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Remove omegaconf #129

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1e37b35
Update s3gen.py
BBC-Esq Jun 7, 2025
65b718d
Update flow.py
BBC-Esq Jun 7, 2025
530e9d0
Update flow_matching.py
BBC-Esq Jun 7, 2025
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101 changes: 77 additions & 24 deletions src/chatterbox/models/s3gen/flow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,10 +14,10 @@
import logging
import random
from typing import Dict, Optional
from types import SimpleNamespace
import torch
import torch.nn as nn
from torch.nn import functional as F
from omegaconf import DictConfig
from .utils.mask import make_pad_mask


Expand All @@ -33,13 +33,38 @@ def __init__(self,
encoder: torch.nn.Module = None,
length_regulator: torch.nn.Module = None,
decoder: torch.nn.Module = None,
decoder_conf: Dict = {'in_channels': 240, 'out_channel': 80, 'spk_emb_dim': 80, 'n_spks': 1,
'cfm_params': DictConfig({'sigma_min': 1e-06, 'solver': 'euler', 't_scheduler': 'cosine',
'training_cfg_rate': 0.2, 'inference_cfg_rate': 0.7, 'reg_loss_type': 'l1'}),
'decoder_params': {'channels': [256, 256], 'dropout': 0.0, 'attention_head_dim': 64,
'n_blocks': 4, 'num_mid_blocks': 12, 'num_heads': 8, 'act_fn': 'gelu'}},
mel_feat_conf: Dict = {'n_fft': 1024, 'num_mels': 80, 'sampling_rate': 22050,
'hop_size': 256, 'win_size': 1024, 'fmin': 0, 'fmax': 8000}):
decoder_conf: Dict = {
'in_channels': 240,
'out_channel': 80,
'spk_emb_dim': 80,
'n_spks': 1,
'cfm_params': SimpleNamespace(
sigma_min=1e-6,
solver='euler',
t_scheduler='cosine',
training_cfg_rate=0.2,
inference_cfg_rate=0.7,
reg_loss_type='l1',
),
'decoder_params': {
'channels': [256, 256],
'dropout': 0.0,
'attention_head_dim': 64,
'n_blocks': 4,
'num_mid_blocks': 12,
'num_heads': 8,
'act_fn': 'gelu',
},
},
mel_feat_conf: Dict = {
'n_fft': 1024,
'num_mels': 80,
'sampling_rate': 22050,
'hop_size': 256,
'win_size': 1024,
'fmin': 0,
'fmax': 8000,
}):
super().__init__()
self.input_size = input_size
self.output_size = output_size
Expand All @@ -56,6 +81,7 @@ def __init__(self,
self.decoder = decoder
self.length_regulator = length_regulator
self.only_mask_loss = only_mask_loss
self.fp16 = False # (preserves existing behaviour)

def forward(
self,
Expand Down Expand Up @@ -111,7 +137,7 @@ def inference(self,
prompt_feat_len,
embedding,
flow_cache):
if self.fp16 is True:
if self.fp16:
prompt_feat = prompt_feat.half()
embedding = embedding.half()

Expand All @@ -129,8 +155,11 @@ def inference(self,
# text encode
h, h_lengths = self.encoder(token, token_len)
h = self.encoder_proj(h)
mel_len1, mel_len2 = prompt_feat.shape[1], int(token_len2 / self.input_frame_rate * 22050 / 256)
h, h_lengths = self.length_regulator.inference(h[:, :token_len1], h[:, token_len1:], mel_len1, mel_len2, self.input_frame_rate)
mel_len1 = prompt_feat.shape[1]
mel_len2 = int(token_len2 / self.input_frame_rate * 22050 / 256)
h, h_lengths = self.length_regulator.inference(
h[:, :token_len1], h[:, token_len1:], mel_len1, mel_len2, self.input_frame_rate
)

