Medix-AI/coqui-tts
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Add docs and missing files

This commit is contained in:
Eren G??lge 2023-05-23 13:24:48 +02:00
parent fb31ce4b0a
commit 92d4823ad4
2 changed files with 66 additions and 3 deletions
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21
TTS/tts/models/vits.py
View File

@ -1725,22 +1725,37 @@ class Vits(BaseTTS):
assert not self.training
def load_fairseq_checkpoint(self, config, checkpoint_dir, eval=False):
"""Load VITS checkpoints released by fairseq here: https://github.com/facebookresearch/fairseq/tree/main/examples/mms
Performs some changes for compatibility.
Args:
config (Coqpit): 🐸TTS model config.
checkpoint_dir (str): Path to the checkpoint directory.
eval (bool, optional): Set to True for evaluation. Defaults to False.
"""
import json
# set paths
config_file = os.path.join(checkpoint_dir, "config.json")
checkpoint_file = os.path.join(checkpoint_dir, "G_100000.pth")
vocab_file = os.path.join(checkpoint_dir, "vocab.txt")
# set config params
with open(config_file, 'r') as file:
with open(config_file, "r") as file:
# Load the JSON data as a dictionary
config_org = json.load(file)
self.config.audio.sample_rate = config_org['data']['sampling_rate']
self.config.audio.sample_rate = config_org["data"]["sampling_rate"]
# self.config.add_blank = config['add_blank']
# set tokenizer
vocab = FairseqVocab(vocab_file)
self.text_encoder.emb = nn.Embedding(vocab.num_chars, config.model_args.hidden_channels)
self.tokenizer = TTSTokenizer(
use_phonemes=False, text_cleaner=None, characters=vocab, phonemizer=None, add_blank=config_org['data']['add_blank'], use_eos_bos=False
use_phonemes=False,
text_cleaner=None,
characters=vocab,
phonemizer=None,
add_blank=config_org["data"]["add_blank"],
use_eos_bos=False,
)
# load fairseq checkpoint
new_chk = rehash_fairseq_vits_checkpoint(checkpoint_file)

48
TTS/tts/utils/fairseq.py Normal file
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@ -0,0 +1,48 @@
import torch
def rehash_fairseq_vits_checkpoint(checkpoint_file):
chk = torch.load(checkpoint_file)["model"]
new_chk = {}
for k, v in chk.items():
if "enc_p." in k:
new_chk[k.replace("enc_p.", "text_encoder.")] = v
elif "dec." in k:
new_chk[k.replace("dec.", "waveform_decoder.")] = v
elif "enc_q." in k:
new_chk[k.replace("enc_q.", "posterior_encoder.")] = v
elif "flow.flows.2." in k:
new_chk[k.replace("flow.flows.2.", "flow.flows.1.")] = v
elif "flow.flows.4." in k:
new_chk[k.replace("flow.flows.4.", "flow.flows.2.")] = v
elif "flow.flows.6." in k:
new_chk[k.replace("flow.flows.6.", "flow.flows.3.")] = v
elif "dp.flows.0.m" in k:
new_chk[k.replace("dp.flows.0.m", "duration_predictor.flows.0.translation")] = v
elif "dp.flows.0.logs" in k:
new_chk[k.replace("dp.flows.0.logs", "duration_predictor.flows.0.log_scale")] = v
elif "dp.flows.1" in k:
new_chk[k.replace("dp.flows.1", "duration_predictor.flows.1")] = v
elif "dp.flows.3" in k:
new_chk[k.replace("dp.flows.3", "duration_predictor.flows.2")] = v
elif "dp.flows.5" in k:
new_chk[k.replace("dp.flows.5", "duration_predictor.flows.3")] = v
elif "dp.flows.7" in k:
new_chk[k.replace("dp.flows.7", "duration_predictor.flows.4")] = v
elif "dp.post_flows.0.m" in k:
new_chk[k.replace("dp.post_flows.0.m", "duration_predictor.post_flows.0.translation")] = v
elif "dp.post_flows.0.logs" in k:
new_chk[k.replace("dp.post_flows.0.logs", "duration_predictor.post_flows.0.log_scale")] = v
elif "dp.post_flows.1" in k:
new_chk[k.replace("dp.post_flows.1", "duration_predictor.post_flows.1")] = v
elif "dp.post_flows.3" in k:
new_chk[k.replace("dp.post_flows.3", "duration_predictor.post_flows.2")] = v
elif "dp.post_flows.5" in k:
new_chk[k.replace("dp.post_flows.5", "duration_predictor.post_flows.3")] = v
elif "dp.post_flows.7" in k:
new_chk[k.replace("dp.post_flows.7", "duration_predictor.post_flows.4")] = v
elif "dp." in k:
new_chk[k.replace("dp.", "duration_predictor.")] = v
else:
new_chk[k] = v
return new_chk