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Build error
fix ds ckpt
Browse files
checkpoints/ds_exp/config.yaml
ADDED
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| 1 |
+
K_step: 71
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| 2 |
+
accumulate_grad_batches: 1
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| 3 |
+
amp: false
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| 4 |
+
audio_num_mel_bins: 80
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| 5 |
+
audio_sample_rate: 22050
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| 6 |
+
base_config:
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| 7 |
+
- egs/egs_bases/tts/ds.yaml
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| 8 |
+
- ./fs2_orig.yaml
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| 9 |
+
binarization_args:
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| 10 |
+
min_sil_duration: 0.1
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| 11 |
+
shuffle: false
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| 12 |
+
test_range:
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| 13 |
+
- 0
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| 14 |
+
- 523
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| 15 |
+
train_range:
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| 16 |
+
- 871
|
| 17 |
+
- -1
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| 18 |
+
trim_eos_bos: false
|
| 19 |
+
valid_range:
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| 20 |
+
- 523
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| 21 |
+
- 871
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| 22 |
+
with_align: true
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| 23 |
+
with_f0: true
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| 24 |
+
with_f0cwt: true
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| 25 |
+
with_linear: false
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| 26 |
+
with_spk_embed: false
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| 27 |
+
with_wav: false
|
| 28 |
+
binarizer_cls: data_gen.tts.base_binarizer.BaseBinarizer
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| 29 |
+
binary_data_dir: data/binary/ljspeech_cwt
|
| 30 |
+
check_val_every_n_epoch: 10
|
| 31 |
+
clip_grad_norm: 1
|
| 32 |
+
clip_grad_value: 0
|
| 33 |
+
conv_use_pos: false
|
| 34 |
+
cwt_std_scale: 0.8
|
| 35 |
+
debug: false
|
| 36 |
+
dec_dilations:
|
| 37 |
+
- 1
|
| 38 |
+
- 1
|
| 39 |
+
- 1
|
| 40 |
+
- 1
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| 41 |
+
dec_ffn_kernel_size: 9
|
| 42 |
+
dec_inp_add_noise: false
|
| 43 |
+
dec_kernel_size: 5
|
| 44 |
+
dec_layers: 4
|
| 45 |
+
dec_post_net_kernel: 3
|
| 46 |
+
decay_steps: 50000
|
| 47 |
+
decoder_rnn_dim: 0
|
| 48 |
+
decoder_type: fft
|
| 49 |
+
diff_decoder_type: wavenet
|
| 50 |
+
diff_loss_type: l1
|
| 51 |
+
dilation_cycle_length: 1
|
| 52 |
+
dropout: 0.1
|
| 53 |
+
ds_workers: 2
|
| 54 |
+
dur_predictor_kernel: 3
|
| 55 |
+
dur_predictor_layers: 2
|
| 56 |
+
enc_dec_norm: ln
|
| 57 |
+
enc_dilations:
|
| 58 |
+
- 1
|
| 59 |
+
- 1
|
| 60 |
+
- 1
|
| 61 |
+
- 1
|
| 62 |
+
enc_ffn_kernel_size: 9
|
| 63 |
+
enc_kernel_size: 5
|
| 64 |
+
enc_layers: 4
|
| 65 |
+
enc_post_net_kernel: 3
|
| 66 |
+
enc_pre_ln: true
