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Copy file name to clipboardexpand all lines: python/README.md
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# Intel® Distribution for Python
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# Intel® Distribution for Python*
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[Intel® Distribution for Python] enhances performance and can improve your program speed from 10 to 100 times faster. It is a Python distribution that includes the [Intel® Math Kernel Library] (oneMKL) and other Intel performance libraries to enable near-native performance through acceleration of core numerical and machine learning packages.
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[Intel® Distribution for Python] is available as part of the [Intel® oneAPI Base Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/base-toolkit.html).
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[Intel® Distribution for Python*] enhances performance and can improve your program speed from 10 to 100 times faster. It is a Python* distribution that includes the [Intel® Math Kernel Library] (oneMKL) and other Intel performance libraries to enable near-native performance through acceleration of core numerical and machine learning packages.
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## Images
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The images below include variations for only the core packages in the [Intel® Distribution for Python] installation, or all of the packages.
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The images below include variations for only the core packages in the [Intel® Distribution for Python*] installation, or all of the packages.
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| Tag(s) | IDP |
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| ---------------------- | ---------- |
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|`3.10-full`, `latest`|`2024.2.0`|
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|`3.10-core`|`2024.2.0`|
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## Build from Source
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## Run a Performance Sample
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To run a performance sample run the following commands:
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```bash
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git clone https://github.com/intel/ai-containers
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cd ai-containers/python
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docker run --rm -it \
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-v $PWD/tests:/tests \
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intel/python:latest \
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python /tests/perf_sample.py
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```
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### Compare the results against stock python
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In the previous command, you should see a result at the bottom like: `Time Consuming: 0.03897857666015625`. We can compare this against `python:3.11-slim-bullseye`
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```bash
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# Use the working directory from the above command
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docker run --rm -it \
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-v $PWD/tests:/tests \
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python:3.11-slim-bullseye \
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bash
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pip install numpy
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python /tests/perf_sample.py
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```
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## Build from Source (Advanced)
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To build the images from source, clone the [AI Containers](https://github.com/intel/ai-containers) repository, follow the main `README.md` file to setup your environment, and run the following command:
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@@ -27,8 +52,8 @@ You can find the list of services below for each container in the group:
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