9de5b76336
* feat: move to uv first * fix: update doc to uv first * fix: merge dev/tests into uv pyproject * fix: update docker docs to match current config * fix: migrate examples to readme * fix: add llmcompressor to conflict * feat: rec uv sync with lockfile for dev/ci * fix: update docker docs to clarify how to use uv images * chore: docs * fix: use system python, no venv * fix: set backend cpu * fix: only set for installing pytorch step * fix: remove unsloth kernel and installs * fix: remove U in tests * fix: set backend in deps too * chore: test * chore: comments * fix: attempt to lock torch * fix: workaround torch cuda and not upgraded * fix: forgot to push * fix: missed source * fix: nightly upstream loralinear config * fix: nightly phi3 long rope not work * fix: forgot commit * fix: test phi3 template change * fix: no more requirements * fix: carry over changes from new requirements to pyproject * chore: remove lockfile per discussion * fix: set match-runtime * fix: remove unneeded hf hub buildtime * fix: duplicate cache delete on nightly * fix: torchvision being overridden * fix: migrate to uv images * fix: leftover from merge * fix: simplify base readme * fix: update assertion message to be clearer * chore: docs * fix: change fallback for cicd script * fix: match against main exactly * fix: peft 0.19.1 change * fix: e2e test * fix: ci * fix: e2e test
74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
"""Modal app to run axolotl GPU tests"""
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import os
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import pathlib
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import tempfile
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import jinja2
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import modal
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import modal.experimental
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from jinja2 import select_autoescape
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from modal import App
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cicd_path = pathlib.Path(__file__).parent.resolve()
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template_loader = jinja2.FileSystemLoader(searchpath=cicd_path)
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template_env = jinja2.Environment(
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loader=template_loader, autoescape=select_autoescape()
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)
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dockerfile = os.environ.get("E2E_DOCKERFILE", "Dockerfile-uv.jinja")
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df_template = template_env.get_template(dockerfile)
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df_args = {
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"AXOLOTL_EXTRAS": os.environ.get("AXOLOTL_EXTRAS", ""),
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"AXOLOTL_ARGS": os.environ.get("AXOLOTL_ARGS", ""),
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"PYTORCH_VERSION": os.environ.get("PYTORCH_VERSION", "2.6.0"),
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"BASE_TAG": os.environ.get("BASE_TAG", "main-base-py3.11-cu126-2.6.0"),
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"CUDA": os.environ.get("CUDA", "126"),
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"GITHUB_REF": os.environ.get("GITHUB_REF", "refs/heads/main"),
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"GITHUB_SHA": os.environ.get("GITHUB_SHA", ""),
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"NIGHTLY_BUILD": os.environ.get("NIGHTLY_BUILD", ""),
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"CODECOV_TOKEN": os.environ.get("CODECOV_TOKEN", ""),
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"HF_HOME": "/workspace/data/huggingface-cache/hub",
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"PYTHONUNBUFFERED": os.environ.get("PYTHONUNBUFFERED", "1"),
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"DEEPSPEED_LOG_LEVEL": os.environ.get("DEEPSPEED_LOG_LEVEL", "WARNING"),
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}
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dockerfile_contents = df_template.render(**df_args)
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temp_dir = tempfile.mkdtemp()
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with open(pathlib.Path(temp_dir) / "Dockerfile", "w", encoding="utf-8") as f:
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f.write(dockerfile_contents)
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cicd_image = modal.experimental.raw_dockerfile_image(
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pathlib.Path(temp_dir) / "Dockerfile",
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# context_mount=None,
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force_build=True,
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# gpu="A10G",
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).env(df_args)
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app = App("Axolotl CI/CD", secrets=[])
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hf_cache_volume = modal.Volume.from_name(
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"axolotl-ci-hf-hub-cache", create_if_missing=True
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)
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VOLUME_CONFIG = {
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"/workspace/data/huggingface-cache/hub": hf_cache_volume,
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}
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N_GPUS = int(os.environ.get("N_GPUS", 1))
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GPU_TYPE = os.environ.get("GPU_TYPE", "L40S")
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GPU_CONFIG = f"{GPU_TYPE}:{N_GPUS}"
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def run_cmd(cmd: str, run_folder: str):
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import subprocess # nosec
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sp_env = os.environ.copy()
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sp_env["AXOLOTL_DATASET_NUM_PROC"] = "8"
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# Propagate errors from subprocess.
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exit_code = subprocess.call(cmd.split(), cwd=run_folder, env=sp_env) # nosec
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if exit_code:
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raise RuntimeError(f"Command '{cmd}' failed with exit code {exit_code}")
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