Row 5175

Row ID: 5175 | Dataset Entry | Axioma AXP Content Repository

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Hi all, I created a docker image and a VS Code devcontainer configuration file based on it. With this config (or you can solely use the image), we can avoid the heavy work of environment configuration, such as the annoying incompatible CUDA version, python version, and python dependencies problems. This is because you can always hack the \`Dockerfile\` to change the environment config and rebuild the image.

Since docker container is totally clean, we don't have to do \`conda create -n XXX\` for each project, thus making our code highly reproducible.

Moreover, you can have a CUDA11 container while your host is on CUDA12, this is convenient in a lot of situations.

I hope this can be helpful to you!

Link: [https://github.com/LYK-love/VS-Code-DevContainer-Config](https://github.com/LYK-love/VS-Code-DevContainer-Config)

FieldValue
text Hi all, I created a docker image and a VS Code devcontainer configuration file based on it. With this config (or you can solely use the image), we can avoid the heavy work of environment configuration, such as the annoying incompatible CUDA version, python version, and python dependencies problems. This is because you can always hack the \`Dockerfile\` to change the environment config and rebuild the image. Since docker container is totally clean, we don't have to do \`conda create -n XXX\` fo…
label r/deeplearning
dataType post
communityName r/deeplearning
datetime 2024-04-26
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{
  "text": "Hi all, I created a docker image and a VS Code devcontainer configuration file based on it. With this config (or you can solely use the image), we can avoid the heavy work of environment configuration, such as the annoying incompatible CUDA version, python version, and python dependencies problems. This is because you can always hack the \\`Dockerfile\\` to change the environment config and rebuild the image. \n\nSince docker container is totally clean, we don't have to do \\`conda create -n XXX\\` for each project, thus making our code highly reproducible. \n\nMoreover, you can have a CUDA11 container while your host is on CUDA12, this is convenient in a lot of situations.\n\nI hope this can be helpful to you!\n\nLink: [https://github.com/LYK-love/VS-Code-DevContainer-Config](https://github.com/LYK-love/VS-Code-DevContainer-Config)",
  "label": "r/deeplearning",
  "dataType": "post",
  "communityName": "r/deeplearning",
  "datetime": "2024-04-26",
  "username_encoded": "Z0FBQUFBQm5LakwyLUxZcVlhWHBvdlByX3V3RjB0QW1NZnEwUTJjd3h5T3lPbENkWk93cWFYSTZxeXpJOGZzYVB4TUtlNjdKczd5azh1V0x3Qzk3bjZwNG03Um02a1dvOGdmQUNuM3F1cjR0YnQ2S01Jekszd0E9",
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}
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