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test_xla_examples.py
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Wed, May 1, 21:01

test_xla_examples.py
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# coding=utf-8
# Copyright 2018 HuggingFace Inc..
#
# 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.
import logging
import sys
import unittest
from time import time
from unittest.mock import patch
from transformers.testing_utils import require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger()
@require_torch_tpu
class TorchXLAExamplesTests(unittest.TestCase):
def test_run_glue(self):
import xla_spawn
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
output_directory = "run_glue_output"
testargs = f"""
transformers/examples/text-classification/run_glue.py
--num_cores=8
transformers/examples/text-classification/run_glue.py
--do_train
--do_eval
--task_name=mrpc
--cache_dir=./cache_dir
--num_train_epochs=1
--max_seq_length=128
--learning_rate=3e-5
--output_dir={output_directory}
--overwrite_output_dir
--logging_steps=5
--save_steps=5
--overwrite_cache
--tpu_metrics_debug
--model_name_or_path=bert-base-cased
--per_device_train_batch_size=64
--per_device_eval_batch_size=64
--evaluation_strategy steps
--overwrite_cache
""".split()
with patch.object(sys, "argv", testargs):
start = time()
xla_spawn.main()
end = time()
result = {}
with open(f"{output_directory}/eval_results_mrpc.txt") as f:
lines = f.readlines()
for line in lines:
key, value = line.split(" = ")
result[key] = float(value)
del result["eval_loss"]
for value in result.values():
# Assert that the model trains
self.assertGreaterEqual(value, 0.70)
# Assert that the script takes less than 300 seconds to make sure it doesn't hang.
self.assertLess(end - start, 500)
def test_trainer_tpu(self):
import xla_spawn
testargs = """
transformers/tests/test_trainer_tpu.py
--num_cores=8
transformers/tests/test_trainer_tpu.py
""".split()
with patch.object(sys, "argv", testargs):
xla_spawn.main()

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