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* Reorganize example folder * Continue reorganization * Change requirements for tests * Final cleanup * Finish regroup with tests all passing * Copyright * Requirements and readme * Make a full link for the documentation * Address review comments * Apply suggestions from code review Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Add symlink * Reorg again * Apply suggestions from code review Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com> * Adapt title * Update to new strucutre * Remove test * Update READMEs Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
import argparse
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import logging
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import sys
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import unittest
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from unittest.mock import patch
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import run_glue_deebert
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from transformers.testing_utils import require_torch_non_multi_gpu_but_fix_me, slow
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger()
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def get_setup_file():
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parser = argparse.ArgumentParser()
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parser.add_argument("-f")
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args = parser.parse_args()
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return args.f
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class DeeBertTests(unittest.TestCase):
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def setup(self) -> None:
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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@slow
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@require_torch_non_multi_gpu_but_fix_me
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def test_glue_deebert_train(self):
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train_args = """
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run_glue_deebert.py
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--model_type roberta
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--model_name_or_path roberta-base
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--task_name MRPC
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--do_train
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--do_eval
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--do_lower_case
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--data_dir ./tests/fixtures/tests_samples/MRPC/
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--max_seq_length 128
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--per_gpu_eval_batch_size=1
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--per_gpu_train_batch_size=8
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--learning_rate 2e-4
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--num_train_epochs 3
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--overwrite_output_dir
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--seed 42
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--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
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--plot_data_dir ./examples/deebert/results/
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--save_steps 0
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--overwrite_cache
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--eval_after_first_stage
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""".split()
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with patch.object(sys, "argv", train_args):
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result = run_glue_deebert.main()
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for value in result.values():
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self.assertGreaterEqual(value, 0.666)
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eval_args = """
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run_glue_deebert.py
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--model_type roberta
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--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
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--task_name MRPC
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--do_eval
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--do_lower_case
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--data_dir ./tests/fixtures/tests_samples/MRPC/
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--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
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--plot_data_dir ./examples/deebert/results/
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--max_seq_length 128
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--eval_each_highway
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--eval_highway
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--overwrite_cache
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--per_gpu_eval_batch_size=1
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""".split()
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with patch.object(sys, "argv", eval_args):
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result = run_glue_deebert.main()
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for value in result.values():
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self.assertGreaterEqual(value, 0.666)
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entropy_eval_args = """
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run_glue_deebert.py
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--model_type roberta
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--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
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--task_name MRPC
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--do_eval
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--do_lower_case
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--data_dir ./tests/fixtures/tests_samples/MRPC/
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--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
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--plot_data_dir ./examples/deebert/results/
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--max_seq_length 128
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--early_exit_entropy 0.1
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--eval_highway
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--overwrite_cache
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--per_gpu_eval_batch_size=1
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""".split()
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with patch.object(sys, "argv", entropy_eval_args):
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result = run_glue_deebert.main()
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for value in result.values():
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self.assertGreaterEqual(value, 0.666)
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