Скачать или смотреть Troubleshooting mkl and mkl-service Installation Issues with Conda in Docker

Struggling to install `mkl` and `mkl-service` using Conda in a Docker container? This guide provides a clear explanation of the problem along with step-by-step solutions to ensure your packages install correctly.
---
This video is based on the question https://stackoverflow.com/q/75368928/ asked by the user 'MD. Jahidul Islam' ( https://stackoverflow.com/u/1096949/ ) and on the answer https://stackoverflow.com/a/75375632/ provided by the user 'merv' ( https://stackoverflow.com/u/570918/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: unable to install mkl mkl-service using conda in docker

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Troubleshooting mkl and mkl-service Installation Issues with Conda in Docker

Are you facing issues while trying to install the mkl and mkl-service packages using Conda in a Docker container? You’re not alone. Many developers encounter this problem, particularly when working with specific architectures. In this guide, we’ll break down the problem you might be experiencing and provide you with a detailed solution to overcome it.

The Problem

When you attempt to create a Conda environment with the command below:

[[See Video to Reveal this Text or Code Snippet]]

You might receive an error message similar to:

[[See Video to Reveal this Text or Code Snippet]]

This indicates that Conda cannot find the mkl and mkl-service packages in the specified channels. The important aspect to note is related to the architecture of the Docker image.

Current Environment Context

It’s crucial to understand your platform and architecture when building Docker containers, especially when working with libraries that depend on specific versions or architectures.

The provided error message specifies that Conda is attempting to use package channels related to the linux-aarch64 architecture. This is likely the root of the issue.

Understanding the Solution

Architecture Compatibility

The Intel Math Kernel Library (MKL) only works for the x86_64 architecture. Therefore, if your Docker image is set to an arm architecture (like aarch64), you will encounter errors while trying to install MKL-related packages.

Steps to Resolve the Issue

To resolve the issue, you’ll want to ensure the Docker image you are using is compatible. Here are steps you can follow:

Specify the Correct Platform:
You can explicitly set your Docker build to target the linux/amd64 platform using the following command:

[[See Video to Reveal this Text or Code Snippet]]

Update Your Dockerfile:
As an alternative, you can modify your Dockerfile's FROM line to specify the architecture by adding:

[[See Video to Reveal this Text or Code Snippet]]

Rebuild the Docker Image:
After making the necessary modifications, rebuild your Docker image to ensure that it uses the specified architecture.

Try Running the Conda Create Command Again:
Once rebuilt, attempt to create the environment using the same Conda command. This should resolve any package not found errors related to mkl and mkl-service.

Conclusion

By understanding the architecture requirements for mkl and mkl-service and setting your Docker environment to the appropriate platform, you can successfully install these packages using Conda. It’s essential to always check the compatibility and available package channels when working within Docker containers. Happy coding, and feel free to reach out with any further questions!