Add Suno bark

mlx_audio/codec/models/encodec/__init__.py

@@ -1 +1 @@
-from .encodec import Encodec
+from .encodec import Encodec, EncodecConfig

mlx_audio/codec/models/encodec/encodec.py

@@ -1,6 +1,7 @@
 import functools
 import json
 import math
+from dataclasses import dataclass
 from pathlib import Path
 from types import SimpleNamespace
 from typing import List, Optional, Tuple, Union
@@ -11,6 +12,40 @@
 from huggingface_hub import snapshot_download
 
 
+def filter_dataclass_fields(data_dict, dataclass_type):
+    """Filter a dictionary to only include keys that are fields in the dataclass."""
+    valid_fields = {f.name for f in dataclass_type.__dataclass_fields__.values()}
+    return {k: v for k, v in data_dict.items() if k in valid_fields}
+
+
+@dataclass
+class EncodecConfig:
+    model_type: str = "encodec"
+    audio_channels: int = 1
+    num_filters: int = 32
+    kernel_size: int = 7
+    num_residual_layers: int = 1
+    dilation_growth_rate: int = 2
+    codebook_size: int = 1024
+    codebook_dim: int = 128
+    hidden_size: int = 128
+    num_lstm_layers: int = 2
+    residual_kernel_size: int = 3
+    use_causal_conv: bool = True
+    normalize: bool = False
+    pad_mode: str = "reflect"
+    norm_type: str = "weight_norm"
+    last_kernel_size: int = 7
+    trim_right_ratio: float = 1.0
+    compress: int = 2
+    upsampling_ratios: List[int] = None
+    target_bandwidths: List[float] = None
+    sampling_rate: int = 24000
+    chunk_length_s: Optional[float] = None
+    overlap: Optional[float] = None
+    architectures: List[str] = None
+
+
 def preprocess_audio(
     raw_audio: Union[mx.array, List[mx.array]],
     sampling_rate: int = 24000,
@@ -513,7 +548,7 @@ def decode(self, codes: mx.array) -> mx.array:
 class Encodec(nn.Module):
     def __init__(self, config):
         super().__init__()
-        self.config = SimpleNamespace(**config)
+        self.config = config
         self.encoder = EncodecEncoder(self.config)
         self.decoder = EncodecDecoder(self.config)
         self.quantizer = EncodecResidualVectorQuantizer(self.config)
@@ -689,6 +724,8 @@ def from_pretrained(cls, path_or_repo: str):
         with open(path / "config.json", "r") as f:
             config = json.load(f)
 
+        filtered_config = filter_dataclass_fields(config, EncodecConfig)
+        config = EncodecConfig(**filtered_config)
         model = cls(config)
         model.load_weights(str(path / "model.safetensors"))
         processor = functools.partial(

mlx_audio/codec/tests/test_encodec.py

@@ -2,33 +2,33 @@
 
 import mlx.core as mx
 
-from ..models.encodec import Encodec
-
-config = {
-    "audio_channels": 1,
-    "chunk_length_s": None,
-    "codebook_dim": 128,
-    "codebook_size": 1024,
-    "compress": 2,
-    "dilation_growth_rate": 2,
-    "hidden_size": 128,
-    "kernel_size": 7,
-    "last_kernel_size": 7,
-    "model_type": "encodec",
-    "norm_type": "weight_norm",
-    "normalize": False,
-    "num_filters": 32,
-    "num_lstm_layers": 2,
-    "num_residual_layers": 1,
-    "overlap": None,
-    "pad_mode": "reflect",
-    "residual_kernel_size": 3,
-    "sampling_rate": 24000,
-    "target_bandwidths": [1.5, 3.0, 6.0, 12.0, 24.0],
-    "trim_right_ratio": 1.0,
-    "upsampling_ratios": [8, 5, 4, 2],
-    "use_causal_conv": True,
-}
+from ..models.encodec import Encodec, EncodecConfig
+
+config = EncodecConfig(
+    audio_channels=1,
+    chunk_length_s=None,
+    codebook_dim=128,
+    codebook_size=1024,
+    compress=2,
+    dilation_growth_rate=2,
+    hidden_size=128,
+    kernel_size=7,
+    last_kernel_size=7,
+    model_type="encodec",
+    norm_type="weight_norm",
+    normalize=False,
+    num_filters=32,
+    num_lstm_layers=2,
+    num_residual_layers=1,
+    overlap=None,
+    pad_mode="reflect",
+    residual_kernel_size=3,
+    sampling_rate=24000,
+    target_bandwidths=[1.5, 3.0, 6.0, 12.0, 24.0],
+    trim_right_ratio=1.0,
+    upsampling_ratios=[8, 5, 4, 2],
+    use_causal_conv=True,
+)
 
 
 class TesEncodec(unittest.TestCase):

mlx_audio/tts/generate.py

@@ -24,7 +24,8 @@ def generate_audio(
     join_audio: bool = False,
     play: bool = False,
     verbose: bool = True,
-    from_cli: bool = False,
+    temperature: float = 0.7,
+    **kwargs,
 ) -> None:
     """
     Generates audio from text using a specified TTS model.
@@ -85,6 +86,7 @@ def generate_audio(
             lang_code=lang_code,
             ref_audio=ref_audio,
             ref_text=ref_text,
+            temperature=temperature,
             verbose=True,
         )
 
@@ -154,7 +156,7 @@ def parse_args():
         default=None,
         help="Text to generate (leave blank to input via stdin)",
     )
-    parser.add_argument("--voice", type=str, default="af_heart", help="Voice name")
+    parser.add_argument("--voice", type=str, default=None, help="Voice name")
     parser.add_argument("--speed", type=float, default=1.0, help="Speed of the audio")
     parser.add_argument("--lang_code", type=str, default="a", help="Language code")
     parser.add_argument(
@@ -177,6 +179,9 @@ def parse_args():
     parser.add_argument(
         "--ref_text", type=str, default=None, help="Caption for reference audio"
     )
+    parser.add_argument(
+        "--temperature", type=float, default=0.7, help="Temperature for the model"
+    )
 
     args = parser.parse_args()
 

mlx_audio/tts/models/bark/__init__.py

@@ -0,0 +1,4 @@
+from .bark import Model, ModelConfig
+from .pipeline import Pipeline
+
+__all__ = ["Model", "Pipeline", "ModelConfig"]