hiyouga f5df1ceaf1 add npu examples
Former-commit-id: af343034dd31303be59678af9d1eae338864e884
2024-05-14 23:32:53 +08:00

56 lines
2.0 KiB
Python

from typing import TYPE_CHECKING
from ...extras.logging import get_logger
from ...extras.packages import is_flash_attn2_available, is_sdpa_available
if TYPE_CHECKING:
from transformers import PretrainedConfig
from ...hparams import ModelArguments
logger = get_logger(__name__)
def configure_attn_implementation(config: "PretrainedConfig", model_args: "ModelArguments") -> None:
if model_args.flash_attn == "auto":
return
elif model_args.flash_attn == "off":
requested_attn_implementation = "eager"
elif model_args.flash_attn == "sdpa":
if not is_sdpa_available():
logger.warning("torch>=2.1.1 is required for SDPA attention.")
return
requested_attn_implementation = "sdpa"
elif model_args.flash_attn == "fa2":
if not is_flash_attn2_available():
logger.warning("FlashAttention-2 is not installed.")
return
requested_attn_implementation = "flash_attention_2"
else:
raise NotImplementedError("Unknown attention type: {}".format(model_args.flash_attn))
if getattr(config, "model_type", None) == "internlm2": # special case for custom models
setattr(config, "attn_implementation", requested_attn_implementation)
else:
setattr(config, "_attn_implementation", requested_attn_implementation)
def print_attn_implementation(config: "PretrainedConfig") -> None:
if getattr(config, "model_type", None) == "internlm2": # special case for custom models
attn_implementation = getattr(config, "attn_implementation", None)
else:
attn_implementation = getattr(config, "_attn_implementation", None)
if attn_implementation == "flash_attention_2":
logger.info("Using FlashAttention-2 for faster training and inference.")
elif attn_implementation == "sdpa":
logger.info("Using torch SDPA for faster training and inference.")
else:
logger.info("Using vanilla attention implementation.")