wehub-resource-sync
73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from dataclasses import dataclass
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from transformers import ParakeetEncoderConfig, PretrainedConfig
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class ParakeetConfig(ParakeetEncoderConfig):
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def __init__(
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self,
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llm_hidden_size: int,
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projection_hidden_size: int,
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projection_bias: bool,
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sampling_rate: int,
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projection_eps: float = 1e-5,
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**kwargs,
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):
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super().__init__(**kwargs)
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self.llm_hidden_size = llm_hidden_size
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self.projection_hidden_size = projection_hidden_size
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self.projection_bias = projection_bias
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self.sampling_rate = sampling_rate
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self.projection_eps = projection_eps
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@staticmethod
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def from_hf_config(
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config: PretrainedConfig, *, llm_hidden_size: int, max_model_len: int
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) -> "ParakeetConfig":
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assert isinstance(config, PretrainedConfig)
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return ParakeetConfig(
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**config.to_dict(),
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scale_input=False,
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attention_bias=False,
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llm_hidden_size=llm_hidden_size,
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max_position_embeddings=max_model_len
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+ 1, # + 1 because it seems like max_model_len+1 can be passed
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)
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@dataclass(kw_only=True, frozen=True)
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class ExtractorConfig:
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feature_size: int
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sampling_rate: int
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subsampling_factor: int
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subsampling_conv_kernel_size: int
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subsampling_conv_stride: int
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hop_length: int = 160
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"""Default `160`: Matches HF default"""
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clip_duration_s: int = 30
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clip_min_duration_s: float = 0.1
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win_length: int = 400
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preemphasis: float = 0.97
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n_fft: int = 512
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padding_value: float = 0.0
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@classmethod
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def from_hf_config(cls, config: PretrainedConfig) -> "ExtractorConfig":
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assert isinstance(config, PretrainedConfig)
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defaults = ("hop_length", "win_length", "preemphasis", "n_fft", "padding_value")
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optional_kwargs = {
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name: getattr(config, name) for name in defaults if hasattr(config, name)
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}
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return cls(
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feature_size=config.num_mel_bins,
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sampling_rate=config.sampling_rate,
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subsampling_factor=config.subsampling_factor,
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subsampling_conv_kernel_size=config.subsampling_conv_kernel_size,
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subsampling_conv_stride=config.subsampling_conv_stride,
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**optional_kwargs,
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)
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