Delete configuration_spark_tts.py
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configuration_spark_tts.py
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# Copyright (c) 2025 SparkAudio & The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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""" SparkTTS model configuration"""
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from transformers.configuration_utils import PretrainedConfig
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from transformers.utils import logging
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logger = logging.get_logger(__name__)
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class SparkTTSConfig(PretrainedConfig):
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"""
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This is the configuration class to store the configuration of a [`SparkTTSModel`].
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It is used to instantiate a SparkTTS model according to the specified arguments, defining the model
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architecture and sub-component paths.
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Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs.
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Read the documentation from [`PretrainedConfig`] for more information.
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Args:
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llm_model_name_or_path (`str`, *optional*, defaults to `"./LLM"`):
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Path to the pretrained LLM model or model identifier from huggingface.co/models.
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bicodec_model_name_or_path (`str`, *optional*, defaults to `"./BiCodec"`):
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Path to the pretrained BiCodec model directory.
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wav2vec2_model_name_or_path (`str`, *optional*, defaults to `"./wav2vec2-large-xlsr-53"`):
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Path to the pretrained Wav2Vec2 model directory.
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sample_rate (`int`, *optional*, defaults to 16000):
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The sampling rate of the audio files.
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highpass_cutoff_freq (`int`, *optional*, defaults to 40):
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Highpass filter cutoff frequency for audio processing.
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latent_hop_length (`int`, *optional*, defaults to 320):
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Hop length used in BiCodec processing.
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ref_segment_duration (`float`, *optional*, defaults to 6.0):
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Duration (in seconds) of the reference audio clip used for speaker embedding.
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volume_normalize (`bool`, *optional*, defaults to `True`):
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Whether to normalize the volume of audio inputs.
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bicodec_config (`dict`, *optional*):
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A dictionary containing the configuration for the BiCodec model components (encoder, decoder, etc.).
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This is typically loaded from the `BiCodec/config.yaml` originally.
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**kwargs
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Additional keyword arguments passed along to [`PretrainedConfig`].
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"""
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model_type = "spark-tts"
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processor_class = "SparkTTSProcessor"
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config_files = ["config.json"]
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attribute_map = {} # Add mappings if needed for renaming attributes
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def __init__(
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self,
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llm_model_name_or_path="./LLM",
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bicodec_model_name_or_path="./BiCodec",
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wav2vec2_model_name_or_path="./wav2vec2-large-xlsr-53",
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sample_rate=16000,
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highpass_cutoff_freq=40,
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latent_hop_length=320,
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ref_segment_duration=6.0,
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volume_normalize=True,
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bicodec_config=None,
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**kwargs,
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):
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self.llm_model_name_or_path = llm_model_name_or_path
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self.bicodec_model_name_or_path = bicodec_model_name_or_path
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self.wav2vec2_model_name_or_path = wav2vec2_model_name_or_path
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self.sample_rate = sample_rate
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self.highpass_cutoff_freq = highpass_cutoff_freq
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self.latent_hop_length = latent_hop_length
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self.ref_segment_duration = ref_segment_duration
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self.volume_normalize = volume_normalize
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self.bicodec_config = bicodec_config if bicodec_config is not None else {}
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# REMOVE THIS WARNING - the check in SparkTTSModel is better
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# if not self.bicodec_config:
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# logger.warning("BiCodec config is empty. BiCodec model might not load correctly.")
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super().__init__(**kwargs)
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