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import argparse | |
import logging | |
import sys | |
from unittest.mock import patch | |
import run_glue_deebert | |
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow | |
logging.basicConfig(level=logging.DEBUG) | |
logger = logging.getLogger() | |
def get_setup_file(): | |
parser = argparse.ArgumentParser() | |
parser.add_argument("-f") | |
args = parser.parse_args() | |
return args.f | |
class DeeBertTests(TestCasePlus): | |
def setup(self) -> None: | |
stream_handler = logging.StreamHandler(sys.stdout) | |
logger.addHandler(stream_handler) | |
def run_and_check(self, args): | |
n_gpu = get_gpu_count() | |
if n_gpu > 1: | |
pass | |
# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560 | |
# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py" | |
# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split() | |
# cmd = [sys.executable] + distributed_args + args | |
# execute_subprocess_async(cmd, env=self.get_env()) | |
# XXX: test the results - need to save them first into .json file | |
else: | |
args.insert(0, "run_glue_deebert.py") | |
with patch.object(sys, "argv", args): | |
result = run_glue_deebert.main() | |
for value in result.values(): | |
self.assertGreaterEqual(value, 0.666) | |
def test_glue_deebert_train(self): | |
train_args = """ | |
--model_type roberta | |
--model_name_or_path roberta-base | |
--task_name MRPC | |
--do_train | |
--do_eval | |
--do_lower_case | |
--data_dir ./tests/fixtures/tests_samples/MRPC/ | |
--max_seq_length 128 | |
--per_gpu_eval_batch_size=1 | |
--per_gpu_train_batch_size=8 | |
--learning_rate 2e-4 | |
--num_train_epochs 3 | |
--overwrite_output_dir | |
--seed 42 | |
--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage | |
--plot_data_dir ./examples/deebert/results/ | |
--save_steps 0 | |
--overwrite_cache | |
--eval_after_first_stage | |
""".split() | |
self.run_and_check(train_args) | |
eval_args = """ | |
--model_type roberta | |
--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage | |
--task_name MRPC | |
--do_eval | |
--do_lower_case | |
--data_dir ./tests/fixtures/tests_samples/MRPC/ | |
--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage | |
--plot_data_dir ./examples/deebert/results/ | |
--max_seq_length 128 | |
--eval_each_highway | |
--eval_highway | |
--overwrite_cache | |
--per_gpu_eval_batch_size=1 | |
""".split() | |
self.run_and_check(eval_args) | |
entropy_eval_args = """ | |
--model_type roberta | |
--model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage | |
--task_name MRPC | |
--do_eval | |
--do_lower_case | |
--data_dir ./tests/fixtures/tests_samples/MRPC/ | |
--output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage | |
--plot_data_dir ./examples/deebert/results/ | |
--max_seq_length 128 | |
--early_exit_entropy 0.1 | |
--eval_highway | |
--overwrite_cache | |
--per_gpu_eval_batch_size=1 | |
""".split() | |
self.run_and_check(entropy_eval_args) | |