|
| 67 |
+
enc_prenet: true
|
| 68 |
+
encoder_K: 8
|
| 69 |
+
encoder_type: fft
|
| 70 |
+
endless_ds: true
|
| 71 |
+
eval_max_batches: -1
|
| 72 |
+
f0_max: 600
|
| 73 |
+
f0_min: 80
|
| 74 |
+
ffn_act: gelu
|
| 75 |
+
ffn_hidden_size: 1024
|
| 76 |
+
fft_size: 1024
|
| 77 |
+
fmax: 7600
|
| 78 |
+
fmin: 80
|
| 79 |
+
frames_multiple: 1
|
| 80 |
+
fs2_ckpt: checkpoints/fs2orig_exp/model_ckpt_steps_100000.ckpt
|
| 81 |
+
gen_dir_name: ''
|
| 82 |
+
griffin_lim_iters: 30
|
| 83 |
+
hidden_size: 256
|
| 84 |
+
hop_size: 256
|
| 85 |
+
infer: false
|
| 86 |
+
keep_bins: 80
|
| 87 |
+
lambda_commit: 0.25
|
| 88 |
+
lambda_energy: 0.1
|
| 89 |
+
lambda_f0: 1.0
|
| 90 |
+
lambda_ph_dur: 0.1
|
| 91 |
+
lambda_sent_dur: 1.0
|
| 92 |
+
lambda_uv: 1.0
|
| 93 |
+
lambda_word_dur: 1.0
|
| 94 |
+
layers_in_block: 2
|
| 95 |
+
load_ckpt: ''
|
| 96 |
+
loud_norm: false
|
| 97 |
+
lr: 0.001
|
| 98 |
+
max_beta: 0.06
|
| 99 |
+
max_epochs: 1000
|
| 100 |
+
max_frames: 1548
|
| 101 |
+
max_input_tokens: 1550
|
| 102 |
+
max_sentences: 128
|
| 103 |
+
max_tokens: 30000
|
| 104 |
+
max_updates: 160000
|
| 105 |
+
max_valid_sentences: 1
|
| 106 |
+
max_valid_tokens: 60000
|
| 107 |
+
mel_losses: l1
|
| 108 |
+
mel_vmax: 1.5
|
| 109 |
+
mel_vmin: -6
|
| 110 |
+
min_frames: 0
|
| 111 |
+
num_ckpt_keep: 3
|
| 112 |
+
num_heads: 2
|
| 113 |
+
num_sanity_val_steps: 5
|
| 114 |
+
num_spk: 1
|
| 115 |
+
num_valid_plots: 10
|
| 116 |
+
optimizer_adam_beta1: 0.9
|
| 117 |
+
optimizer_adam_beta2: 0.98
|
| 118 |
+
out_wav_norm: false
|
| 119 |
+
pitch_extractor: parselmouth
|
| 120 |
+
pitch_key: pitch
|
| 121 |
+
pitch_type: cwt
|
| 122 |
+
predictor_dropout: 0.5
|
| 123 |
+
predictor_grad: 0.1
|
| 124 |
+
predictor_hidden: -1
|
| 125 |
+
predictor_kernel: 5
|
| 126 |
+
predictor_layers: 5
|
| 127 |
+
preprocess_args:
|
| 128 |
+
add_eos_bos: true
|
| 129 |
+
mfa_group_shuffle: false
|
| 130 |
+
mfa_offset: 0.02
|
| 131 |
+
nsample_per_mfa_group: 1000
|
| 132 |
+
reset_phone_dict: true
|
| 133 |
+
reset_word_dict: true
|
| 134 |
+
save_sil_mask: true
|
| 135 |
+
txt_processor: en
|
| 136 |
+
use_mfa: true
|
| 137 |
+
vad_max_silence_length: 12
|
| 138 |
+
wav_processors: []
|
| 139 |
+
with_phsep: true
|
| 140 |
+
preprocess_cls: egs.datasets.audio.lj.preprocess.LJPreprocess
|
| 141 |
+
print_nan_grads: false
|
| 142 |
+
processed_data_dir: data/processed/ljspeech
|
| 143 |
+
profile_infer: false
|
| 144 |
+
raw_data_dir: data/raw/LJSpeech-1.1
|
| 145 |
+
ref_norm_layer: bn
|
| 146 |
+
rename_tmux: true
|
| 147 |
+
residual_channels: 256
|
| 148 |
+
residual_layers: 20
|
| 149 |
+
resume_from_checkpoint: 0
|
| 150 |
+
save_best: false
|
| 151 |
+
save_codes:
|
| 152 |
+
- tasks
|
| 153 |
+
- modules
|
| 154 |
+
- egs
|
| 155 |
+
save_f0: false
|
| 156 |
+
save_gt: true
|
| 157 |
+
schedule_type: linear
|
| 158 |
+
scheduler: warmup
|
| 159 |
+
seed: 1234
|
| 160 |
+
sort_by_len: true
|
| 161 |
+
spec_max:
|
| 162 |
+
- -0.5982
|
| 163 |
+
- -0.0778
|
| 164 |
+
- 0.1205
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| 165 |
+
- 0.2747
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| 166 |
+
- 0.4657
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| 167 |
+
- 0.5123
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| 168 |
+
- 0.583
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| 169 |
