTorch is installed correctly, it should print the version number of PyTorch.

Need a straightforward way to install PyTorch in Anaconda? Saturn Cloud provides an easy-to-use environment to handle your data science installations. Join for free today.