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changed training

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Malte Grosse 2024-05-03 11:44:41 +09:00
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@ -4,12 +4,12 @@ This documentation is for advanced users which are aware of following tools: git
## Overview ## Overview
Available are two worker agents with Available are two worker agents with
- 12 CPUs - 12 physical CPUs
- 40 GB memory - 40 GB memory
- 20 GB Nvidia GPU memory - 20 GB Nvidia GPU memory
- 100 GB Hdd Diskspace - 100 GB Hdd Diskspace
Only two pipelines can run in parallel to ensure having the promised hardware resources. If more jobs occur, they will be stored in a queue and released after the fifo principle. Only two pipelines can run in parallel to ensure having the promised hardware resources. If more jobs occur, they will be stored in a queue and released after the fifo principle. Storage is not persistent - every build/training job needs to saved somewhere external.
## Development ## Development
@ -58,7 +58,7 @@ steps:
``` ```
See the official [documentation](https://woodpecker-ci.org/docs/usage/workflow-syntax) for the syntax. See the official [documentation](https://woodpecker-ci.org/docs/usage/workflow-syntax) for the syntax.
Generally, the pipeline is based on different steps, and in each step, another container environment can be chosen. In the example above, first an official tensorflow container with python 3 is used to run the training python script. In the second step, the model gets compressed and pushed on the temp sandbox storage. Generally, the pipeline is based on different steps, and in each step, another container environment can be chosen. In the example above, first an official tensorflow container with python 3 is used to run the training python script. In the second step, the model gets compressed and pushed on the temp. sandbox storage.
3. Commit and push 3. Commit and push
4. See current state of the pipelines at the [overview site](https://ci.sandbox.iuk.hdm-stuttgart.de/repos) 4. See current state of the pipelines at the [overview site](https://ci.sandbox.iuk.hdm-stuttgart.de/repos)