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11 Commits

Author SHA1 Message Date
salman
454eea049f Merge branch 'main' into print_venv 2025-07-07 10:01:00 +01:00
NanoCode012
5a961ecadf Fix: do not call preprocess in multimodal or pretraining case (#2861)
* fix: let users know to not call preprocess for vision mode

* fix: improve ux for pretraining dataset and skip prepare ds

* feat: add info to doc

* Update src/axolotl/cli/preprocess.py following comment

Co-authored-by: salman <salman.mohammadi@outlook.com>

---------

Co-authored-by: salman <salman.mohammadi@outlook.com>
2025-07-06 21:55:33 -04:00
Wing Lian
b37ddf9778 don't use tokenizer parallelism when using packing (#2862) [skip ci] 2025-07-06 21:55:09 -04:00
Wing Lian
bf38e507fb respect shuffle_merged_datasets for single dataset too (#2866) [skip ci]
* respect shuffle_merged_datasets for single dataset too

* update inline comment for behavior

Co-authored-by: NanoCode012 <nano@axolotl.ai>

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>
2025-07-06 21:20:41 -04:00
Wing Lian
a5946ff1f0 build fa2 from source for base image with torch2.6 and cu124 (#2867) 2025-07-05 09:21:18 -04:00
Salman Mohammadi
d00bd99279 Merge branch 'print_venv' of github.com:axolotl-ai-cloud/axolotl into print_venv 2025-07-04 12:44:49 +01:00
Salman Mohammadi
2b41bfe9eb reverting 2025-07-04 12:40:58 +01:00
salman
5bbbd599b4 Merge branch 'main' into print_venv 2025-07-04 12:36:13 +01:00
Salman Mohammadi
26c782183d merging commands 2025-07-04 12:35:20 +01:00
Wing Lian
70ca1b2291 fix nightlies to use correct cache (#2848) [skip ci]
* fix nightlies to use correct cache

* fix for handling None for bf16
2025-07-03 12:21:39 -04:00
Salman Mohammadi
8065fed126 adding venv to prompt 2025-07-02 15:27:42 +01:00
10 changed files with 46 additions and 119 deletions

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@@ -5,11 +5,13 @@ on:
branches:
- "main"
paths:
- 'Dockerfile-base'
- 'docker/Dockerfile-base'
- 'docker/Dockerfile-uv-base'
- '.github/workflows/base.yml'
pull_request:
paths:
- 'Dockerfile-base'
- 'docker/Dockerfile-base'
- 'docker/Dockerfile-uv-base'
- '.github/workflows/base.yml'
workflow_dispatch:

