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minor fixes for aidatatang_200zh zipformer recipe
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@ -75,7 +75,7 @@ from typing import List, Tuple
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import k2
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import torch
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import torch.nn as nn
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from asr_datamodule import WenetSpeechAsrDataModule
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from asr_datamodule import Aidatatang_200zhAsrDataModule
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from lhotse.cut import Cut
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from onnx_pretrained import OnnxModel, greedy_search
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@ -256,7 +256,7 @@ def save_results(
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@torch.no_grad()
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def main():
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parser = get_parser()
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WenetSpeechAsrDataModule.add_arguments(parser)
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Aidatatang_200zhAsrDataModule.add_arguments(parser)
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args = parser.parse_args()
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assert (
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@ -285,7 +285,7 @@ def main():
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# we need cut ids to display recognition results.
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args.return_cuts = True
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wenetspeech = WenetSpeechAsrDataModule(args)
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aidatatang_200zh = Aidatatang_200zhAsrDataModule(args)
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def remove_short_utt(c: Cut):
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T = ((c.num_frames - 7) // 2 + 1) // 2
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@ -295,20 +295,16 @@ def main():
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)
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return T > 0
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dev_cuts = wenetspeech.valid_cuts()
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dev_cuts = aidatatang_200zh.valid_cuts()
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dev_cuts = dev_cuts.filter(remove_short_utt)
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dev_dl = wenetspeech.valid_dataloaders(dev_cuts)
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dev_dl = aidatatang_200zh.valid_dataloaders(dev_cuts)
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test_net_cuts = wenetspeech.test_net_cuts()
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test_net_cuts = test_net_cuts.filter(remove_short_utt)
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test_net_dl = wenetspeech.test_dataloaders(test_net_cuts)
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test_cuts = aidatatang_200zh.test_cuts()
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test_cuts = test_cuts.filter(remove_short_utt)
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test_dl = aidatatang_200zh.test_dataloaders(test_cuts)
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test_meeting_cuts = wenetspeech.test_meeting_cuts()
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test_meeting_cuts = test_meeting_cuts.filter(remove_short_utt)
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test_meeting_dl = wenetspeech.test_dataloaders(test_meeting_cuts)
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test_sets = ["DEV", "TEST_NET", "TEST_MEETING"]
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test_dl = [dev_dl, test_net_dl, test_meeting_dl]
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test_sets = ["dev", "test"]
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test_dl = [dev_dl, test_dl]
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for test_set, test_dl in zip(test_sets, test_dl):
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start_time = time.time()
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