Clearer message on missing model files
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erew123 authored and GitHub committed
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commit
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@@ -79,7 +79,7 @@ def install_and_restart():
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raise ImportError("Could not install required packages")
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try:
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from f5_tts.model import CFM, DiT, UNetT
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from f5_tts.model import CFM, DiT
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from f5_tts.model.utils import (
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get_tokenizer,
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convert_char_to_pinyin,
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@@ -190,21 +190,14 @@ class tts_class:
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self.sway_sampling_coef = -1.0
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self.speed = 1.0
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# F5-TTS model configuration
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self.f5_model_cfg = dict(
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self.model_cfg = dict(
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dim=1024,
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depth=22,
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heads=16,
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ff_mult=2,
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text_dim=512,
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conv_layers=4
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)
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# Add E2-TTS model configuration
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self.e2_model_cfg = dict(
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dim=1024,
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depth=24,
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heads=16,
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ff_mult=4
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)
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)
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################################################################
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# DONT CHANGE # Print out Python, CUDA, DeepSpeed versions ####
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################################################################
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@@ -394,7 +387,7 @@ class tts_class:
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return self.available_models
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# Look for model directories that match the pattern f5tts_v*
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for model_dir in models_dir.glob("*tts_v*"):
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for model_dir in models_dir.glob("f5tts_v*"):
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if model_dir.is_dir():
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# First try to find model_*.safetensors files
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model_files = list(model_dir.glob("model_*.safetensors"))
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@@ -501,6 +494,8 @@ class tts_class:
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model_files = list(model_dir.glob("*.safetensors"))
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if not model_files:
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print(f"[{self.branding}ENG] \033[91mError\033[0m: No model's safetensors file was found in the F5-TTS models directory.")
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print(f"[{self.branding}ENG] \033[93mPlease download an F5-TTS model file in the Gradio interface section for the F5-TTS engine.\033[0m")
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raise FileNotFoundError("No safetensors model file found in the model directory")
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# Use the first found model file
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@@ -514,10 +509,7 @@ class tts_class:
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self.vocoder.load_state_dict(vocoder_state)
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self.vocoder = self.vocoder.eval()
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# Determine if this is an E2-TTS model from the folder name
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is_e2_model = "e2tts" in model_folder.lower()
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# Initialize model with appropriate architecture
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# Initialize F5-TTS model with same mel_spec_kwargs as original
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vocab_char_map, vocab_size = get_tokenizer(str(vocab_path), "custom")
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mel_spec_kwargs = dict(
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@@ -529,34 +521,14 @@ class tts_class:
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mel_spec_type=self.mel_spec_type,
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)
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if is_e2_model:
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print(f"[{self.branding}ENG] Initializing E2-TTS model") if self.debug_tts else None
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self.model = CFM(
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transformer=UNetT(
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**self.e2_model_cfg,
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text_num_embeds=vocab_size,
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mel_dim=self.n_mel_channels
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),
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mel_spec_kwargs=mel_spec_kwargs,
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odeint_kwargs=dict(
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method=self.ode_method,
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),
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vocab_char_map=vocab_char_map
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).float() # Ensure float32
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else:
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print(f"[{self.branding}ENG] Initializing F5-TTS model") if self.debug_tts else None
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self.model = CFM(
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transformer=DiT(
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**self.f5_model_cfg,
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text_num_embeds=vocab_size,
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mel_dim=self.n_mel_channels
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),
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mel_spec_kwargs=mel_spec_kwargs,
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odeint_kwargs=dict(
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method=self.ode_method,
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),
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vocab_char_map=vocab_char_map
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).float() # Ensure float32
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self.model = CFM(
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transformer=DiT(**self.model_cfg, text_num_embeds=vocab_size, mel_dim=self.n_mel_channels),
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mel_spec_kwargs=mel_spec_kwargs,
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odeint_kwargs=dict(
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method=self.ode_method,
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),
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vocab_char_map=vocab_char_map
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).float() # Ensure float32
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# Load model weights
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if str(model_path).endswith('.safetensors'):
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@@ -602,8 +574,7 @@ class tts_class:
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self.vocoder = self.vocoder.to(self.device)
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self.is_tts_model_loaded = True
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model_type = "E2-TTS" if is_e2_model else "F5-TTS"
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print(f"[{self.branding}ENG] {model_type} model loaded successfully") if self.debug_tts else None
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print(f"[{self.branding}ENG] F5-TTS model loaded successfully") if self.debug_tts else None
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except Exception as e:
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print(f"[{self.branding}ENG] \033[91mError loading model: {str(e)}\033[0m")
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@@ -926,38 +897,6 @@ class tts_class:
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return chunks
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#############################################################################################################################
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#############################################################################################################################
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# DONT CHANGE ME # De-Capitalise words (Not used currently) #################################################################
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#############################################################################################################################
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#############################################################################################################################
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def process_text_for_tts(self, text):
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"""
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Process text by converting fully capitalized words to lowercase,
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while preserving other words' capitalization.
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Args:
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self: The class instance
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text (str): Input text string
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Returns:
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str: Processed text with fully capitalized words converted to lowercase
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"""
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# Split text into words
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words = text.split()
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# Process each word
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processed_words = []
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for word in words:
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# Check if word is fully uppercase and longer than 1 character
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if word.isupper() and len(word) > 1:
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processed_words.append(word.lower())
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else:
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processed_words.append(word)
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# Join words back together
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return ' '.join(processed_words)
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##########################################################################################################################################
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##########################################################################################################################################
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# CHANGE ME # Model changing. Unload out old model and load in a new one #################################################################
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@@ -1044,8 +983,6 @@ class tts_class:
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str(ref_audio_path), ref_text
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)
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text = self.process_text_for_tts(text)
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# Generate the audio using infer_process
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final_wave, final_sample_rate, _ = await self.infer_process(
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ref_audio,
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@@ -1102,4 +1039,4 @@ class tts_class:
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except Exception as e:
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print(f"[{self.branding}Debug] Device verification warning: {str(e)}") if self.debug_tts else None
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self.tts_generating_lock = False
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self.tts_generating_lock = False
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