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@@ -18,96 +18,9 @@ jobs:
env:
SKIP: no-commit-to-branch
preload-cache:
name: Preload HF cache
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python_version: ["3.11"]
pytorch_version: ["2.6.0"]
timeout-minutes: 20
env:
AXOLOTL_IS_CI_CACHE_PRELOAD: "1"
steps:
- name: Check out repository code
uses: actions/checkout@v4
- name: Restore HF cache
id: hf-cache-restore
uses: actions/cache/restore@v4
with:
path: |
/home/runner/.cache/huggingface/hub/datasets--*
/home/runner/.cache/huggingface/hub/models--*
key: ${{ runner.os }}-hf-hub-cache-v2
- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python_version }}
cache: 'pip' # caching pip dependencies
- name: upgrade pip
run: |
pip3 install --upgrade pip
pip3 install --upgrade packaging==23.2 setuptools==75.8.0 wheel
- name: Install PyTorch
run: |
pip3 install torch==${{ matrix.pytorch_version }}
- name: Install dependencies
run: |
pip3 show torch
pip3 install --no-build-isolation -U -e .
python scripts/unsloth_install.py | sh
python scripts/cutcrossentropy_install.py | sh
pip3 install -r requirements-dev.txt -r requirements-tests.txt
- name: Make sure PyTorch version wasn't clobbered
run: |
python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
- name: Ensure axolotl CLI was installed
run: |
axolotl --help
- name: Pre-Download dataset fixture
run: |
huggingface-cli download --repo-type=dataset axolotl-ai-internal/axolotl-oss-dataset-fixtures
- name: Run tests
run: |
pytest -v tests/conftest.py
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
files: ./coverage.xml
flags: unittests,pytorch-${{ matrix.pytorch_version }}
fail_ci_if_error: false
- name: cleanup pip cache
run: |
find "$(pip cache dir)/http-v2" -type f -mtime +14 -exec rm {} \;
- name: Save HF cache
id: hf-cache
uses: actions/cache/save@v4
with:
path: |
/home/runner/.cache/huggingface/hub/datasets--*
/home/runner/.cache/huggingface/hub/models--*
key: ${{ steps.hf-cache-restore.outputs.cache-primary-key }}
pytest:
name: PyTest
runs-on: ubuntu-latest
needs: [preload-cache]
strategy:
fail-fast: false
max-parallel: 2
@@ -120,14 +33,11 @@ jobs:
- name: Check out repository code
uses: actions/checkout@v4
- name: Restore HF cache
id: hf-cache-restore
uses: actions/cache/restore@v4
with:
path: |
/home/runner/.cache/huggingface/hub/datasets--*
/home/runner/.cache/huggingface/hub/models--*
key: ${{ runner.os }}-hf-hub-cache-v2
- name: Restore Cache from S3
id: hf-cache-restore-s3
run: |
mkdir -p /home/runner/.cache/huggingface/hub
curl -L https://d1dttdx32dkk5p.cloudfront.net/hf-cache.tar.zst | tar -xf - -C /home/runner/.cache/huggingface/hub/ --use-compress-program unzstd
- name: Setup Python
uses: actions/setup-python@v5
@@ -168,10 +78,6 @@ jobs:
run: |
axolotl --help
- name: Pre-Download dataset fixture
run: |
huggingface-cli download --repo-type=dataset axolotl-ai-internal/axolotl-oss-dataset-fixtures
- name: Run tests
run: |
pytest -v -n8 --dist loadfile --ignore=tests/e2e/ --ignore=tests/patched/ --ignore=tests/cli/ tests/
@@ -193,15 +99,8 @@ jobs:
fail-fast: false
matrix:
include:
- cuda: 124
cuda_version: 12.4.1
python_version: "3.11"
pytorch: 2.5.1
num_gpus: 1
axolotl_extras:
nightly_build: "true"
- cuda: 124
cuda_version: 12.4.1
- cuda: 126
cuda_version: 12.6.3
python_version: "3.11"
pytorch: 2.6.0
num_gpus: 1

View File

@@ -22,9 +22,11 @@ RUN apt-get update \
&& mkdir /root/.conda \
&& bash Miniconda3-latest-Linux-x86_64.sh -b \
&& rm -f Miniconda3-latest-Linux-x86_64.sh \
&& conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}"
&& conda create -n "axolotl-py${PYTHON_VERSION}" python="${PYTHON_VERSION}" \
&& conda init bash \
&& echo "conda activate axolotl-py${PYTHON_VERSION}" >> ~/.bashrc
ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}"
ENV PATH="/root/miniconda3/envs/axolotl-py${PYTHON_VERSION}/bin:${PATH}"
WORKDIR /workspace
@@ -37,3 +39,7 @@ RUN git lfs install --skip-repo && \
pip3 install awscli && \
# The base image ships with `pydantic==1.8.2` which is not working
pip3 install -U --no-cache-dir pydantic==1.10.10
RUN if [ "$PYTORCH_VERSION" = "2.6.0" ] && [ "$CUDA" = "124" ] ; then \
FLASH_ATTENTION_FORCE_BUILD="TRUE" pip3 install --no-build-isolation flash-attn==2.8.0.post2; \
fi

