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