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8f18274f75
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
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import shutil
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import unittest
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import cv2
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from modelscope.exporters.cv import CartoonTranslationExporter
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from modelscope.msdatasets import MsDataset
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from modelscope.outputs import OutputKeys
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from modelscope.pipelines import pipeline
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from modelscope.pipelines.base import Pipeline
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from modelscope.trainers.cv import CartoonTranslationTrainer
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from modelscope.utils.constant import Tasks
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from modelscope.utils.test_utils import test_level
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class TestImagePortraitStylizationTrainer(unittest.TestCase):
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def setUp(self) -> None:
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self.task = Tasks.image_portrait_stylization
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self.test_image = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/image_cartoon.png'
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def tearDown(self):
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shutil.rmtree('exp_localtoon')
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super().tearDown()
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_with_model_name(self):
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model_id = 'damo/cv_unet_person-image-cartoon_compound-models'
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data_dir = MsDataset.load(
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'dctnet_train_clipart_mini_ms',
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namespace='menyifang',
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split='train').config_kwargs['split_config']['train']
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data_photo = os.path.join(data_dir, 'face_photo')
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data_cartoon = os.path.join(data_dir, 'face_cartoon')
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work_dir = 'exp_localtoon'
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max_steps = 10
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trainer = CartoonTranslationTrainer(
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model=model_id,
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work_dir=work_dir,
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photo=data_photo,
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cartoon=data_cartoon,
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max_steps=max_steps)
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trainer.train()
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ckpt_path = os.path.join(work_dir, 'saved_models', 'model-' + str(0))
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pb_path = os.path.join(trainer.model_dir, 'cartoon_h.pb')
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exporter = CartoonTranslationExporter()
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exporter.export_frozen_graph_def(
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ckpt_path=ckpt_path, frozen_graph_path=pb_path)
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self.pipeline_person_image_cartoon(trainer.model_dir)
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def pipeline_person_image_cartoon(self, model_dir):
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pipeline_cartoon = pipeline(task=self.task, model=model_dir)
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result = pipeline_cartoon(input=self.test_image)
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if result is not None:
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cv2.imwrite('result.png', result[OutputKeys.OUTPUT_IMG])
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print(f'Output written to {os.path.abspath("result.png")}')
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if __name__ == '__main__':
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unittest.main()
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