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from typing import Optional |
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from transformers import Qwen2Config |
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from transformers.configuration_utils import PretrainedConfig |
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class StepAudio2EncoderConfig(PretrainedConfig): |
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model_type = "step_audio_2_encoder" |
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def __init__( |
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self, |
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n_mels=128, |
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n_audio_ctx=1500, |
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n_audio_state=512, |
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n_audio_head=8, |
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n_audio_layer=6, |
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llm_dim=4096, |
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kernel_size=3, |
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adapter_stride=2, |
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**kwargs, |
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): |
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self.n_mels = n_mels |
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self.n_audio_ctx = n_audio_ctx |
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self.n_audio_state = n_audio_state |
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self.n_audio_head = n_audio_head |
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self.n_audio_layer = n_audio_layer |
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self.llm_dim = llm_dim |
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self.kernel_size = kernel_size |
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self.adapter_stride = adapter_stride |
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super().__init__(**kwargs) |
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class StepAudio2Config(PretrainedConfig): |
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model_type = "step_audio_2" |
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architectures = ["StepAudio2ForCausalLM"] |
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def __init__( |
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self, |
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audio_encoder_config=None, |
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use_sliding_window: bool = False, |
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sliding_window: Optional[int] = 2048, |
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max_window_layers: Optional[int] = None, |
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**kwargs |
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): |
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kwargs.setdefault("use_sliding_window", use_sliding_window) |
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kwargs.setdefault("sliding_window", sliding_window) |
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if max_window_layers is None: |
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max_window_layers = kwargs.get("num_hidden_layers", None) |
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kwargs.setdefault("max_window_layers", max_window_layers) |
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super().__init__(**kwargs) |
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self.text_config = Qwen2Config(**kwargs) |
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if audio_encoder_config is None: |
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self.audio_encoder_config = StepAudio2EncoderConfig() |
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elif isinstance(audio_encoder_config, dict): |
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self.audio_encoder_config = StepAudio2EncoderConfig(**audio_encoder_config) |
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