+
- 0.7093
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| 170 |
+
- 0.6461
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| 171 |
+
- 0.6101
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| 172 |
+
- 0.7316
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| 173 |
+
- 0.7715
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| 174 |
+
- 0.7681
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| 175 |
+
- 0.8349
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| 176 |
+
- 0.7815
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| 177 |
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- 0.7591
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| 178 |
+
- 0.791
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| 179 |
+
- 0.7433
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| 180 |
+
- 0.7352
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| 181 |
+
- 0.6869
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| 182 |
+
- 0.6854
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| 183 |
+
- 0.6623
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| 184 |
+
- 0.5353
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| 185 |
+
- 0.6492
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+
- 0.6909
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- 0.6106
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- 0.5761
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- 0.5236
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- 0.5638
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- 0.4054
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- 0.4545
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- 0.3407
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- 0.3037
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- 0.338
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- 0.1599
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- 0.1603
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- 0.2741
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- 0.213
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- 0.1569
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- 0.1911
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- 0.2324
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- 0.1221
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- -0.0933
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- 0.0513
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| 237 |
+
- 0.0888
|
| 238 |
+
- 0.1998
|
| 239 |
+
- 0.228
|
| 240 |
+
- 0.2932
|
| 241 |
+
- 0.3047
|
| 242 |
+
spec_min:
|
| 243 |
+
- -4.7574
|
| 244 |
+
- -4.6783
|
| 245 |
+
- -4.6431
|
| 246 |
+
- -4.5832
|
| 247 |
+
- -4.539
|
| 248 |
+
- -4.6771
|
| 249 |
+
- -4.8089
|
| 250 |
+
- -4.7672
|
| 251 |
+
- -4.5784
|
| 252 |
+
- -4.7755
|
| 253 |
+
- -4.715
|
| 254 |
+
- -4.8919
|
| 255 |
+
- -4.8271
|
| 256 |
+
- -4.7389
|
| 257 |
+
- -4.6047
|
| 258 |
+
- -4.7759
|
| 259 |
+
- -4.6799
|
| 260 |
+
- -4.8201
|
| 261 |
+
- -4.7823
|
| 262 |
+
- -4.8262
|
| 263 |
+
- -4.7857
|
| 264 |
+
- -4.7545
|
| 265 |
+
- -4.9358
|
| 266 |
+
- -4.9733
|
| 267 |
+
- -5.1134
|
| 268 |
+
- -5.1395
|
| 269 |
+
- -4.9016
|
| 270 |
+
- -4.8434
|
| 271 |
+
- -5.0189
|
| 272 |
+
- -4.846
|
| 273 |
+
- -5.0529
|