View File

@@ -22,9 +22,11 @@ RUN apt-get update \
&& mkdir /root/.conda \
&& bash Miniconda3-latest-Linux-x86_64.sh -b \
&& rm -f Miniconda3-latest-Linux-x86_64.sh \
&& conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}"
&& conda create -n "axolotl-py${PYTHON_VERSION}" python="${PYTHON_VERSION}" \
&& conda init bash \
&& echo "conda activate axolotl-py${PYTHON_VERSION}" >> ~/.bashrc
ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}"
ENV PATH="/root/miniconda3/envs/axolotl-py${PYTHON_VERSION}/bin:${PATH}"
WORKDIR /workspace

View File

@@ -22,9 +22,11 @@ RUN apt-get update \
&& mkdir /root/.conda \
&& bash Miniconda3-latest-Linux-x86_64.sh -b \
&& rm -f Miniconda3-latest-Linux-x86_64.sh \
&& conda create -n "py${PYTHON_VERSION}" python="${PYTHON_VERSION}"
&& conda create -n "axolotl-py${PYTHON_VERSION}" python="${PYTHON_VERSION}" \
&& conda init bash \
&& echo "conda activate axolotl-py${PYTHON_VERSION}" >> ~/.bashrc
ENV PATH="/root/miniconda3/envs/py${PYTHON_VERSION}/bin:${PATH}"
ENV PATH="/root/miniconda3/envs/axolotl-py${PYTHON_VERSION}/bin:${PATH}"
WORKDIR /workspace

View File

@@ -51,6 +51,10 @@ description: Frequently asked questions
> pad_token: "..."
> ```
**Q: `IterableDataset error` or `KeyError: 'input_ids'` when using `preprocess` CLI**
> A: This is because you may be using `preprocess` CLI with `pretraining_dataset:` or `skip_prepare_dataset: true` respectively. Please use `axolotl train` CLI directly instead as these datasets are prepared on demand.
### Chat templates
**Q: `jinja2.exceptions.UndefinedError: 'dict object' has no attribute 'content' / 'role' / ____`**

View File

@@ -35,6 +35,12 @@ def do_preprocess(cfg: DictDefault, cli_args: PreprocessCliArgs) -> None:
check_accelerate_default_config()
check_user_token()
for key in ["skip_prepare_dataset", "pretraining_dataset"]:
if cfg.get("key"):
raise ValueError(
f"You have set `{key}:`. `preprocess` is not needed. Run the `axolotl train` CLI directly instead."
)
if not cfg.dataset_prepared_path:
msg = (
Fore.RED

View File

@@ -219,7 +219,9 @@ class TrainerBuilderBase(abc.ABC):
if self.cfg.bf16 == "full":
training_args_kwargs["bf16_full_eval"] = True
else:
training_args_kwargs["bf16"] = self.cfg.bf16 or self.cfg.bfloat16
bf16 = self.cfg.bf16 or self.cfg.bfloat16
bf16 = bf16 if bf16 is not None else False
training_args_kwargs["bf16"] = bf16
def _configure_scheduler(self, training_args_kwargs: dict):
if self.cfg.lr_scheduler in ["one_cycle", "rex"]:

View File

@@ -526,8 +526,9 @@ def merge_datasets(datasets: list[Dataset], cfg: DictDefault) -> Dataset:
if len(datasets) == 1:
ds = datasets[0]
# Do not shuffle if curriculum sampling is enabled
if cfg.curriculum_sampling:
# Do not shuffle if curriculum sampling is enabled or
# shuffle_merged_datasets is disabled
if cfg.curriculum_sampling or not cfg.shuffle_merged_datasets:
return ds
return ds.shuffle(seed=cfg.seed)

View File

@@ -609,6 +609,9 @@ def prepare_opinionated_env(cfg):
if cfg.qlora_sharded_model_loading:
# model loading is forked after the tokenizer
os.environ["TOKENIZERS_PARALLELISM"] = "false"
if cfg.sample_packing:
# multipack parallel packing sampler defaults to using fork
os.environ["TOKENIZERS_PARALLELISM"] = "false"
def setup_trainer(