huggingface-transformers/examples/test_examples.py

138 строки
4.5 KiB
Python

# 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 argparse
import logging
import os
import sys
import unittest
from unittest.mock import patch
SRC_DIRS = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in ["text-generation", "text-classification", "language-modeling", "question-answering"]
]
sys.path.extend(SRC_DIRS)
if SRC_DIRS is not None:
import run_generation
import run_glue
import run_language_modeling
import run_squad
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 ExamplesTests(unittest.TestCase):
def test_run_glue(self):
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
testargs = """
run_glue.py
--model_name_or_path distilbert-base-uncased
--data_dir ./tests/fixtures/tests_samples/MRPC/
--task_name mrpc
--do_train
--do_eval
--output_dir ./tests/fixtures/tests_samples/temp_dir
--per_device_train_batch_size=2
--per_device_eval_batch_size=1
--learning_rate=1e-4
--max_steps=10
--warmup_steps=2
--overwrite_output_dir
--seed=42
--max_seq_length=128
""".split()
with patch.object(sys, "argv", testargs):
result = run_glue.main()
del result["eval_loss"]
for value in result.values():
self.assertGreaterEqual(value, 0.75)
def test_run_language_modeling(self):
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
# TODO: switch to smaller model like sshleifer/tiny-distilroberta-base
testargs = """
run_language_modeling.py
--model_name_or_path distilroberta-base
--model_type roberta
--mlm
--line_by_line
--train_data_file ./tests/fixtures/sample_text.txt
--eval_data_file ./tests/fixtures/sample_text.txt
--output_dir ./tests/fixtures/tests_samples/temp_dir
--overwrite_output_dir
--do_train
--do_eval
--num_train_epochs=1
--no_cuda
""".split()
with patch.object(sys, "argv", testargs):
result = run_language_modeling.main()
self.assertLess(result["perplexity"], 35)
def test_run_squad(self):
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
testargs = """
run_squad.py
--model_type=distilbert
--model_name_or_path=sshleifer/tiny-distilbert-base-cased-distilled-squad
--data_dir=./tests/fixtures/tests_samples/SQUAD
--output_dir=./tests/fixtures/tests_samples/temp_dir
--max_steps=10
--warmup_steps=2
--do_train
--do_eval
--version_2_with_negative
--learning_rate=2e-4
--per_gpu_train_batch_size=2
--per_gpu_eval_batch_size=1
--overwrite_output_dir
--seed=42
""".split()
with patch.object(sys, "argv", testargs):
result = run_squad.main()
self.assertGreaterEqual(result["f1"], 25)
self.assertGreaterEqual(result["exact"], 21)
def test_generation(self):
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
testargs = ["run_generation.py", "--prompt=Hello", "--length=10", "--seed=42"]
model_type, model_name = ("--model_type=gpt2", "--model_name_or_path=sshleifer/tiny-gpt2")
with patch.object(sys, "argv", testargs + [model_type, model_name]):
result = run_generation.main()
self.assertGreaterEqual(len(result[0]), 10)