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Add teardown for tests

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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12643554

* add teardown for tests

* add teardown for dialog_modeling_trainer,document_grounded_dialog_generate_trainer,document_grounded_dialog_rerank_trainer,document_grounded_dialog_retrieval_trainer,training_args,translation_evaluation_trainer,translation_trainer
This commit is contained in:
yuze.zyz
2023-06-28 09:44:44 +08:00
committed by wenmeng.zwm
parent eb0f0216c6
commit 8f18274f75
12 changed files with 75 additions and 12 deletions
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6
tests/trainers/test_dialog_modeling_trainer.py
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@@ -1,5 +1,6 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import unittest
import torch
@@ -17,6 +18,11 @@ class TestDialogModelingTrainer(unittest.TestCase):
model_id = 'damo/nlp_space_pretrained-dialog-model'
output_dir = './dialog_fintune_result'
def tearDown(self):
if os.path.exists(self.output_dir):
shutil.rmtree(self.output_dir)
super().tearDown()
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
def test_trainer_with_model_and_args(self):
# download data set

5
tests/trainers/test_document_grounded_dialog_rerank_trainer.py
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@@ -1,5 +1,6 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import unittest
import json
@@ -19,6 +20,10 @@ class TestDialogIntentTrainer(unittest.TestCase):
def setUp(self):
self.model_id = 'DAMO_ConvAI/nlp_convai_ranking_pretrain'
def tearDown(self):
shutil.rmtree('./model')
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer_with_model_and_args(self):
args = {

5
tests/trainers/test_image_portrait_stylization_trainer.py
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@@ -1,5 +1,6 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import unittest
import cv2
@@ -20,6 +21,10 @@ class TestImagePortraitStylizationTrainer(unittest.TestCase):
self.task = Tasks.image_portrait_stylization
self.test_image = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/image_cartoon.png'
def tearDown(self):
shutil.rmtree('exp_localtoon')
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_run_with_model_name(self):
model_id = 'damo/cv_unet_person-image-cartoon_compound-models'

5
tests/trainers/test_nerf_recon_acc_trainer.py
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@@ -1,5 +1,6 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import unittest
from modelscope.msdatasets import MsDataset
@@ -10,6 +11,10 @@ from modelscope.utils.test_utils import test_level
class TestNeRFReconAccTrainer(unittest.TestCase):
def tearDown(self):
shutil.rmtree('exp_nerf')
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_run_with_model_name(self):
model_id = 'damo/cv_nerf-3d-reconstruction-accelerate_damo'

4
tests/trainers/test_ocr_detection_db_trainer.py
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@@ -36,6 +36,10 @@ class TestOCRDetectionDBTrainerSingleGPU(unittest.TestCase):
self.saved_infer_model = os.path.join(self.saved_dir,
'pytorch_model.pt')
def tearDown(self):
shutil.rmtree(self.saved_dir)
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer_finetune_singleGPU(self):

18
tests/trainers/test_ofa_mmspeech_trainer.py
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@@ -69,11 +69,17 @@ class TestMMSpeechTrainer(unittest.TestCase):
'metrics': [{'type': 'accuracy'}]},
'preprocessor': []}
self.WORKSPACE = './workspace/ckpts/asr_recognition'
def tearDown(self) -> None:
if os.path.exists(self.WORKSPACE):
shutil.rmtree(self.WORKSPACE, ignore_errors=True)
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer_std(self):
WORKSPACE = './workspace/ckpts/asr_recognition'
os.makedirs(WORKSPACE, exist_ok=True)
config_file = os.path.join(WORKSPACE, ModelFile.CONFIGURATION)
os.makedirs(self.WORKSPACE, exist_ok=True)
config_file = os.path.join(self.WORKSPACE, ModelFile.CONFIGURATION)
with open(config_file, 'w') as writer:
json.dump(self.finetune_cfg, writer)
@@ -81,7 +87,7 @@ class TestMMSpeechTrainer(unittest.TestCase):
args = dict(
model=pretrained_model,
work_dir=WORKSPACE,
work_dir=self.WORKSPACE,
train_dataset=MsDataset.load(
'aishell1_subset',
subset_name='default',
@@ -100,8 +106,8 @@ class TestMMSpeechTrainer(unittest.TestCase):
self.assertIn(
ModelFile.TORCH_MODEL_BIN_FILE,
os.listdir(os.path.join(WORKSPACE, ModelFile.TRAIN_OUTPUT_DIR)))
shutil.rmtree(WORKSPACE)
os.listdir(
os.path.join(self.WORKSPACE, ModelFile.TRAIN_OUTPUT_DIR)))
if __name__ == '__main__':

