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Merge branch 'develop' into 'master' 

examples/deepvoice3 minor fixes

See merge request !73
This commit is contained in:
liuyibing01 2020-08-12 16:29:29 +08:00
parent 610181d4c0 3717ac1342
commit b604d1c7dd
4 changed files with 5 additions and 6 deletions
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2
examples/deepvoice3/README.md
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@ -87,7 +87,7 @@ runs/Jul07_09-39-34_instance-mqcyj27y-4/
... ...
``` ```
Since e use waveflow to synthesize audio while training, so download the trained waveflow model and extract it in current directory before training. Since we use waveflow to synthesize audio while training, so download the trained waveflow model and extract it in current directory before training.
```bash ```bash
wget https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_res128_ljspeech_ckpt_1.0.zip wget https://paddlespeech.bj.bcebos.com/Parakeet/waveflow_res128_ljspeech_ckpt_1.0.zip

1
examples/deepvoice3/configs/ljspeech.yaml
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@ -39,6 +39,7 @@ clip_value: 5.0
clip_norm: 100.0 clip_norm: 100.0
# training: # training:
max_iteration: 1000000
batch_size: 16 batch_size: 16
report_interval: 10000 report_interval: 10000
save_interval: 10000 save_interval: 10000

6
examples/deepvoice3/data.py
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@ -62,10 +62,8 @@ class DataCollector(object):
for example in examples: for example in examples:
text, spec, mel, _ = example text, spec, mel, _ = example
text_seqs.append(en.text_to_sequence(text, self.p_pronunciation)) text_seqs.append(en.text_to_sequence(text, self.p_pronunciation))
# if max_frames - mel.shape[0] < 0: specs.append(np.pad(spec, [(0, max_frames - spec.shape[0]), (0, 0)], mode="constant"))
# import pdb; pdb.set_trace() mels.append(np.pad(mel, [(0, max_frames - mel.shape[0]), (0, 0)], mode="constant"))
specs.append(np.pad(spec, [(0, max_frames - spec.shape[0]), (0, 0)]))
mels.append(np.pad(mel, [(0, max_frames - mel.shape[0]), (0, 0)]))
specs = np.stack(specs) specs = np.stack(specs)
mels = np.stack(mels) mels = np.stack(mels)

2
examples/deepvoice3/train.py
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@ -81,7 +81,7 @@ def train(args, config):
optim = create_optimizer(model, config) optim = create_optimizer(model, config)
global global_step global global_step
max_iteration = 1000000 max_iteration = config["max_iteration"]
iterator = iter(tqdm.tqdm(train_loader)) iterator = iter(tqdm.tqdm(train_loader))
while global_step <= max_iteration: while global_step <= max_iteration: