From 0c3cc5ebad3b2ef22d21028d9ac8fa23c0bb8ed8 Mon Sep 17 00:00:00 2001 From: James Betker Date: Sat, 12 Feb 2022 20:00:46 -0700 Subject: [PATCH] use script updates to fix output size disparities --- codes/scripts/audio/gen/use_diffuse_tts.py | 30 +++++++++++++------ .../gen/use_diffuse_voice_translation.py | 9 +++--- 2 files changed, 26 insertions(+), 13 deletions(-) diff --git a/codes/scripts/audio/gen/use_diffuse_tts.py b/codes/scripts/audio/gen/use_diffuse_tts.py index 08a0fbec..4d787a94 100644 --- a/codes/scripts/audio/gen/use_diffuse_tts.py +++ b/codes/scripts/audio/gen/use_diffuse_tts.py @@ -9,6 +9,7 @@ from scripts.audio.gen.speech_synthesis_utils import do_spectrogram_diffusion, \ load_discrete_vocoder_diffuser, wav_to_mel, convert_mel_to_codes from utils.audio import plot_spectrogram from utils.util import load_model_from_config +import torch.nn.functional as F def ceil_multiple(base, multiple): @@ -18,6 +19,18 @@ def ceil_multiple(base, multiple): return base + (multiple - res) +def determine_output_size(codes, base_sample_rate): + aligned_codes_compression_factor = base_sample_rate * 221 // 11025 + output_size = codes.shape[-1]*aligned_codes_compression_factor + padded_size = ceil_multiple(output_size, 2048) + padding_added = padded_size - output_size + padding_needed_for_codes = padding_added // aligned_codes_compression_factor + if padding_needed_for_codes > 0: + codes = F.pad(codes, (0, padding_needed_for_codes)) + output_shape = (1, 1, padded_size) + return output_shape, codes + + if __name__ == '__main__': conditioning_clips = { # Male @@ -25,6 +38,7 @@ if __name__ == '__main__': 'carlin': 'Y:\\clips\\books1\\12_dchha13 Bubonic Nukes\\00097.wav', 'entangled': 'Y:\\clips\\books1\\3857_25_The_Entangled_Bank__000000000\\00123.wav', 'snowden': 'Y:\\clips\\books1\\7658_Edward_Snowden_-_Permanent_Record__000000004\\00027.wav', + 'plants': 'Y:\\clips\\books1\\12028_The_Secret_Life_of_Plants_-_18__000000000\\00399.wav', # Female 'the_doctor': 'Y:\\clips\\books2\\37062___The_Doctor__000000003\\00206.wav', 'puppy': 'Y:\\clips\\books2\\17830___3_Puppy_Kisses__000000002\\00046.wav', @@ -112,17 +126,17 @@ if __name__ == '__main__': ] parser = argparse.ArgumentParser() - parser.add_argument('-text', type=str, help='Text to speak.', default='instead of molten iron, jupiter and brown dwarfs have hydrogen, which is under so much pressure that it develops metallic properties.') - parser.add_argument('-opt_code_gen', type=str, help='Path to options YAML file used to train the code_gen model', default='D:\\dlas\\experiments\\train_encoder_build_ctc_alignments_medium\\train_encoder_build_ctc_alignments.yml') + parser.add_argument('-text', type=str, help='Text to speak.', default='my father worked at the airport. he was air traffic control. he always knew when the president was flying in but was not allowed to tell anyone.') + parser.add_argument('-opt_code_gen', type=str, help='Path to options YAML file used to train the code_gen model', default='D:\\dlas\\options\\train_encoder_build_ctc_alignments.yml') parser.add_argument('-code_gen_model_name', type=str, help='Name of the code_gen model in opt.', default='generator') - parser.add_argument('-code_gen_model_path', type=str, help='Path to saved code_gen model weights', default='D:\\dlas\\experiments\\train_encoder_build_ctc_alignments_medium\\models\\32000_generator_ema.pth') - parser.add_argument('-opt', type=str, help='Path to options YAML file used to train the diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium.yml') + parser.add_argument('-code_gen_model_path', type=str, help='Path to saved code_gen model weights', default='D:\\dlas\\experiments\\train_encoder_build_ctc_alignments_medium\\models\\50000_generator_ema.pth') + parser.add_argument('-opt', type=str, help='Path to options YAML file used to train the diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium\\train_diffusion_tts5_medium.yml') parser.add_argument('-diffusion_model_name', type=str, help='Name of the diffusion model in opt.', default='generator') parser.add_argument('-diffusion_model_path', type=str, help='Path to saved model weights', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium\\models\\73000_generator_ema.pth') parser.add_argument('-sr_opt', type=str, help='Path to options YAML file used to train the SR diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample.yml') parser.add_argument('-sr_diffusion_model_name', type=str, help='Name of the SR diffusion model in opt.', default='generator') - parser.add_argument('-sr_diffusion_model_path', type=str, help='Path to saved model weights for the SR diffuser', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample_continued\\models\\45000_generator_ema.pth') - parser.add_argument('-cond', type=str, help='Type of conditioning voice', default='the_doctor') + parser.add_argument('-sr_diffusion_model_path', type=str, help='Path to saved model weights