학습 스텝 완료 후 에러(Could not synthesize characters to Hangul.) #78

froglike6 · 2020-05-18T01:41:51Z

Exiting due to exception: Could not synthesize characters to Hangul.
Traceback (most recent call last):
File "train.py", line 268, in train
log_dir, step, loss, "train")
File "train.py", line 104, in save_and_plot
parallel_run(fn, items, parallel=False)
File "/root/tts/multi-speaker-tacotron-tensorflow/utils/init.py", line 151, in parallel_run
out = fn(item)
File "train.py", line 95, in save_and_plot_fn
skip_eos_and_pad=True, combine_jamo=True))
File "/root/tts/multi-speaker-tacotron-tensorflow/text/init.py", line 77, in sequence_to_text
return jamo_to_korean(result)
File "/root/tts/multi-speaker-tacotron-tensorflow/text/korean.py", line 64, in jamo_to_korean
new_text += _get_text_from_candidates(candidates)
File "/root/tts/multi-speaker-tacotron-tensorflow/text/korean.py", line 53, in _get_text_from_candidates
return j2h(**dict(zip(["lead", "vowel", "tail"], candidates)))
File "/usr/local/lib/python3.6/site-packages/jamo/jamo.py", line 290, in j2h
return jamo_to_hangul(lead, vowel, tail)
File "/usr/local/lib/python3.6/site-packages/jamo/jamo.py", line 277, in jamo_to_hangul
'\x00')
jamo.jamo.InvalidJamoError: Could not synthesize characters to Hangul.
2020-05-18 10:29:45.504211: W tensorflow/core/kernels/queue_base.cc:295] _0_datafeeder/input_queue_1: Skipping cancelled enqueue attempt with queue not closed
2020-05-18 10:29:45.504287: W tensorflow/core/kernels/queue_base.cc:295] _1_datafeeder/input_queue: Skipping cancelled enqueue attempt with queue not closed
Traceback (most recent call last):
Traceback (most recent call last):
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
return fn(*args)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
return fn(*args)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1306, in _run_fn
status, run_metadata)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1306, in _run_fn
status, run_metadata)
File "/usr/lib64/python3.6/contextlib.py", line 88, in exit
next(self.gen)
File "/usr/lib64/python3.6/contextlib.py", line 88, in exit
next(self.gen)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.CancelledError: Enqueue operation was cancelled
[[Node: datafeeder/input_queue_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue, _arg_datafeeder/inputs_0_1, _arg_datafeeder/input_lengths_0_0, _arg_datafeeder/loss_coeff_0_3, _arg_datafeeder/mel_targets_0_4, _arg_datafeeder/linear_targets_0_2)]]
tensorflow.python.framework.errors_impl.CancelledError: Enqueue operation was cancelled
[[Node: datafeeder/input_queue_1_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue_1, _arg_datafeeder/inputs_1_0_1, _arg_datafeeder/input_lengths_1_0_0, _arg_datafeeder/loss_coeff_1_0_3, _arg_datafeeder/mel_targets_1_0_4, _arg_datafeeder/linear_targets_1_0_2)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
Traceback (most recent call last):
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 204, in run
self._enqueue_next_group()
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 204, in run
self._enqueue_next_group()
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 242, in _enqueue_next_group
self._session.run(self._enqueue_op, feed_dict=feed_dict)
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 242, in _enqueue_next_group
self._session.run(self._enqueue_op, feed_dict=feed_dict)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
options, run_metadata)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
options, run_metadata)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.CancelledError: Enqueue operation was cancelled
[[Node: datafeeder/input_queue_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue, _arg_datafeeder/inputs_0_1, _arg_datafeeder/input_lengths_0_0, _arg_datafeeder/loss_coeff_0_3, _arg_datafeeder/mel_targets_0_4, _arg_datafeeder/linear_targets_0_2)]]

Caused by op 'datafeeder/input_queue_enqueue', defined at:
File "train.py", line 322, in
main()
File "train.py", line 318, in main
train(config.model_dir, config)
File "train.py", line 136, in train
data_type='train', batch_size=hparams.batch_size)
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 160, in init
self._enqueue_op = queue.enqueue(self._placeholders)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 321, in enqueue
self._queue_ref, vals, name=scope)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1587, in _queue_enqueue_v2
name=name)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1204, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

CancelledError (see above for traceback): Enqueue operation was cancelled
[[Node: datafeeder/input_queue_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue, _arg_datafeeder/inputs_0_1, _arg_datafeeder/input_lengths_0_0, _arg_datafeeder/loss_coeff_0_3, _arg_datafeeder/mel_targets_0_4, _arg_datafeeder/linear_targets_0_2)]]

tensorflow.python.framework.errors_impl.CancelledError: Enqueue operation was cancelled
[[Node: datafeeder/input_queue_1_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue_1, _arg_datafeeder/inputs_1_0_1, _arg_datafeeder/input_lengths_1_0_0, _arg_datafeeder/loss_coeff_1_0_3, _arg_datafeeder/mel_targets_1_0_4, _arg_datafeeder/linear_targets_1_0_2)]]

