Various fixes for CI, save_only_model for RL, prevent packing multiprocessing deadlocks (#2661)
* lean mistral ft tests, remove e2e torch 2.4.1 test * make sure to pass save_only_model for RL * more tests to make ci leaner, add cleanup to modal ci * fix module for import in e2e tests * use mp spawn to prevent deadlocks with packing * make sure cleanup shell script is executable when cloned out
This commit is contained in:
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cicd/__init__.py
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0
cicd/__init__.py
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@@ -18,7 +18,7 @@ pytest -v --durations=10 \
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--cov-append
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# Run patched tests excluding lora kernels with coverage append
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pytest -v --durations=10 \
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pytest --full-trace -vvv --durations=10 \
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--ignore=tests/e2e/patched/lora_kernels \
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/workspace/axolotl/tests/e2e/patched \
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--cov=axolotl \
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cicd/cleanup.py
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cicd/cleanup.py
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@@ -0,0 +1,19 @@
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"""Modal app to run axolotl GPU cleanup"""
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from .single_gpu import VOLUME_CONFIG, app, cicd_image, run_cmd
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@app.function(
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image=cicd_image,
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timeout=60 * 60,
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cpu=8.0,
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memory=131072,
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volumes=VOLUME_CONFIG,
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)
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def cleanup():
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run_cmd("./cicd/cleanup.sh", "/workspace/axolotl")
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@app.local_entrypoint()
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def main():
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cleanup.remote()
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6
cicd/cleanup.sh
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cicd/cleanup.sh
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@@ -0,0 +1,6 @@
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#!/bin/bash
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set -e
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# cleanup old cache files for datasets processing and intermediate mappings
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find /workspace/data/huggingface-cache/hub/datasets -name "cache-*" -type f -mtime +1 -exec rm {} \;
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find /workspace/data/huggingface-cache/hub/datasets -name "*.lock" -type f -mtime +1 -exec rm {} \;
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@@ -1,69 +1,6 @@
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"""Modal app to run axolotl GPU tests"""
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# pylint: disable=duplicate-code
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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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from jinja2 import select_autoescape
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from modal import App, Image
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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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df_template = template_env.get_template("Dockerfile.jinja")
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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", "2.4.1"),
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"BASE_TAG": os.environ.get("BASE_TAG", "main-base-py3.11-cu121-2.4.1"),
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"CUDA": os.environ.get("CUDA", "121"),
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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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}
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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 = Image.from_dockerfile(
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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_CONFIG = modal.gpu.L40S(count=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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# Propagate errors from subprocess.
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if exit_code := subprocess.call(cmd.split(), cwd=run_folder): # nosec
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exit(exit_code) # pylint: disable=consider-using-sys-exit
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from .single_gpu import GPU_CONFIG, VOLUME_CONFIG, app, cicd_image, run_cmd
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@app.function(
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66
cicd/single_gpu.py
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cicd/single_gpu.py
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@@ -0,0 +1,66 @@
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"""Modal app to run axolotl GPU tests"""
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# pylint: disable=duplicate-code
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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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from jinja2 import select_autoescape
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from modal import App, Image
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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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df_template = template_env.get_template("Dockerfile.jinja")
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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", "2.4.1"),
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"BASE_TAG": os.environ.get("BASE_TAG", "main-base-py3.11-cu121-2.4.1"),
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"CUDA": os.environ.get("CUDA", "121"),
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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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}
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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 = Image.from_dockerfile(
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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_CONFIG = modal.gpu.L40S(count=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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# Propagate errors from subprocess.
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if exit_code := subprocess.call(cmd.split(), cwd=run_folder): # nosec
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exit(exit_code) # pylint: disable=consider-using-sys-exit
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