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Bump Anndata version #521

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Bump Anndata version

Bump Anndata version #521

Workflow file for this run

.github/workflows/main.yml at 4da238c
name: CI Pipeline
on:
pull_request:
branches:
- main
jobs:
tests:
runs-on: self-hosted
steps:
- name: Checkout repository
uses: actions/checkout@v2
- name: setup python
uses: actions/setup-python@v5
with:
python-version: 3.11.8
- name: Install dependencies
run: |
pip install -r requirements-dev.txt
pip install .[mamba-ssm]
# First download before tests as they make use of the downloaded files
- name: Download all files
run: |
python ci/download_all.py
- name: Execute unittests
run: |
CUDA_VISIBLE_DEVICES=-1 pytest --cov-report=html:html_cov --cov-branch --cov-report term --cov=helical ci/
- name: Upload coverage report
uses: actions/upload-artifact@v4
with:
name: coverage-report
path: html_cov/
integration-tests:
needs: tests
runs-on: self-hosted
env:
CUDA_VISIBLE_DEVICES: 0
steps:
- name: Checkout repository
uses: actions/checkout@v2
- name: setup python
uses: actions/setup-python@v5
with:
python-version: 3.11.8
# because jobs may not be run in the same order, we need to install the dependencies again
- name: Install helical
run: |
pip install .[mamba-ssm]
# Required to get the data
- name: Download all files
run: |
python ci/download_all.py
- name: Execute Geneformer v1
run: |
python examples/run_models/run_geneformer.py ++model_name="gf-12L-30M-i2048" ++device="cuda"
- name: Fine-tune Geneformer v1
run: |
python examples/fine_tune_models/fine_tune_geneformer.py ++model_name="gf-12L-30M-i2048" ++device="cuda"
- name: Execute Geneformer v2
run: |
python examples/run_models/run_geneformer.py ++model_name="gf-12L-95M-i4096" ++device="cuda"
- name: Fine-tune Geneformer v2
run: |
python examples/fine_tune_models/fine_tune_geneformer.py ++model_name="gf-12L-30M-i2048" ++device="cuda"
- name: Execute scGPT
run: |
python examples/run_models/run_scgpt.py ++device="cuda"
- name: Fine-tune scGPT
run: |
python examples/fine_tune_models/fine_tune_scgpt.py ++device="cuda"
- name: Execute UCE
run: |
python examples/run_models/run_uce.py ++device="cuda"
- name: Fine-tune UCE
run: |
python examples/fine_tune_models/fine_tune_UCE.py ++device="cuda"
- name: Execute Hyena
run: |
python examples/run_models/run_hyena_dna.py ++device="cuda"
- name: Execute Hyena
run: |
python examples/fine_tune_models/fine_tune_hyena_dna.py ++device="cuda"
- name: Execute Helix-mRNA
run: |
python examples/run_models/run_helix_mrna.py ++device="cuda"
- name: Fine-tune Helix-mRNA
run: |
python examples/fine_tune_models/fine_tune_helix_mrna.py ++device="cuda"
- name: Execute Mamba2-mRNA
run: |
python examples/run_models/run_mamba2_mrna.py ++device="cuda"
- name: Fine-tune Mamba2-mRNA
run: |
python examples/fine_tune_models/fine_tune_mamba2_mrna.py ++device="cuda"
- name: Execute Caduceus
run: |
python examples/run_models/run_caduceus.py
- name: Fine-tune Caduceus
run: |
python examples/fine_tune_models/fine_tune_caduceus.py
notebooks:
needs: tests
runs-on: self-hosted
env:
CUDA_VISIBLE_DEVICES: 0
steps:
- name: Checkout repository
uses: actions/checkout@v2
- name: setup python
uses: actions/setup-python@v5
with:
python-version: 3.11.8
# because jobs may not be run in the same order, we need to install the dependencies again
- name: Install helical
run: |
pip install .[mamba-ssm]
- name: Reduce datasets to speedup checks
run: |
sed -i 's/train\[:65%\]/train\[:5%\]/g' ./examples/notebooks/Cell-Type-Annotation.ipynb
sed -i 's/train\[70%:\]/train\[5%:7%\]/g' ./examples/notebooks/Cell-Type-Annotation.ipynb
sed -i 's/get_anndata_from_hf_dataset(ds\[\\"train\\"\])/get_anndata_from_hf_dataset(ds\[\\"train\\"\])[:100]/g' ./examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb
sed -i 's/get_anndata_from_hf_dataset(ds\[\\"test\\"\])/get_anndata_from_hf_dataset(ds\[\\"test\\"\])[:10]/g' ./examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb
sed -i 's/list(np.array(train_dataset.obs\[\\"LVL1\\"].tolist()))/list(np.array(train_dataset.obs\[\\"LVL1\\"].tolist()))[:100]/g' ./examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb
sed -i 's/list(np.array(test_dataset.obs\[\\"LVL1\\"].tolist()))/list(np.array(test_dataset.obs\[\\"LVL1\\"].tolist()))[:10]/g' ./examples/notebooks/Cell-Type-Classification-Fine-Tuning.ipynb
- name: Run Notebooks
run: |
pytest --durations=0 --nbmake ./examples/notebooks/*.ipynb