Caused by op 'datafeeder/input_queue_1_enqueue', defined at:
File "train.py", line 322, in
main()
File "train.py", line 318, in main
train(config.model_dir, config)
File "train.py", line 139, in train
data_type='test', batch_size=config.num_test)
File "/root/tts/multi-speaker-tacotron-tensorflow/datasets/datafeeder.py", line 160, in init
self._enqueue_op = queue.enqueue(self._placeholders)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 321, in enqueue
self._queue_ref, vals, name=scope)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1587, in _queue_enqueue_v2
name=name)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1204, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

CancelledError (see above for traceback): Enqueue operation was cancelled
[[Node: datafeeder/input_queue_1_enqueue = QueueEnqueueV2[Tcomponents=[DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](datafeeder/input_queue_1, _arg_datafeeder/inputs_1_0_1, _arg_datafeeder/input_lengths_1_0_0, _arg_datafeeder/loss_coeff_1_0_3, _arg_datafeeder/mel_targets_1_0_4, _arg_datafeeder/linear_targets_1_0_2)]]

위와 같이 뜹니다.. 어떻게 해야 하나요?

solalala-12 · 2020-05-18T08:51:31Z

synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데

froglike6 · 2020-05-19T03:36:39Z

학습 후 파일 저장 시 이 에러가 뜹니다 2020년 5월 18일 (월) 오후 5:51, LEE SORA <[email protected]>님이 작성:

…

synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AO25MHOQVVNV7KHGXPUWGFLRSDZKFANCNFSM4NDU5AKA> .

solalala-12 · 2020-05-19T04:24:34Z

학습 후 파일 저장 시 이 에러가 뜹니다 2020년 5월 18일 (월) 오후 5:51, LEE SORA [email protected]님이 작성:
…
synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AO25MHOQVVNV7KHGXPUWGFLRSDZKFANCNFSM4NDU5AKA .

#10 참고해보세요~

froglike6 · 2020-05-19T14:10:16Z

학습 후 파일 저장 시 이 에러가 뜹니다 2020년 5월 18일 (월) 오후 5:51, LEE SORA [email protected]님이 작성:
…
synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AO25MHOQVVNV7KHGXPUWGFLRSDZKFANCNFSM4NDU5AKA .

#10 참고해보세요~

이 문제 해결했더니 list index out of range 에러뜨네요..

solalala-12 · 2020-05-20T01:10:41Z

학습 후 파일 저장 시 이 에러가 뜹니다 2020년 5월 18일 (월) 오후 5:51, LEE SORA [email protected]님이 작성:
…
synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AO25MHOQVVNV7KHGXPUWGFLRSDZKFANCNFSM4NDU5AKA .

#10 참고해보세요~

이 문제 해결했더니 list index out of range 에러뜨네요..

train.py 를 실행했더니 Could not synthesize characters to Hangul. 에러가 뜨신건가요 ?
list index out of range 에러도 상세히 올려주시면 답변 드리겠습니다.

froglike6 · 2020-05-20T04:41:24Z

학습 후 파일 저장 시 이 에러가 뜹니다 2020년 5월 18일 (월) 오후 5:51, LEE SORA [email protected]님이 작성:
…
synthesize 어떤 문구 하셨나요? input으로 들어온 텍스트를 변환하는 과정에서 생기는 문제같은데 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AO25MHOQVVNV7KHGXPUWGFLRSDZKFANCNFSM4NDU5AKA .

#10 참고해보세요~

이 문제 해결했더니 list index out of range 에러뜨네요..

train.py 를 실행했더니 Could not synthesize characters to Hangul. 에러가 뜨신건가요 ?
list index out of range 에러도 상세히 올려주시면 답변 드리겠습니다.

