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