mirror of
https://github.com/modelscope/modelscope.git
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104 lines
3.4 KiB
Python
104 lines
3.4 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 tempfile
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import unittest
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import json
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from modelscope.hub.snapshot_download import snapshot_download
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from modelscope.metainfo import Trainers
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from modelscope.msdatasets import MsDataset
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from modelscope.trainers import build_trainer
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from modelscope.utils.config import Config
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from modelscope.utils.constant import DownloadMode, ModelFile, Tasks
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from modelscope.utils.test_utils import test_level
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class TestDialogIntentTrainer(unittest.TestCase):
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def setUp(self):
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self.save_dir = tempfile.TemporaryDirectory().name
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if not os.path.exists(self.save_dir):
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os.mkdir(self.save_dir)
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def tearDown(self):
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shutil.rmtree(self.save_dir)
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super().tearDown()
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@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
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def test_trainer_with_model_and_args(self):
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model_id = 'damo/nlp_space_pretrained-dialog-model'
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data_banking = MsDataset.load('banking77')
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self.data_dir = data_banking._hf_ds.config_kwargs['split_config'][
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'train']
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self.model_dir = snapshot_download(model_id)
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self.debugging = True
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kwargs = dict(
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model_dir=self.model_dir,
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cfg_name='intent_train_config.json',
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cfg_modify_fn=self.cfg_modify_fn)
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trainer = build_trainer(
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name=Trainers.dialog_intent_trainer, default_args=kwargs)
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trainer.train()
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def cfg_modify_fn(self, cfg):
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config = {
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'num_intent': 77,
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'BPETextField': {
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'vocab_path': '',
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'data_name': 'banking77',
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'data_root': self.data_dir,
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'understand': True,
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'generation': False,
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'max_len': 256
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},
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'Dataset': {
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'data_dir': self.data_dir,
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'with_contrastive': False,
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'trigger_role': 'user',
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'trigger_data': 'banking'
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},
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'Trainer': {
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'can_norm': True,
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'seed': 11,
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'gpu': 1,
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'save_dir': self.save_dir,
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'batch_size_label': 128,
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'batch_size_nolabel': 0,
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'log_steps': 20
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},
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'Model': {
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'init_checkpoint': self.model_dir,
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'model': 'IntentUnifiedTransformer',
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'example': False,
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'num_intent': 77,
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'with_rdrop': True,
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'num_turn_embeddings': 21,
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'dropout': 0.25,
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'kl_ratio': 5.0,
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'embed_dropout': 0.25,
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'attn_dropout': 0.25,
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'ff_dropout': 0.25,
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'with_pool': False,
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'warmup_steps': -1
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}
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}
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cfg.BPETextField.vocab_path = os.path.join(self.model_dir,
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ModelFile.VOCAB_FILE)
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cfg.num_intent = 77
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cfg.Trainer.update(config['Trainer'])
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cfg.BPETextField.update(config['BPETextField'])
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cfg.Dataset.update(config['Dataset'])
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cfg.Model.update(config['Model'])
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if self.debugging:
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cfg.Trainer.save_checkpoint = False
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cfg.Trainer.num_epochs = 1
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cfg.Trainer.batch_size_label = 64
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return cfg
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if __name__ == '__main__':
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unittest.main()
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