for the SR diffuser', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample_continued\\models\\53500_generator_ema.pth') + parser.add_argument('-cond', type=str, help='Type of conditioning voice', default='plants') parser.add_argument('-diffusion_steps', type=int, help='Number of diffusion steps to perform to create the generate. Lower steps reduces quality, but >40 is generally pretty good.', default=100) parser.add_argument('-output_path', type=str, help='Where to store outputs.', default='../results/use_diffuse_tts') parser.add_argument('-device', type=str, help='Device to run on', default='cuda') @@ -135,8 +149,6 @@ if __name__ == '__main__': print("Loading provided conditional audio..") sr_cond = load_audio(conditioning_clips[args.cond], sr_sample_rate).to(args.device) - if sr_cond.shape[-1] > 88000: - sr_cond = sr_cond[:,:88000] cond_mel = wav_to_mel(sr_cond) cond = torchaudio.functional.resample(sr_cond, sr_sample_rate, base_sample_rate) torchaudio.save(os.path.join(args.output_path, 'cond_base.wav'), cond.cpu(), base_sample_rate) @@ -163,7 +175,7 @@ if __name__ == '__main__': aligned_codes = code.to(args.device) print("Performing initial diffusion..") - output_shape = (1, 1, ceil_multiple(aligned_codes.shape[-1]*aligned_codes_compression_factor, 2048)) + output_shape, aligned_codes = determine_output_size(aligned_codes, base_sample_rate) diffusion = diffusion.cuda() output_base = diffuser.p_sample_loop(diffusion, output_shape, noise=torch.zeros(output_shape, device=args.device), model_kwargs={'tokens': aligned_codes, diff --git a/codes/scripts/audio/gen/use_diffuse_voice_translation.py b/codes/scripts/audio/gen/use_diffuse_voice_translation.py index 61bf9dce..e2aded88 100644 --- a/codes/scripts/audio/gen/use_diffuse_voice_translation.py +++ b/codes/scripts/audio/gen/use_diffuse_voice_translation.py @@ -28,7 +28,7 @@ def get_ctc_codes_for(src_clip_path): return torch.argmax(logits, dim=-1), clip -def determine_output_size(codes, base_sample_rate) +def determine_output_size(codes, base_sample_rate): aligned_codes_compression_factor = base_sample_rate * 221 // 11025 output_size = codes.shape[-1]*aligned_codes_compression_factor padded_size = ceil_multiple(output_size, 2048) @@ -47,6 +47,7 @@ if __name__ == '__main__': 'carlin': 'Y:\\clips\\books1\\12_dchha13 Bubonic Nukes\\00097.wav', 'entangled': 'Y:\\clips\\books1\\3857_25_The_Entangled_Bank__000000000\\00123.wav', 'snowden': 'Y:\\clips\\books1\\7658_Edward_Snowden_-_Permanent_Record__000000004\\00027.wav', + 'plants': 'Y:\\clips\\books1\\12028_The_Secret_Life_of_Plants_-_18__000000000\\00399.wav', # Female 'the_doctor': 'Y:\\clips\\books2\\37062___The_Doctor__000000003\\00206.wav', 'puppy': 'Y:\\clips\\books2\\17830___3_Puppy_Kisses__000000002\\00046.wav', @@ -55,13 +56,13 @@ if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-src_clip', type=str, help='Path to the audio files to translate', default='D:\\tortoise-tts\\voices') - parser.add_argument('-opt', type=str, help='Path to options YAML file used to train the diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium.yml') + parser.add_argument('-opt', type=str, help='Path to options YAML file used to train the diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium\\train_diffusion_tts5_medium.yml') parser.add_argument('-diffusion_model_name', type=str, help='Name of the diffusion model in opt.', default='generator') parser.add_argument('-diffusion_model_path', type=str, help='Path to saved model weights', default='X:\\dlas\\experiments\\train_diffusion_tts5_medium\\models\\73000_generator_ema.pth') parser.add_argument('-sr_opt', type=str, help='Path to options YAML file used to train the SR diffusion model', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample.yml') parser.add_argument('-sr_diffusion_model_name', type=str, help='Name of the SR diffusion model in opt.', default='generator') - parser.add_argument('-sr_diffusion_model_path', type=str, help='Path to saved model weights for the SR diffuser', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample_continued\\models\\45000_generator_ema.pth') - parser.add_argument('-voice', type=str, help='Type of conditioning voice', default='simmons') + parser.add_argument('-sr_diffusion_model_path', type=str, help='Path to saved model weights for the SR diffuser', default='X:\\dlas\\experiments\\train_diffusion_tts6_upsample_continued\\models\\53500_generator_ema.pth') + parser.add_argument('-voice', type=str, help='Type of conditioning voice', default='plants') parser.add_argument('-diffusion_steps', type=int, help='Number of diffusion steps to perform to create the generate. Lower steps reduces quality, but >40 is generally pretty good.', default=100) parser.add_argument('-output_path', type=str, help='Where to store outputs.', default='../results/use_diffuse_voice_translation') parser.add_argument('-device', type=str, help='Device to run on', default='cuda')