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1st try on restore bert's cache during testing

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Orion-Zheng 2023-10-26 10:49:47 +08:00 committed by Zian(Andy) Zheng
parent 65f8d8b5bb
commit 8b1b237a5f
2 changed files with 7 additions and 9 deletions
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14
.github/workflows/example_check_on_schedule.yml vendored
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@ -65,19 +65,17 @@ jobs:
- name: Install Colossal-AI - name: Install Colossal-AI
run: | run: |
CUDA_EXT=1 pip install -v . CUDA_EXT=1 pip install -v .
- name: Restore huggingface cache
run: |
example_dir=${{ matrix.directory }}
if [[ $example_dir == *language/bert* ]]; then
echo "restore Bert weights"
cp -p -r /home/lcsoftware/gitact/actions-runner/_work/_temp/_github_home/hf_cache "${PWD}/examples/${example_dir}"
fi
- name: Traverse all files - name: Traverse all files
run: | run: |
example_dir=${{ matrix.directory }} example_dir=${{ matrix.directory }}
echo "Testing ${example_dir} now" echo "Testing ${example_dir} now"
if [[ $example_dir == *language/bert* ]]; then
echo "restore Bert weights to ${PWD}/examples/${example_dir}"
cp -p -r /home/lcsoftware/gitact/actions-runner/_work/_temp/_github_home/hf_cache "${PWD}/examples/${example_dir}"
ls -A ${PWD}/examples/${example_dir} | grep *bert-base*
fi
cd "${PWD}/examples/${example_dir}" cd "${PWD}/examples/${example_dir}"
ls -A | grep *bert-base*
bash test_ci.sh bash test_ci.sh
env: env:
NCCL_SHM_DISABLE: 1 NCCL_SHM_DISABLE: 1

2
examples/language/bert/finetune.py
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@ -248,7 +248,7 @@ def main():
cfg = AutoConfig.from_pretrained(model_name, num_labels=data_builder.num_labels) cfg = AutoConfig.from_pretrained(model_name, num_labels=data_builder.num_labels)
if model_name == "bert-base-uncased": if model_name == "bert-base-uncased":
model = BertForSequenceClassification.from_pretrained(model_name, config=cfg).cuda() model = BertForSequenceClassification.from_pretrained(model_name, config=cfg, cache_dir="./").cuda()
elif model_name == "albert-xxlarge-v2": elif model_name == "albert-xxlarge-v2":
model = AlbertForSequenceClassification.from_pretrained(model_name, config=cfg) model = AlbertForSequenceClassification.from_pretrained(model_name, config=cfg)
else: else: