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"""Llama Model.""" |
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import warnings |
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from megatron import get_args |
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from .enums import PositionEmbeddingType |
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from . import GPTModel |
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class LlamaModel(GPTModel): |
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def __init__(self, |
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num_tokentypes: int = 0, |
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parallel_output: bool = True, |
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pre_process: bool = True, |
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post_process: bool = True, |
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model_type=None, |
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version: int = 2): |
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args = get_args() |
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assert version in {1, 2}, f"Unknown llama version {version}" |
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assert args.position_embedding_type == PositionEmbeddingType.rotary, \ |
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f"Llama uses rotary embedding, not {args.position_embedding_type}" |
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assert not args.use_post_ln, "Llama does not use post_ln" |
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assert args.glu_activation == "swiglu", "Llama works with swiglu activation" |
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assert not args.use_bias, "Llama does not use bias" |
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assert not args.parallel_attn, "Llama does not use parallel_attn" |
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assert args.use_rms_norm, "Llama uses rms_norm" |
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assert not args.tie_embed_logits , "Llama unties embedding and lm_head weights" |
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if args.bias_gelu_fusion: |
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warnings.warn("Llama is not intended to use bias_gelu_fusion") |
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if args.bias_dropout_fusion: |
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warnings.warn("Llama is not intended to use bias_dropout_fusion") |
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if args.hidden_dropout > 0.0 and not args.lima_dropout: |
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warnings.warn( "Llama is not intended to use dropout") |
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if args.attention_dropout > 0.0: |
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warnings.warn( "Llama is not intended to use dropout") |
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super().__init__(num_tokentypes=num_tokentypes, parallel_output=parallel_output, |
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pre_process=pre_process, post_process=post_process, |
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model_type=model_type) |
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