train.py problem

[rabbia970]

Hi,

whenever I run train.py file using various parameters or path getting the below error. I am unable to understand the purpose of "train.txt". Please help

Command line args:
{'--checkpoint': None,
'--checkpoint-dir': 'checkpoints',
'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--data-root': './prepro',
'--help': False,
'--hparams': '',
'--load-embedding': None,
'--log-event-path': None,
'--preset': 'presets/deepvoice3_ljspeech.json',
'--reset-optimizer': False,
'--restore-parts': None,
'--speaker-id': None,
'--train-postnet-only': False,
'--train-seq2seq-only': False}
Training whole model
Training seq2seq model
[!] Windows Detected - IF THAllocator.c 0x05 error occurs SET num_workers to 1
Hyperparameters:
adam_beta1: 0.5
adam_beta2: 0.9
adam_eps: 1e-06
allow_clipping_in_normalization: True
amsgrad: False
batch_size: 16
binary_divergence_weight: 0.1
builder: deepvoice3
checkpoint_interval: 10000
clip_thresh: 0.1
converter_channels: 256
decoder_channels: 256
downsample_step: 4
dropout: 0.050000000000000044
embedding_weight_std: 0.1
encoder_channels: 512
eval_interval: 10000
fft_size: 1024
fmax: 7600
fmin: 125
force_monotonic_attention: True
freeze_embedding: False
frontend: en
guided_attention_sigma: 0.2
hop_size: 256
ignore_recognition_level: 2
initial_learning_rate: 0.0005
kernel_size: 3
key_position_rate: 1.385
key_projection: True
lr_schedule: noam_learning_rate_decay
lr_schedule_kwargs: {}
masked_loss_weight: 0.5
max_positions: 512
min_level_db: -100
min_text: 20
n_speakers: 1
name: deepvoice3
nepochs: 2000
num_mels: 80
num_workers: 2
outputs_per_step: 1
padding_idx: 0
pin_memory: True
power: 1.4
preemphasis: 0.97
priority_freq: 3000
priority_freq_weight: 0.0
process_only_htk_aligned: False
query_position_rate: 1.0
ref_level_db: 20
replace_pronunciation_prob: 0.5
rescaling: False
rescaling_max: 0.999
sample_rate: 22050
save_optimizer_state: True
speaker_embed_dim: 16
speaker_embedding_weight_std: 0.01
text_embed_dim: 256
trainable_positional_encodings: False
use_decoder_state_for_postnet_input: True
use_guided_attention: True
use_memory_mask: True
value_projection: True
weight_decay: 0.0
window_ahead: 3
window_backward: 1
Traceback (most recent call last):
File "train.py", line 954, in
X = FileSourceDataset(TextDataSource(data_root, speaker_id))
File "C:\ProgramData\Anaconda3\envs\tf-gpu\lib\site-packages\nnmnkwii\datasets_init_.py", line 108, in init
collected_files = self.file_data_source.collect_files()
File "train.py", line 106, in collect_files
with open(meta, "rb") as f:
FileNotFoundError: [Errno 2] No such file or directory: './prepro\train.txt'

(tf-gpu) C:\Windows\System32\deepvoice3_pytorch>python train.py --preset=presets/deepvoice3_ljspeech.json --data-root=.\prepro
Command line args:
{'--checkpoint': None,
'--checkpoint-dir': 'checkpoints',
'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--data-root': '.\prepro',
'--help': False,
'--hparams': '',
'--load-embedding': None,
'--log-event-path': None,
'--preset': 'presets/deepvoice3_ljspeech.json',
'--reset-optimizer': False,
'--restore-parts': None,
'--speaker-id': None,
'--train-postnet-only': False,
'--train-seq2seq-only': False}
Training whole model
Training seq2seq model
[!] Windows Detected - IF THAllocator.c 0x05 error occurs SET num_workers to 1
Hyperparameters:
adam_beta1: 0.5
adam_beta2: 0.9
adam_eps: 1e-06
allow_clipping_in_normalization: True
amsgrad: False
batch_size: 16
binary_divergence_weight: 0.1
builder: deepvoice3
checkpoint_interval: 10000
clip_thresh: 0.1
converter_channels: 256
decoder_channels: 256
downsample_step: 4
dropout: 0.050000000000000044
embedding_weight_std: 0.1
encoder_channels: 512
eval_interval: 10000
fft_size: 1024
fmax: 7600
fmin: 125
force_monotonic_attention: True
freeze_embedding: False
frontend: en
guided_attention_sigma: 0.2
hop_size: 256
ignore_recognition_level: 2
initial_learning_rate: 0.0005
kernel_size: 3
key_position_rate: 1.385
key_projection: True
lr_schedule: noam_learning_rate_decay
lr_schedule_kwargs: {}
masked_loss_weight: 0.5
max_positions: 512
min_level_db: -100
min_text: 20
n_speakers: 1
name: deepvoice3
nepochs: 2000
num_mels: 80
num_workers: 2
outputs_per_step: 1
padding_idx: 0
pin_memory: True
power: 1.4
preemphasis: 0.97
priority_freq: 3000
priority_freq_weight: 0.0
process_only_htk_aligned: False
query_position_rate: 1.0
ref_level_db: 20
replace_pronunciation_prob: 0.5
rescaling: False
rescaling_max: 0.999
sample_rate: 22050
save_optimizer_state: True
speaker_embed_dim: 16
speaker_embedding_weight_std: 0.01
text_embed_dim: 256
trainable_positional_encodings: False
use_decoder_state_for_postnet_input: True
use_guided_attention: True
use_memory_mask: True
value_projection: True
weight_decay: 0.0
window_ahead: 3
window_backward: 1
Traceback (most recent call last):
File "train.py", line 954, in
X = FileSourceDataset(TextDataSource(data_root, speaker_id))
File "C:\ProgramData\Anaconda3\envs\tf-gpu\lib\site-packages\nnmnkwii\datasets_init_.py", line 108, in init
collected_files = self.file_data_source.collect_files()
File "train.py", line 106, in collect_files
with open(meta, "rb") as f:
FileNotFoundError: [Errno 2] No such file or directory: '.\prepro\train.txt'

[wolfassi123]

@rabbia970 did you manage to solve the issue?

[GoombaProgrammer]

you need to set the data dir to the preprocessed dir