# get conditions
conds = torch.zeros([1, mel_len1 + mel_len2, self.output_size], device=token.device).to(h.dtype)
Expand Down Expand Up @@ -165,13 +194,38 @@ def __init__(self,
pre_lookahead_len: int = 3,
encoder: torch.nn.Module = None,
decoder: torch.nn.Module = None,
decoder_conf: Dict = {'in_channels': 240, 'out_channel': 80, 'spk_emb_dim': 80, 'n_spks': 1,
'cfm_params': DictConfig({'sigma_min': 1e-06, 'solver': 'euler', 't_scheduler': 'cosine',
'training_cfg_rate': 0.2, 'inference_cfg_rate': 0.7, 'reg_loss_type': 'l1'}),
'decoder_params': {'channels': [256, 256], 'dropout': 0.0, 'attention_head_dim': 64,
'n_blocks': 4, 'num_mid_blocks': 12, 'num_heads': 8, 'act_fn': 'gelu'}},
mel_feat_conf: Dict = {'n_fft': 1024, 'num_mels': 80, 'sampling_rate': 22050,
'hop_size': 256, 'win_size': 1024, 'fmin': 0, 'fmax': 8000}):
decoder_conf: Dict = {
'in_channels': 240,
'out_channel': 80,
'spk_emb_dim': 80,
'n_spks': 1,
'cfm_params': SimpleNamespace(
sigma_min=1e-6,
solver='euler',
t_scheduler='cosine',
training_cfg_rate=0.2,
inference_cfg_rate=0.7,
reg_loss_type='l1',
),
'decoder_params': {
'channels': [256, 256],
'dropout': 0.0,
'attention_head_dim': 64,
'n_blocks': 4,
'num_mid_blocks': 12,
'num_heads': 8,
'act_fn': 'gelu',
},
},
mel_feat_conf: Dict = {
'n_fft': 1024,
'num_mels': 80,
'sampling_rate': 22050,
'hop_size': 256,
'win_size': 1024,
'fmin': 0,
'fmax': 8000,
}):
super().__init__()
self.input_size = input_size
self.output_size = output_size
Expand All @@ -189,9 +243,7 @@ def __init__(self,
self.only_mask_loss = only_mask_loss
self.token_mel_ratio = token_mel_ratio
self.pre_lookahead_len = pre_lookahead_len

# FIXME: this was missing - just putting it in as false
self.fp16 = False
self.fp16 = False # ensures attribute exists

@torch.inference_mode()
def inference(self,
Expand All @@ -203,7 +255,7 @@ def inference(self,
prompt_feat_len,
embedding,
finalize):
if self.fp16 is True:
if self.fp16:
prompt_feat = prompt_feat.half()
embedding = embedding.half()

Expand All @@ -219,9 +271,10 @@ def inference(self,

# text encode
h, h_lengths = self.encoder(token, token_len)
if finalize is False:
if not finalize:
h = h[:, :-self.pre_lookahead_len * self.token_mel_ratio]
mel_len1, mel_len2 = prompt_feat.shape[1], h.shape[1] - prompt_feat.shape[1]
mel_len1 = prompt_feat.shape[1]
mel_len2 = h.shape[1] - mel_len1
h = self.encoder_proj(h)

# get conditions
Expand Down
18 changes: 9 additions & 9 deletions src/chatterbox/models/s3gen/flow_matching.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,17 +15,17 @@
import torch
import torch.nn.functional as F
from .matcha.flow_matching import BASECFM
from omegaconf import OmegaConf
from types import SimpleNamespace


CFM_PARAMS = OmegaConf.create({
"sigma_min": 1e-06,
"solver": "euler",
"t_scheduler": "cosine",
"training_cfg_rate": 0.2,
"inference_cfg_rate": 0.7,
"reg_loss_type": "l1"
})
CFM_PARAMS = SimpleNamespace(
sigma_min=1e-6,
solver="euler",
t_scheduler="cosine",
training_cfg_rate=0.2,
inference_cfg_rate=0.7,
reg_loss_type="l1",
)


class ConditionalCFM(BASECFM):
Expand Down
18 changes: 9 additions & 9 deletions src/chatterbox/models/s3gen/s3gen.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@
import torchaudio as ta
from functools import lru_cache
from typing import Optional
from omegaconf import DictConfig
from types import SimpleNamespace

from ..s3tokenizer import S3_SR, SPEECH_VOCAB_SIZE, S3Tokenizer
from .const import S3GEN_SR
Expand Down Expand Up @@ -85,14 +85,14 @@ def __init__(self):
num_heads=8,
act_fn='gelu',
)
cfm_params = DictConfig({
"sigma_min": 1e-06,
"solver": 'euler',
"t_scheduler": 'cosine',
"training_cfg_rate": 0.2,
"inference_cfg_rate": 0.7,
"reg_loss_type": 'l1',
})
cfm_params = SimpleNamespace(
sigma_min=1e-6,
solver='euler',
t_scheduler='cosine',
training_cfg_rate=0.2,
inference_cfg_rate=0.7,
reg_loss_type='l1',
)
decoder = CausalConditionalCFM(
spk_emb_dim=80,
cfm_params=cfm_params,
Expand Down