adding rust

Languages/deu/G_100000.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf70a8d4b18a87bd237e1d8e5789f5dc3181d8cf577683cf0bacace87d44ffaa
+size 145489905

Languages/deu/config.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ec453d50be1976ddb3b501c7dc09128cdf360b83e5b0cf7dec68dc5caa460f49
+size 1887

Languages/deu/vocab.txt

@@ -0,0 +1,45 @@
+ 
+v
+2
+q
+g
+-
+f
+1
+8
+a
+h
+4
+ö
+3
+r
+m
+ä
+l
+n
+t
+ë
+d
+b
+y
+ß
+o
+u
+_
+j
+s
+6
+5
+ï
+c
+i
+ü
+p
+k
+e
+–
+w
+z
+7
+x
+0

app.py

@@ -23,7 +23,7 @@ from configurations.get_constants import constantConfig
 
 from speaker_encoder.voice_encoder import SpeakerEncoder
 
-from df.enhance import enhance, init_df, load_audio, save_audio
+from df_local.enhance import enhance, init_df, load_audio, save_audio
 from configurations.get_hyperparameters import hyperparameterConfig
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 

{df → df_local}/checkpoint.py

@@ -8,9 +8,9 @@ import torch
 from loguru import logger
 from torch import nn
 
-from df.config import Csv, config
-from df.model import init_model
-from df.utils import check_finite_module
+from df_local.config import Csv, config
+from df_local.model import init_model
+from df_local.utils import check_finite_module
 from libdf import DF
 
 

{df → df_local}/deepfilternet2.py

@@ -5,8 +5,8 @@ import torch
 from loguru import logger
 from torch import Tensor, nn
 
-from df.config import Csv, DfParams, config
-from df.modules import (
+from df_local.config import Csv, DfParams, config
+from df_local.modules import (
     Conv2dNormAct,
     ConvTranspose2dNormAct,
     DfOp,
@@ -18,7 +18,7 @@ from df.modules import (
     erb_fb,
     get_device,
 )
-from df.multiframe import MF_METHODS, MultiFrameModule
+from df_local.multiframe import MF_METHODS, MultiFrameModule
 from libdf import DF
 
 

{df → df_local}/enhance.py

@@ -12,13 +12,13 @@ from torch import Tensor, nn
 from torch.nn import functional as F
 from torchaudio.backend.common import AudioMetaData
 
-import df
-from df import config
-from df.checkpoint import load_model as load_model_cp
-from df.logger import init_logger, warn_once
-from df.model import ModelParams
-from df.modules import get_device
-from df.utils import as_complex, as_real, get_norm_alpha, resample
+import df_local
+from df_local import config
+from df_local.checkpoint import load_model as load_model_cp
+from df_local.logger import init_logger, warn_once
+from df_local.model import ModelParams
+from df_local.modules import get_device
+from df_local.utils import as_complex, as_real, get_norm_alpha, resample
 from libdf import DF, erb, erb_norm, unit_norm
 
 
@@ -100,7 +100,7 @@ def init_df(
         use_default_model = True
         model_base_dir = os.path.relpath(
             os.path.join(
-                os.path.dirname(df.__file__), os.pardir, "pretrained_models", default_model
+                os.path.dirname(df_local.__file__), os.pardir, "pretrained_models", default_model
             )
         )
     if not os.path.isdir(model_base_dir):

{df → df_local}/logger.py

@@ -10,8 +10,8 @@ import torch
 from loguru import logger
 from torch.types import Number
 
-from df.modules import GroupedLinearEinsum
-from df.utils import get_branch_name, get_commit_hash, get_device, get_host
+from df_local.modules import GroupedLinearEinsum
+from df_local.utils import get_branch_name, get_commit_hash, get_device, get_host
 
 _logger_initialized = False
 WARN_ONCE_NO = logger.level("WARNING").no + 1
@@ -171,7 +171,7 @@ def log_model_summary(model: torch.nn.Module, verbose=False):
         logger.debug("Failed to import ptflops. Cannot print model summary.")
         return
 
-    from df.model import ModelParams
+    from df_local.model import ModelParams
 
     # Generate input of 1 second audio
     # Necessary inputs are:

{df → df_local}/model.py

@@ -3,13 +3,13 @@ from importlib import import_module
 import torch
 from loguru import logger
 
-from df.config import DfParams, config
+from df_local.config import DfParams, config
 
 
 class ModelParams(DfParams):
     def __init__(self):
         self.__model = config("MODEL", default="deepfilternet", section="train")
-        self.__params = getattr(import_module("df." + self.__model), "ModelParams")()
+        self.__params = getattr(import_module("df_local." + self.__model), "ModelParams")()
 
     def __getattr__(self, attr: str):
         return getattr(self.__params, attr)
@@ -19,6 +19,6 @@ def init_model(*args, **kwargs):
     """Initialize the model specified in the config."""
     model = config("MODEL", default="deepfilternet", section="train")
     logger.info(f"Initializing model `{model}`")
-    model = getattr(import_module("df." + model), "init_model")(*args, **kwargs)
+    model = getattr(import_module("df_local." + model), "init_model")(*args, **kwargs)
     model.to(memory_format=torch.channels_last)
     return model

{df → df_local}/modules.py

@@ -10,8 +10,8 @@ from torch.nn import init
 from torch.nn.parameter import Parameter
 from typing_extensions import Final
 
-from df.model import ModelParams
-from df.utils import as_complex, as_real, get_device, get_norm_alpha
+from df_local.model import ModelParams
+from df_local.utils import as_complex, as_real, get_device, get_norm_alpha
 from libdf import unit_norm_init
 
 
@@ -875,7 +875,7 @@ def test_grouped_gru():
 
 def test_erb():
     import libdf
-    from df.config import config
+    from df_local.config import config
 
     config.use_defaults()
     p = ModelParams()
@@ -895,7 +895,7 @@ def test_erb():
 
 
 def test_unit_norm():
-    from df.config import config
+    from df_local.config import config
     from libdf import unit_norm
 
     config.use_defaults()
@@ -915,7 +915,7 @@ def test_unit_norm():
 
 
 def test_dfop():
-    from df.config import config
+    from df_local.config import config
 
     config.use_defaults()
     p = ModelParams()

{df → df_local}/utils.py

@@ -14,8 +14,8 @@ from torch import Tensor
 from torch.autograd import Function
 from torch.types import Number
 
-from df.config import config
-from df.model import ModelParams
+from df_local.config import config
+from df_local.model import ModelParams
 
 try:
     from torchaudio.functional import resample as ta_resample

requirements.txt

@@ -20,6 +20,8 @@ ctranslate2==3.18.0
 cycler==0.11.0
 Cython==3.0.0
 decorator==5.1.1
+DeepFilterLib==0.2.4
+deepfilternet==0.2.4
 executing==1.2.0
 fastapi==0.101.1
 faster-whisper==0.7.1