transformers/utils/split_model_tests.py

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# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This script is used to get the list of folders under `tests/models` and split the list into `NUM_SLICES` splits.
The main use case is a GitHub Actions workflow file calling this script to get the (nested) list of folders allowing it
to split the list of jobs to run into multiple slices each containing a smaller number of jobs. This way, we can bypass
the maximum of 256 jobs in a matrix.
See the `setup` and `run_models_gpu` jobs defined in the workflow file `.github/workflows/self-scheduled.yml` for more
details.
Usage:
This script is required to be run under `tests` folder of `transformers` root directory.
Assume we are under `transformers` root directory:
```bash
cd tests
python ../utils/split_model_tests.py --num_splits 64
```
"""
import argparse
import os
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--num_splits",
type=int,
default=1,
help="the number of splits into which the (flat) list of folders will be split.",
)
args = parser.parse_args()
tests = os.getcwd()
model_tests = os.listdir(os.path.join(tests, "models"))
d1 = sorted(filter(os.path.isdir, os.listdir(tests)))
d2 = sorted(filter(os.path.isdir, [f"models/{x}" for x in model_tests]))
d1.remove("models")
d = d2 + d1
num_jobs = len(d)
num_jobs_per_splits = num_jobs // args.num_splits
model_splits = []
end = 0
for idx in range(args.num_splits):
start = end
end = start + num_jobs_per_splits + (1 if idx < num_jobs % args.num_splits else 0)
model_splits.append(d[start:end])
print(model_splits)