| 274 |
+
- -4.951
|
| 275 |
+
- -5.0217
|
| 276 |
+
- -5.0049
|
| 277 |
+
- -5.1831
|
| 278 |
+
- -5.1445
|
| 279 |
+
- -5.1015
|
| 280 |
+
- -5.0281
|
| 281 |
+
- -4.9887
|
| 282 |
+
- -4.9916
|
| 283 |
+
- -4.9785
|
| 284 |
+
- -4.9071
|
| 285 |
+
- -4.9488
|
| 286 |
+
- -5.0342
|
| 287 |
+
- -4.9332
|
| 288 |
+
- -5.065
|
| 289 |
+
- -4.8924
|
| 290 |
+
- -5.0875
|
| 291 |
+
- -5.0483
|
| 292 |
+
- -5.0848
|
| 293 |
+
- -5.0655
|
| 294 |
+
- -5.0279
|
| 295 |
+
- -5.0015
|
| 296 |
+
- -5.0792
|
| 297 |
+
- -5.0636
|
| 298 |
+
- -5.2413
|
| 299 |
+
- -5.1421
|
| 300 |
+
- -5.171
|
| 301 |
+
- -5.3256
|
| 302 |
+
- -5.0511
|
| 303 |
+
- -5.1186
|
| 304 |
+
- -5.0057
|
| 305 |
+
- -5.0446
|
| 306 |
+
- -5.1173
|
| 307 |
+
- -5.0325
|
| 308 |
+
- -5.1085
|
| 309 |
+
- -5.0053
|
| 310 |
+
- -5.0755
|
| 311 |
+
- -5.1176
|
| 312 |
+
- -5.1004
|
| 313 |
+
- -5.2153
|
| 314 |
+
- -5.2757
|
| 315 |
+
- -5.3025
|
| 316 |
+
- -5.2867
|
| 317 |
+
- -5.2918
|
| 318 |
+
- -5.3328
|
| 319 |
+
- -5.2731
|
| 320 |
+
- -5.2985
|
| 321 |
+
- -5.24
|
| 322 |
+
- -5.2211
|
| 323 |
+
task_cls: tasks.tts.diffspeech.DiffSpeechTask
|
| 324 |
+
tb_log_interval: 100
|
| 325 |
+
test_ids:
|
| 326 |
+
- 0
|
| 327 |
+
- 1
|
| 328 |
+
- 2
|
| 329 |
+
- 3
|
| 330 |
+
- 4
|
| 331 |
+
- 5
|
| 332 |
+
- 6
|
| 333 |
+
- 7
|
| 334 |
+
- 8
|
| 335 |
+
- 9
|
| 336 |
+
- 10
|
| 337 |
+
- 11
|
| 338 |
+
- 12
|
| 339 |
+
- 13
|
| 340 |
+
- 14
|
| 341 |
+
- 15
|
| 342 |
+
- 16
|
| 343 |
+
- 17
|
| 344 |
+
- 18
|
| 345 |
+
- 19
|
| 346 |
+
- 68
|
| 347 |
+
- 70
|
| 348 |
+
- 74
|
| 349 |
+
- 87
|
| 350 |
+
- 110
|
| 351 |
+
- 172
|
| 352 |
+
- 190
|
| 353 |
+
- 215
|
| 354 |
+
- 231
|
| 355 |
+
- 294
|
| 356 |
+
- 316
|
| 357 |
+
- 324
|
| 358 |
+
- 402
|
| 359 |
+
- 422
|
| 360 |
+
- 485
|
| 361 |
+
- 500
|
| 362 |
+
- 505
|
| 363 |
+
- 508
|
| 364 |
+
- 509
|
| 365 |
+
- 519
|
| 366 |
+
test_input_yaml: ''
|
| 367 |
+
test_num: 100
|
| 368 |
+
test_set_name: test
|
| 369 |
+
timesteps: 100
|
| 370 |
+
train_set_name: train
|
| 371 |
+
train_sets: ''
|
| 372 |
+
use_energy_embed: false
|
| 373 |
+
use_gt_dur: false
|
| 374 |
+
use_gt_energy: false
|
| 375 |
+
use_gt_f0: false
|
| 376 |
+
use_pitch_embed: true
|
| 377 |
+
use_pos_embed: true
|
| 378 |
+
use_spk_embed: false
|
| 379 |
+
use_spk_id: false
|
| 380 |
+
use_uv: true
|
| 381 |
+
use_word_input: false
|
| 382 |
+
val_check_interval: 2000
|
| 383 |
+
valid_infer_interval: 10000
|
| 384 |
+
valid_monitor_key: val_loss
|
| 385 |
+
valid_monitor_mode: min
|
| 386 |
+
valid_set_name: valid
|
| 387 |
+
vocoder: HifiGAN
|
| 388 |
+
vocoder_ckpt: checkpoints/hifi_lj
|
| 389 |
+
warmup_updates: 4000
|
| 390 |
+
weight_decay: 0
|
| 391 |
+
win_size: 1024
|
| 392 |
+
word_dict_size: 10000
|
| 393 |
+
work_dir: checkpoints/0214_ds
|
checkpoints/ds_exp/model_ckpt_steps_160000.ckpt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b41f14a72d74c706ffcda7ae319c3ad873cdc4313a8be47ed117b0c67e7c9aac
|
| 3 |
+
size 161932032
|
egs/datasets/audio/lj/ds.yaml
CHANGED
|
@@ -2,7 +2,7 @@ base_config:
|
|
| 2 |
- egs/egs_bases/tts/ds.yaml
|
| 3 |
- ./fs2_orig.yaml
|
| 4 |
|
| 5 |
-
fs2_ckpt: checkpoints/
|
| 6 |
|
| 7 |
# spec_min and spec_max are calculated on the training set.
|
| 8 |
spec_min: [ -4.7574, -4.6783, -4.6431, -4.5832, -4.5390, -4.6771, -4.8089, -4.7672,
