Made from my ANE-Optimizer Custom GPT.
The provided code implements several Apple Neural Engine (ANE) principles to optimize the performance of a language model, specifically the Llama model. Here's a detailed breakdown of the principles applied:
- Classes like
LlamaRMSNorm
,LlamaRotaryEmbedding
,LlamaMLP
,LlamaAttention
, andLlamaDecoderLayer
inherit fromtorch.nn.Module
and properly initialize their components usingsuper().__init__()
. This ensures the base class is correctly set up before adding additional attributes or methods. LlamaPreTrainedModel
andLlamaModel
properly initialize their base classPreTrainedModel
usingsuper().__init__(config)
.