Felipe97/llama-cpp-compiled

1from __future__ import annotations2 3from typing import Iterable, TYPE_CHECKING4 5if TYPE_CHECKING:6    from torch import Tensor7 8from .base import ModelBase, TextModel, gguf, logger9 10 11@ModelBase.register("BaichuanForCausalLM", "BaiChuanForCausalLM")12@ModelBase.example("baichuan-inc/Baichuan2-7B-Chat", "baichuan-inc/Baichuan-7B")13class BaichuanModel(TextModel):14    model_arch = gguf.MODEL_ARCH.BAICHUAN15 16    def set_vocab(self):17        self._set_vocab_sentencepiece()18 19    def set_gguf_parameters(self):20        super().set_gguf_parameters()21 22        self.gguf_writer.add_tensor_data_layout("Meta AI original pth")23        self.gguf_writer.add_rope_dimension_count(self.hparams["hidden_size"] // self.hparams["num_attention_heads"])24 25    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:26        head_count = self.hparams["num_attention_heads"]27        head_count_kv = self.hparams.get("num_key_value_heads", head_count)28 29        if bid is not None and name == f"model.layers.{bid}.self_attn.W_pack.weight":30            logger.info(f"Unpacking and permuting layer {bid}")31            yield from [32                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_Q, bid),33                    self._reverse_hf_permute_part(data_torch, 0, head_count, head_count)),34                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_K, bid),35                    self._reverse_hf_permute_part(data_torch, 1, head_count, head_count_kv)),36                (self.format_tensor_name(gguf.MODEL_TENSOR.ATTN_V, bid),37                    self._reverse_hf_part(data_torch, 2)),38            ]39        else:40            yield from self.modify_tensors(data_torch, self.map_tensor_name(name), bid)41 42    def _reverse_hf_permute(self, weights: Tensor, n_head: int, n_kv_head: int | None = None) -> Tensor:43        if n_kv_head is not None and n_head != n_kv_head:44            n_head //= n_kv_head45 46        return (47            weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])48            .swapaxes(1, 2)49            .reshape(weights.shape)50        )51 52    def _reverse_hf_permute_part(53        self, weights: Tensor, n_part: int, n_head: int, n_head_kv: int | None = None,54    ) -> Tensor:55        r = weights.shape[0] // 356        return self._reverse_hf_permute(weights[r * n_part:r * n_part + r, ...], n_head, n_head_kv)57 58    def _reverse_hf_part(self, weights: Tensor, n_part: int) -> Tensor:59        r = weights.shape[0] // 360        return weights[r * n_part:r * n_part + r, ...]61