|
|
|
|
| 2 |
- egs/egs_bases/tts/ds.yaml
|
| 3 |
- ./fs2_orig.yaml
|
| 4 |
|
| 5 |
+
fs2_ckpt: checkpoints/aux_exp/model_ckpt_steps_100000.ckpt
|
| 6 |
|
| 7 |
# spec_min and spec_max are calculated on the training set.
|
| 8 |
spec_min: [ -4.7574, -4.6783, -4.6431, -4.5832, -4.5390, -4.6771, -4.8089, -4.7672,
|
egs/egs_bases/tts/ds.yaml
CHANGED
|
@@ -28,5 +28,6 @@ keep_bins: 80
|
|
| 28 |
num_valid_plots: 10
|
| 29 |
use_gt_dur: false
|
| 30 |
use_gt_f0: false
|
|
|
|
| 31 |
#pitch_type: cwt
|
| 32 |
max_updates: 160000
|
|
|
|
| 28 |
num_valid_plots: 10
|
| 29 |
use_gt_dur: false
|
| 30 |
use_gt_f0: false
|
| 31 |
+
use_energy_embed: false
|
| 32 |
#pitch_type: cwt
|
| 33 |
max_updates: 160000
|
modules/tts/diffspeech/shallow_diffusion_tts.py
CHANGED
|
@@ -236,8 +236,6 @@ class GaussianDiffusion(nn.Module):
|
|
| 236 |
b, *_, device = *txt_tokens.shape, txt_tokens.device
|
| 237 |
ret = self.fs2(txt_tokens, mel2ph=mel2ph, spk_embed=spk_embed, spk_id=spk_id,
|
| 238 |
f0=f0, uv=uv, energy=energy, infer=infer, skip_decoder=(not infer), **kwargs)
|
| 239 |
-
# (txt_tokens, mel2ph, spk_embed, ref_mels, f0, uv, energy,
|
| 240 |
-
# skip_decoder=(not infer), infer=infer, **kwargs)
|
| 241 |
cond = ret['decoder_inp'].transpose(1, 2)
|
| 242 |
|
| 243 |
if not infer:
|
|
|
|
| 236 |
b, *_, device = *txt_tokens.shape, txt_tokens.device
|
| 237 |
ret = self.fs2(txt_tokens, mel2ph=mel2ph, spk_embed=spk_embed, spk_id=spk_id,
|
| 238 |
f0=f0, uv=uv, energy=energy, infer=infer, skip_decoder=(not infer), **kwargs)
|
|
|
|
|
|
|
| 239 |
cond = ret['decoder_inp'].transpose(1, 2)
|
| 240 |
|
| 241 |
if not infer:
|
tasks/tts/diffspeech.py
CHANGED
|
@@ -26,12 +26,12 @@ class DiffSpeechTask(FastSpeech2OrigTask):
|
|
| 26 |
self.model = GaussianDiffusion(dict_size, hparams)
|
| 27 |
if hparams['fs2_ckpt'] != '':
|
| 28 |
load_ckpt(self.model.fs2, hparams['fs2_ckpt'], 'model', strict=True)
|
| 29 |
-
for k, v in self.model.fs2.named_parameters():
|
| 30 |
-
if 'predictor' not in k:
|
| 31 |
-
v.requires_grad = False
|
| 32 |
-
# or
|
| 33 |
# for k, v in self.model.fs2.named_parameters():
|
| 34 |
-
#
|
|
|
|
|
|
|
|
|
|
|
|
|
| 35 |
|
| 36 |
def build_optimizer(self, model):
|
| 37 |
self.optimizer = optimizer = torch.optim.AdamW(
|
|
|
|
| 26 |
self.model = GaussianDiffusion(dict_size, hparams)
|
| 27 |
if hparams['fs2_ckpt'] != '':
|
| 28 |
load_ckpt(self.model.fs2, hparams['fs2_ckpt'], 'model', strict=True)
|
|
|
|
|
|
|
|
|
|
|
|
|
| 29 |
# for k, v in self.model.fs2.named_parameters():
|
| 30 |
+
# if 'predictor' not in k:
|
| 31 |
+
# v.requires_grad = False
|
| 32 |
+
# or
|
| 33 |
+
for k, v in self.model.fs2.named_parameters():
|
| 34 |
+
v.requires_grad = False
|
| 35 |
|
| 36 |
def build_optimizer(self, model):
|
| 37 |
self.optimizer = optimizer = torch.optim.AdamW(
|