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Merge pull request #366 from coding-for-reproducible-research/fix_gpu
Add workshop info page to gpu course
2 parents 34f3971 + 03d1a1f commit 068f413

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_toc.yml

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sections:
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- file: programme_information/intro_to_version_control
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- file: programme_information/intermediate_version_control
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- file: programme_information/gpus
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sections:
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- file: programme_information/intro_to_gpus
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- file: cfrr_program_details/course_feedback
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- caption: What Courses Should I Take?

data/workshop_info.csv

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@@ -17,4 +17,5 @@ Introduction to Machine Learning,03/12/2024,27/02/2025,7th/14th/21st March 2025
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Improve your R Code,19/02/2025,22/04/2025,29th April 2025 10am-1pm,https://forms.office.com/e/bUXinqvWja,In-person only,https://coding-for-reproducible-research.github.io/CfRR_Courses/programme_information/improve_your_r_code.html
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Introduction to Markdown in R,19/02/2025,05/06/2025,6th June 2025 10am-1pm,https://forms.office.com/e/8diVktHHzt,In-person only,https://coding-for-reproducible-research.github.io/CfRR_Courses/programme_information/Introduction_to_Markdown_in_R.html
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Using Markdown for Python,19/02/2025,09/06/2025,10th June 2025 10am-1pm,https://forms.office.com/e/5ixSXnxdHb,In-person only,https://coding-for-reproducible-research.github.io/CfRR_Courses/programme_information/markdown_with_python.html
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Mixed Effects Regression with R,,,,,,
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Mixed Effects Regression with R,,,,,,
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Introduction to GPUs,,,,,,
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### Instructional Material
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The instructional material in this course is copyright © 2025 University of Exeter
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and is made available under the Creative Commons Attribution 4.0 International
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licence (https://creativecommons.org/licenses/by/4.0/). Instructional material
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consists of material that is contained within the "individual_modules/python_for_data_analysis" directory, and images folders in
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this directory, with the exception of code snippets and example programs found
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in files within these folders. Such code snippets and example programs are
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considered software for the purposes of this licence.
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### Software
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Except where otherwise noted, software provided in this repository is made
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available under the MIT licence (https://opensource.org/licenses/MIT).
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Copyright © 2025 University of Exeter
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

individual_modules/intro_to_GPUs/conways_game_of_life.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.2"
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"version": "3.9.19"
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}
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},
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"nbformat": 4,

individual_modules/intro_to_GPUs/setup.md

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5. Add a new SSH configuration to the file, specifying the remote machine’s details. Here’s an example configuration:
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```ssh-config
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```
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Host my-remote-machine
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HostName <remote-ip-or-hostname>
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User <your-username>

individual_modules/intro_to_GPUs/theory.ipynb

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"\n",
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"```{figure} figures/gpu_for_graphics.png\n",
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":alt: A graphics card powering 3D rendering on a computer display.\n",
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":name: fig-gpu\n",
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":name: fig-gpu-graphics\n",
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":width: 500px\n",
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":align: center\n",
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"\n",
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"\n",
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"```{figure} figures/gpu_2048_regions.png\n",
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":alt: A computer monitor showing an image of a sunset divided into many small grid regions, representing how a GPU processes tasks in thousands of parallel chunks.\n",
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":name: fig-gpu\n",
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":name: fig-gpu-2048-regions\n",
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":width: 500px\n",
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":align: center\n",
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"\n",
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"\n",
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"```{figure} figures/cpu_4_regions.png\n",
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":alt: A computer monitor showing an image of a sunset divided into four large regions, representing how a CPU processes tasks in fewer, larger chunks.\n",
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":name: fig-gpu\n",
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":name: fig-gpu-4-regions\n",
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":width: 500px\n",
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":align: center\n",
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"\n",
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"\n",
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"```{figure} figures/cpu_architecture.png\n",
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":alt: Illustration of a CPU with four cores, each core handling one task, showing limited parallel task execution.\n",
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":name: fig-gpu\n",
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":name: fig-cpu-architecture\n",
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":width: 500px\n",
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":align: center\n",
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"\n",
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"\n",
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"```{figure} figures/gpu_architecture.png\n",
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":alt: Illustration of a GPU with many small cores, each working on parts of multiple tasks simultaneously, showing massive parallelism.\n",
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":name: fig-gpu\n",
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":name: fig-gpu-architecture\n",
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":width: 500px\n",
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":align: center\n",
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"\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.2"
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"version": "3.9.19"
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}
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},
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"nbformat": 4,
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### Instructional Material
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The instructional material in this course is copyright © 2024 University of Exeter
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The instructional material in this course is copyright © 2025 University of Exeter
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and is made available under the Creative Commons Attribution 4.0 International
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licence (https://creativecommons.org/licenses/by/4.0/). Instructional material
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consists of material that is contained within the "individual_modules/introduction_to_julia" directory, and images folders in
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consists of material that is contained within the "individual_modules/python_for_data_analysis" directory, and images folders in
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this directory, with the exception of code snippets and example programs found
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in files within these folders. Such code snippets and example programs are
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considered software for the purposes of this licence.
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Except where otherwise noted, software provided in this repository is made
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available under the MIT licence (https://opensource.org/licenses/MIT).
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Copyright © 2024 University of Exeter
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Copyright © 2025 University of Exeter
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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The software in this repository is adapted from software that is covered by the
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following copyright and permission notice:
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Copyright © 2024 Software Carpentry
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Permission is hereby granted, free of charge, to any person obtaining
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a copy of this software and associated documentation files (the
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"Software"), to deal in the Software without restriction, including
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without limitation the rights to use, copy, modify, merge, publish,
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distribute, sublicense, and/or sell copies of the Software, and to
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permit persons to whom the Software is furnished to do so, subject to
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the following conditions:
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The above copyright notice and this permission notice shall be
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included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
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LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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SOFTWARE.

programme_information/gpus.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "c6492f92-e51d-4133-b27a-8b702f3411f0",
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"metadata": {},
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"source": [
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"# GPUs\n",
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"\n",
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"Currently there is only a single GPU course avaiable as self-study materials: \n",
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"- **Introduction to GPUs**: Introduction to GPUs introduces the fundamentals of GPU computing for scientific and technical applications. The course covers GPU architectures, running code on modern accelerators, and managing environments on HPC systems. With a focus on optimisation and performance, participants will gain hands-on experience through guided exercises and projects in numerical modelling and simulation."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e24bab45-4d69-4c0f-8459-9bda6574223e",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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