Add static cache

helpers/gradio_demo/app.py

@@ -1,8 +1,9 @@
 import gradio as gr
 import torch
+from transformers import AutoFeatureExtractor, AutoTokenizer, set_seed
 
 from parler_tts import ParlerTTSForConditionalGeneration
-from transformers import AutoTokenizer, AutoFeatureExtractor, set_seed
+
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
@@ -57,7 +58,7 @@ def gen_tts(text, description):
             background-color: #000000;
             justify-content: center;
             align-items: center;
-            border-radius: 9999px !important; 
+            border-radius: 9999px !important;
             width: 13rem;
             margin-top: 10px;
             margin-left: auto;

helpers/model_init_scripts/init_dummy_model.py

@@ -1,7 +1,9 @@
-from parler_tts import ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration, ParlerTTSDecoderConfig
-from transformers import AutoConfig
-import os
 import argparse
+import os
+
+from transformers import AutoConfig
+
+from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
 
 
 if __name__ == "__main__":

helpers/model_init_scripts/init_dummy_model_with_encodec.py

@@ -1,7 +1,10 @@
-from parler_tts import ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration, ParlerTTSDecoderConfig
-from transformers import AutoConfig
-import os
 import argparse
+import os
+
+from transformers import AutoConfig
+
+from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
+
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()

helpers/model_init_scripts/init_model_600M.py

@@ -1,7 +1,9 @@
-from parler_tts import ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration, ParlerTTSDecoderConfig
-from transformers import AutoConfig
-import os
 import argparse
+import os
+
+from transformers import AutoConfig
+
+from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
 
 
 if __name__ == "__main__":

helpers/push_to_hub_scripts/push_dac_to_hub.py

@@ -1,4 +1,6 @@
 import dac
+from transformers import AutoConfig, AutoModel, EncodecFeatureExtractor
+
 from parler_tts import DACConfig, DACModel
 from transformers import AutoConfig, AutoModel
 from transformers import EncodecFeatureExtractor

helpers/push_to_hub_scripts/push_trained_parler_tts_to_hub.py

@@ -1,5 +1,7 @@
+from transformers import AutoFeatureExtractor, AutoTokenizer
+
 from parler_tts import ParlerTTSForConditionalGeneration
-from transformers import AutoTokenizer, AutoFeatureExtractor
+
 
 path = "TODO"
 repo_id = "parler_tts_600M"

parler_tts/__init__.py

@@ -1,16 +1,17 @@
 __version__ = "0.1"
 
 
+from transformers import AutoConfig, AutoModel
+
 from .configuration_parler_tts import ParlerTTSConfig, ParlerTTSDecoderConfig
+from .dac_wrapper import DACConfig, DACModel
 from .modeling_parler_tts import (
     ParlerTTSForCausalLM,
     ParlerTTSForConditionalGeneration,
     apply_delay_pattern_mask,
     build_delay_pattern_mask,
 )
 
-from .dac_wrapper import DACConfig, DACModel
-from transformers import AutoConfig, AutoModel
 
 AutoConfig.register("dac", DACConfig)
 AutoModel.register(DACConfig, DACModel)

parler_tts/dac_wrapper/configuration_dac.py

@@ -1,5 +1,5 @@
+
 from transformers import PretrainedConfig
-from typing import List
 
 
 class DACConfig(PretrainedConfig):

parler_tts/dac_wrapper/modeling_dac.py

@@ -1,10 +1,9 @@
 import torch
-
+from dac.model import DAC
 from transformers import PreTrainedModel
-from transformers.models.encodec.modeling_encodec import EncodecEncoderOutput, EncodecDecoderOutput
-from .configuration_dac import DACConfig
+from transformers.models.encodec.modeling_encodec import EncodecDecoderOutput, EncodecEncoderOutput
 
-from dac.model import DAC
+from .configuration_dac import DACConfig
 
 
 # model doesn't support batching yet
@@ -79,7 +78,7 @@ def encode(
             )
 
         for offset in range(0, input_length - step, stride):
-            mask = padding_mask[..., offset : offset + chunk_length].bool()
+            padding_mask[..., offset : offset + chunk_length].bool()
             frame = audio_data[:, :, offset : offset + chunk_length]
 
             scale = None
@@ -134,4 +133,4 @@ def decode(
         return EncodecDecoderOutput(audio_values)
 
     def forward(self, tensor):
-        raise ValueError(f"`DACModel.forward` not implemented yet")
+        raise ValueError("`DACModel.forward` not implemented yet")