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import dataclasses |
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from typing import Optional |
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@dataclasses.dataclass |
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class LyraBaichuanParam: |
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num_heads: int = 40 |
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size_per_head: int = 128 |
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inter_size: int = 13824 |
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num_layers: int = 40 |
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vocab_size: int = 39424 |
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start_id: Optional[int] = 1 |
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end_id: Optional[int] = 2 |
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tensor_para_size: int = 1 |
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pipeline_para_size: int = 1 |
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remove_padding: bool = True |
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shared_contexts_ratio: float = 1.0 |
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layernorm_eps: float = 1e-6 |
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weights_data_type: str = "fp16" |
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rotary_embedding: int = 128 |
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use_gptj_residual: bool = False |
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def __post_init__(self): |
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if not 0.0 <= self.shared_contexts_ratio <= 1.0: |
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raise ValueError( |
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f'Got an invalid value of shared_context_ratio ' |
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f'{self.shared_contexts_ratio} - range: [0.0, 1.0]') |
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def asdict(self): |
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return dataclasses.asdict(self) |
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LYRA_BAICHUAN_PARAM = LyraBaichuanParam() |
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LIB_SO_PATH = '/usr/lib/ftlib/libth_transformer.so' |
