Training Workflow #131

	name: NVIDIA PyTorch Job

	on:
	workflow_dispatch:
	inputs:
	script_content:
	description: 'Content of Python script'
	required: true
	type: string
	filename:
	description: 'Name of Python script'
	required: true
	type: string

	jobs:
	train:
	runs-on: [gpumode-nvidia-arc]
	container:
	image: nvidia/cuda:12.4.0-devel-ubuntu22.04
	steps:
	- name: Setup Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.10'

	- name: Create script
	shell: python
	run: \|
	with open('${{ github.event.inputs.filename }}', 'w') as f:
	f.write('''${{ github.event.inputs.script_content }}''')

	- name: Install dependencies
	run: \|
	if grep -rE "(import numpy\|from numpy)" "${{ github.event.inputs.filename }}"; then
	echo "Numpy detected, installing numpy"
	pip install numpy
	fi
	# Check if 'import torch' is in any Python file
	if grep -rE "(import torch\|from torch)" "${{ github.event.inputs.filename }}"; then
	echo "PyTorch detected, installing torch"
	pip install torch
	fi
	# Check if 'import triton' is in any Python file
	if grep -rE "(import triton\|from triton)" "${{ github.event.inputs.filename }}"; then
	echo "Triton detected, installing triton"
	pip install triton
	fi

	- name: Run script
	run: \|
	python "${{ github.event.inputs.filename }}" > training.log 2>&1

	- name: Upload artifacts
	uses: actions/upload-artifact@v3
	if: always()
	with:
	name: training-artifacts
	path: \|
	training.log
	${{ github.event.inputs.filename }}
	env:
	CUDA_VISIBLE_DEVICES: 0 # Make sure only one GPU is used for testing

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