17
tests/trainers/test_ofa_trainer.py
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@@ -69,19 +69,24 @@ class TestOfaTrainer(unittest.TestCase):
'evaluation': {'dataloader': {'batch_size_per_gpu': 4, 'workers_per_gpu': 0},
'metrics': [{'type': 'accuracy'}]},
'preprocessor': []}
self.WORKSPACE = './workspace/ckpts/recognition'
def tearDown(self) -> None:
if os.path.exists(self.WORKSPACE):
shutil.rmtree(self.WORKSPACE, ignore_errors=True)
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer_std(self):
WORKSPACE = './workspace/ckpts/recognition'
os.makedirs(WORKSPACE, exist_ok=True)
config_file = os.path.join(WORKSPACE, ModelFile.CONFIGURATION)
os.makedirs(self.WORKSPACE, exist_ok=True)
config_file = os.path.join(self.WORKSPACE, ModelFile.CONFIGURATION)
with open(config_file, 'w') as writer:
json.dump(self.finetune_cfg, writer, indent=4)
pretrained_model = 'damo/ofa_ocr-recognition_scene_base_zh'
args = dict(
model=pretrained_model,
work_dir=WORKSPACE,
work_dir=self.WORKSPACE,
train_dataset=MsDataset.load(
'ocr_fudanvi_zh',
subset_name='scene',
@@ -100,8 +105,8 @@ class TestOfaTrainer(unittest.TestCase):
self.assertIn(
ModelFile.TORCH_MODEL_BIN_FILE,
os.listdir(os.path.join(WORKSPACE, ModelFile.TRAIN_OUTPUT_DIR)))
shutil.rmtree(WORKSPACE)
os.listdir(
os.path.join(self.WORKSPACE, ModelFile.TRAIN_OUTPUT_DIR)))
if __name__ == '__main__':

1
tests/trainers/test_plug_finetune_text_generation.py
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@@ -45,6 +45,7 @@ def test_trainer_with_model_and_args():
trainer = build_trainer(
name=Trainers.nlp_plug_trainer, default_args=kwargs)
trainer.train()
shutil.rmtree(tmp_dir)
if __name__ == '__main__':

4
tests/trainers/test_referring_video_object_segmentation_trainer.py
View File

@@ -60,6 +60,10 @@ class TestImageInstanceSegmentationTrainer(unittest.TestCase):
self.max_epochs = max_epochs
def tearDown(self):
shutil.rmtree('./work_dir')
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer(self):
kwargs = dict(

5
tests/trainers/test_team_transfer_trainer.py
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@@ -1,4 +1,5 @@
import os
import shutil
import unittest
import json
@@ -81,6 +82,10 @@ def train_worker(device_id):
class TEAMTransferTrainerTest(unittest.TestCase):
def tearDown(self) -> None:
super().tearDown()
shutil.rmtree('./ckpt')
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer(self):
if torch.cuda.device_count() > 0:

5
tests/trainers/test_tinynas_damoyolo_trainer.py
View File

@@ -1,6 +1,7 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import shutil
import unittest
from modelscope.hub.snapshot_download import snapshot_download
@@ -21,6 +22,10 @@ class TestTinynasDamoyoloTrainerSingleGPU(unittest.TestCase):
self.model_id = 'damo/cv_tinynas_object-detection_damoyolo'
self.cache_path = _setup()
def tearDown(self) -> None:
super().tearDown()
shutil.rmtree('./workdirs')
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_trainer_from_scratch_singleGPU(self):
kwargs = dict(

12
tests/trainers/test_translation_evaluation_trainer.py
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@@ -1,8 +1,11 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os.path
import shutil
import unittest
from modelscope.metainfo import Trainers
from modelscope.trainers import build_trainer
from modelscope.utils.hub import read_config
from modelscope.utils.test_utils import test_level
@@ -13,6 +16,15 @@ class TranslationEvaluationTest(unittest.TestCase):
self.model_id_large = 'damo/nlp_unite_mup_translation_evaluation_multilingual_large'
self.model_id_base = 'damo/nlp_unite_mup_translation_evaluation_multilingual_base'
def tearDown(self) -> None:
cfg_base = read_config(self.model_id_base)
if os.path.exists(cfg_base.train.work_dir):
shutil.rmtree(cfg_base.train.work_dir, ignore_errors=True)
cfg_large = read_config(self.model_id_large)
if os.path.exists(cfg_large.train.work_dir):
shutil.rmtree(cfg_large.train.work_dir, ignore_errors=True)
super().tearDown()
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_run_with_unite_mup_large(self) -> None:
default_args = {'model': self.model_id_large}