[root@dhmowiki tts]# python3 train.py --data_path=datasets/ksw
[] MODEL dir: logs/ksw_2020-05-20_13-36-08
[] PARAM path: logs/ksw_2020-05-20_13-36-08/params.json

[!] Detect non-krbook dataset. Set sampling rate from 24000 to 20000

[*] git recv-parse HEAD:
da58cf1

==================================================
[*] dit diff:
diff --git a/datasets/generate_data.py b/datasets/generate_data.py
index b351eb2..7afbb1d 100644
--- a/datasets/generate_data.py
+++ b/datasets/generate_data.py
@@ -37,7 +37,7 @@ def build_from_path(config):

 loss_coeff = defaultdict(one)
 if config.metadata_path.endswith("json"):

   with open(config.metadata_path) as f:

```
   with open(config.metadata_path, encoding='utf-8') as f:
       content = f.read()
   info = json.loads(content)
```
elif config.metadata_path.endswith("csv"):
diff --git a/train.py b/train.py
index 3316c3a..be7ea5a 100644
--- a/train.py
+++ b/train.py
@@ -135,7 +135,7 @@ def train(log_dir, config):
coord, data_dirs, hparams, config, 32,
data_type='train', batch_size=hparams.batch_size)
test_feeder = DataFeeder(

           coord, data_dirs, hparams, config, 8,

           coord, data_dirs, hparams, config, 2,
           data_type='test', batch_size=config.num_test)

Set up model:

==================================================
[] Checkpoint path: logs/ksw_2020-05-20_13-36-08/model.ckpt
[] Loading training data from: ['datasets/ksw/data']
[*] Using model: logs/ksw_2020-05-20_13-36-08
Hyperparameters:
adam_beta1: 0.9
adam_beta2: 0.999
attention_size: 256
attention_state_size: 256
attention_type: bah_mon
batch_size: 16
cleaners: korean_cleaners
dec_layer_num: 2
dec_prenet_sizes: [256, 128]
dec_rnn_size: 256
decay_learning_rate_mode: 0
dropout_prob: 0.8
embedding_size: 256
enc_bank_channel_size: 128
enc_bank_size: 16
enc_highway_depth: 4
enc_maxpool_width: 2
enc_prenet_sizes: [256, 128]
enc_proj_sizes: [128, 128]
enc_proj_width: 3
enc_rnn_size: 128
frame_length_ms: 50
frame_shift_ms: 12.5
griffin_lim_iters: 60
ignore_recognition_level: 1
initial_data_greedy: True
initial_learning_rate: 0.002
initial_phase_step: 8000
main_data: ['']
main_data_greedy_factor: 0
max_iters: 200
min_iters: 30
min_level_db: -100
min_tokens: 50
model_type: single
num_freq: 1025
num_mels: 80
post_bank_channel_size: 256
post_bank_size: 8
post_highway_depth: 4
post_maxpool_width: 2
post_proj_sizes: [256, 80]
post_proj_width: 3
post_rnn_size: 256
power: 1.5
preemphasis: 0.97
prioritize_loss: False
recognition_loss_coeff: 0.2
reduction_factor: 4
ref_level_db: 20
sample_rate: 24000
skip_inadequate: False
speaker_embedding_size: 16
use_fixed_test_inputs: False
filter_by_min_max_frame_batch: 100%|███████████| 41/41 [00:00<00:00, 924.70it/s]
[datasets/ksw/data] Loaded metadata for 11 examples (0.01 hours)
[datasets/ksw/data] Max length: 737
[datasets/ksw/data] Min length: 229

{'datasets/ksw/data': 1.0}

filter_by_min_max_frame_batch: 100%|███████████| 41/41 [00:00<00:00, 800.97it/s]
[datasets/ksw/data] Loaded metadata for 11 examples (0.01 hours)
[datasets/ksw/data] Max length: 737
[datasets/ksw/data] Min length: 229

{'datasets/ksw/data': 1.0}

========================================
model_type: single

Initialized Tacotron model. Dimensions:
embedding: 256
speaker embedding: None
prenet out: 128
encoder out: 256
attention out: 256
concat attn & out: 512
decoder cell out: 256
decoder out (4 frames): 320
decoder out (1 frame): 80
postnet out: 512
linear out: 1025

model_type: single

Initialized Tacotron model. Dimensions:
embedding: 256
speaker embedding: None
prenet out: 128
encoder out: 256
attention out: 256
concat attn & out: 512
decoder cell out: 256
decoder out (4 frames): 320
decoder out (1 frame): 80
postnet out: 512
linear out: 1025
2020-05-20 13:36:15.699815: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2020-05-20 13:36:15.699851: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2020-05-20 13:36:15.699860: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2020-05-20 13:36:15.699867: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2020-05-20 13:36:15.699875: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Starting new training run at commit: None
Generated 2 batches of size 2 in 0.000 sec
Traceback (most recent call last):
File "/root/tts/tts/datasets/datafeeder.py", line 204, in run
self._enqueue_next_group()
File "/root/tts/tts/datasets/datafeeder.py", line 229, in _enqueue_next_group
for _ in range(int(n * self._batches_per_group // len(self.data_dirs)))]
File "/root/tts/tts/datasets/datafeeder.py", line 229, in
for _ in range(int(n * self._batches_per_group // len(self.data_dirs)))]
File "/root/tts/tts/datasets/datafeeder.py", line 257, in _get_next_example
data_path = data_paths[self._offset[data_dir]]
IndexError: list index out of range
원래 트레인 실행하면 hangul 에러 떴는데 hangul 에러 해결하고 다시 실행하니 out of range 에러가 뜹니다.

