138 lines
4.4 KiB
Python
138 lines
4.4 KiB
Python
# coding=utf-8
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# Copyright 2018 HuggingFace Inc..
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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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import argparse
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import logging
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import os
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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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SRC_DIRS = [
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os.path.join(os.path.dirname(__file__), dirname)
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for dirname in ["text-generation", "text-classification", "language-modeling", "question-answering"]
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]
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sys.path.extend(SRC_DIRS)
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if SRC_DIRS is not None:
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import run_generation
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import run_glue
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import run_language_modeling
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import run_squad
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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 ExamplesTests(unittest.TestCase):
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def test_run_glue(self):
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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testargs = """
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run_glue.py
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--model_name_or_path bert-base-uncased
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--data_dir ./tests/fixtures/tests_samples/MRPC/
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--task_name mrpc
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--do_train
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--do_eval
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--output_dir ./tests/fixtures/tests_samples/temp_dir
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--per_gpu_train_batch_size=2
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--per_gpu_eval_batch_size=1
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--learning_rate=1e-4
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--max_steps=10
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--warmup_steps=2
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--overwrite_output_dir
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--seed=42
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--max_seq_length=128
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""".split()
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with patch.object(sys, "argv", testargs):
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result = run_glue.main()
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del result["eval_loss"]
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for value in result.values():
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self.assertGreaterEqual(value, 0.75)
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def test_run_language_modeling(self):
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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testargs = """
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run_language_modeling.py
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--model_name_or_path distilroberta-base
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--model_type roberta
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--mlm
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--line_by_line
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--train_data_file ./tests/fixtures/sample_text.txt
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--eval_data_file ./tests/fixtures/sample_text.txt
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--output_dir ./tests/fixtures/tests_samples/temp_dir
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--overwrite_output_dir
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--do_train
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--do_eval
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--num_train_epochs=1
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--no_cuda
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""".split()
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with patch.object(sys, "argv", testargs):
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result = run_language_modeling.main()
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self.assertLess(result["perplexity"], 35)
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def test_run_squad(self):
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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testargs = """
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run_squad.py
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--model_type=bert
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--model_name_or_path=bert-base-uncased
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--data_dir=./tests/fixtures/tests_samples/SQUAD
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--model_name=bert-base-uncased
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--output_dir=./tests/fixtures/tests_samples/temp_dir
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--max_steps=10
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--warmup_steps=2
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--do_train
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--do_eval
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--version_2_with_negative
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--learning_rate=2e-4
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--per_gpu_train_batch_size=2
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--per_gpu_eval_batch_size=1
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--overwrite_output_dir
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--seed=42
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""".split()
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with patch.object(sys, "argv", testargs):
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result = run_squad.main()
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self.assertGreaterEqual(result["f1"], 30)
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self.assertGreaterEqual(result["exact"], 30)
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def test_generation(self):
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stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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testargs = ["run_generation.py", "--prompt=Hello", "--length=10", "--seed=42"]
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model_type, model_name = ("--model_type=openai-gpt", "--model_name_or_path=openai-gpt")
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with patch.object(sys, "argv", testargs + [model_type, model_name]):
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result = run_generation.main()
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self.assertGreaterEqual(len(result[0]), 10)
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