Merge branch 'develop' into 'master'
examples/deepvoice3 minor fixes See merge request !73
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@ -87,7 +87,7 @@ runs/Jul07_09-39-34_instance-mqcyj27y-4/
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...
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```
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Since e use waveflow to synthesize audio while training, so download the trained waveflow model and extract it in current directory before training.
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Since we use waveflow to synthesize audio while training, so download the trained waveflow model and extract it in current directory before training.
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```bash
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wget https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_res128_ljspeech_ckpt_1.0.zip
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@ -39,6 +39,7 @@ clip_value: 5.0
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clip_norm: 100.0
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# training:
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max_iteration: 1000000
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batch_size: 16
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report_interval: 10000
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save_interval: 10000
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@ -62,10 +62,8 @@ class DataCollector(object):
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for example in examples:
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text, spec, mel, _ = example
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text_seqs.append(en.text_to_sequence(text, self.p_pronunciation))
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# if max_frames - mel.shape[0] < 0:
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# import pdb; pdb.set_trace()
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specs.append(np.pad(spec, [(0, max_frames - spec.shape[0]), (0, 0)]))
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mels.append(np.pad(mel, [(0, max_frames - mel.shape[0]), (0, 0)]))
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specs.append(np.pad(spec, [(0, max_frames - spec.shape[0]), (0, 0)], mode="constant"))
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mels.append(np.pad(mel, [(0, max_frames - mel.shape[0]), (0, 0)], mode="constant"))
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specs = np.stack(specs)
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mels = np.stack(mels)
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@ -81,7 +81,7 @@ def train(args, config):
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optim = create_optimizer(model, config)
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global global_step
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max_iteration = 1000000
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max_iteration = config["max_iteration"]
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iterator = iter(tqdm.tqdm(train_loader))
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while global_step <= max_iteration:
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