solalala-12 · 2020-05-20T04:49:26Z

Loaded metadata for 11 examples을 보니 사용할 데이터는 11개 밖에 없는 것 같네요.
다음 batch를 가져오지 못해서 나오는 에러인 것 같습니다.
경로에 데이터가 잘 있는지 확인해보시거나 batch_size를 조절하거나 batches_per_group을 조절해보세요.

froglike6 · 2020-05-20T05:14:19Z

어떻게 조절하는지 아시나요? batch size는 train.py에서 조절하는 것 같은데 32와 8 두가지가 있네요... 2020년 5월 20일 (수) 오후 1:49, LEE SORA <[email protected]>님이 작성:

…

Loaded metadata for 11 examples을 보니 사용할 데이터는 11개 밖에 없는 것 같네요. 다음 batch를 가져오지 못해서 나오는 에러인 것 같습니다. 경로에 데이터가 잘 있는지 확인해보시거나 batch_size를 조절하거나 batches_per_group을 조절해보세요. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#78 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AO25MHLHA2O6CXRINHH7NLLRSNOOFANCNFSM4NDU5AKA> .

solalala-12 · 2020-05-20T08:30:38Z

batch_size는 hparams.py에서 수정하시면 됩니다.

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학습 스텝 완료 후 에러(Could not synthesize characters to Hangul.) #78

학습 스텝 완료 후 에러(Could not synthesize characters to Hangul.) #78

froglike6 commented May 18, 2020

solalala-12 commented May 18, 2020

froglike6 commented May 19, 2020 via email

solalala-12 commented May 19, 2020

froglike6 commented May 19, 2020 •

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solalala-12 commented May 20, 2020

froglike6 commented May 20, 2020 •

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Set up model:

solalala-12 commented May 20, 2020

froglike6 commented May 20, 2020 via email

solalala-12 commented May 20, 2020

학습 스텝 완료 후 에러(Could not synthesize characters to Hangul.) #78

학습 스텝 완료 후 에러(Could not synthesize characters to Hangul.) #78

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froglike6 commented May 18, 2020

solalala-12 commented May 18, 2020

froglike6 commented May 19, 2020 via email

solalala-12 commented May 19, 2020

froglike6 commented May 19, 2020 • edited Loading

solalala-12 commented May 20, 2020

froglike6 commented May 20, 2020 • edited Loading

[root@dhmowiki tts]# python3 train.py --data_path=datasets/ksw [] MODEL dir: logs/ksw_2020-05-20_13-36-08 [] PARAM path: logs/ksw_2020-05-20_13-36-08/params.json

[!] Detect non-krbook dataset. Set sampling rate from 24000 to 20000

Set up model:

{'datasets/ksw/data': 1.0}

filter_by_min_max_frame_batch: 100%|███████████| 41/41 [00:00<00:00, 800.97it/s] [datasets/ksw/data] Loaded metadata for 11 examples (0.01 hours) [datasets/ksw/data] Max length: 737 [datasets/ksw/data] Min length: 229

{'datasets/ksw/data': 1.0}

======================================== model_type: single

Initialized Tacotron model. Dimensions: embedding: 256 speaker embedding: None prenet out: 128 encoder out: 256 attention out: 256 concat attn & out: 512 decoder cell out: 256 decoder out (4 frames): 320 decoder out (1 frame): 80 postnet out: 512 linear out: 1025

model_type: single

solalala-12 commented May 20, 2020

froglike6 commented May 20, 2020 via email

solalala-12 commented May 20, 2020

froglike6 commented May 19, 2020 •

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froglike6 commented May 20, 2020 •

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[root@dhmowiki tts]# python3 train.py --data_path=datasets/ksw
[] MODEL dir: logs/ksw_2020-05-20_13-36-08
[] PARAM path: logs/ksw_2020-05-20_13-36-08/params.json

filter_by_min_max_frame_batch: 100%|███████████| 41/41 [00:00<00:00, 800.97it/s]
[datasets/ksw/data] Loaded metadata for 11 examples (0.01 hours)
[datasets/ksw/data] Max length: 737
[datasets/ksw/data] Min length: 229

========================================
model_type: single

Initialized Tacotron model. Dimensions:
embedding: 256
speaker embedding: None
prenet out: 128
encoder out: 256
attention out: 256
concat attn & out: 512
decoder cell out: 256
decoder out (4 frames): 320
decoder out (1 frame): 80
postnet out: 512
linear out: 1025