| 375 | |
| 376 | |
| 377 | class UnquantizedLinearMethod(LinearMethodBase): |
| 378 | |
| 379 | def create_weights(self, module: Linear, in_features: int, |
| 380 | out_features: int, bias: bool, dtype: torch.dtype): |
| 381 | weight_shape = (out_features, in_features) |
| 382 | module.weight = Parameter(torch.empty(weight_shape, dtype=dtype), |
| 383 | requires_grad=False) |
| 384 | |
| 385 | if bias: |
| 386 | module.bias = Parameter(torch.empty((out_features), dtype=dtype), |
| 387 | requires_grad=False) |
| 388 | else: |
| 389 | module.register_parameter("bias", None) |
| 390 | |
| 391 | def apply(self, module: Linear, input: torch.Tensor, |
| 392 | bias: Optional[torch.Tensor]): |
| 393 | if module.use_custom_cublas_mm: |
| 394 | output = torch.ops.trtllm.cublas_mm(input, |
| 395 | module.weight.t(), |
| 396 | bias, |
| 397 | out_dtype=None) |
| 398 | else: |
| 399 | output = F.linear(input, module.weight, bias) |
| 400 | return output |
| 401 | |
| 402 | def load_weights_vanilla(self, |
| 403 | module: Linear, |
| 404 | weights: List[Dict], |
| 405 | allow_partial_loading: bool = False) -> None: |
| 406 | load_weights_vanilla_helper(module, |
| 407 | weights, |
| 408 | allow_partial_loading=allow_partial_loading) |
| 409 | |
| 410 | def load_weights_fused_qkv_linear( |
| 411 | self, |
| 412 | module: Linear, |
| 413 | weights: List[Dict], |
| 414 | allow_partial_loading: bool = False) -> None: |
| 415 | q_weight, k_weight, v_weight = load_weights_fused_qkv_helper( |
| 416 | module, weights, allow_partial_loading=allow_partial_loading) |
| 417 | if not allow_partial_loading: |
| 418 | copy_weight(module.weight, torch.cat( |
| 419 | (q_weight, k_weight, v_weight))) |
| 420 | else: |
| 421 | for shard_key, weight in zip(('q', 'k', 'v'), |
| 422 | (q_weight, k_weight, v_weight)): |
| 423 | if weight is not None: |
| 424 | assert shard_key in module.fused_weight_shard_indices_mapping, f"Shard key {shard_key} not found in fused weight shard indices mapping" |
| 425 | shard_offset, shard_size = module.fused_weight_shard_indices_mapping[ |
| 426 | shard_key] |
| 427 | copy_weight_shard(module.weight, weight, shard_offset, |
| 428 | shard_size) |
| 429 | |
| 430 | def load_weights_fused_gate_up_linear( |
| 431 | self, |
| 432 | module: Linear, |
| 433 | weights: List[Dict], |
| 434 | allow_partial_loading: bool = False) -> None: |