ColossalAI/colossalai/inference/tensor_parallel/policies/llama.py

69 lines
2.6 KiB
Python

from functools import partial
import torch
from transformers.models.llama.modeling_llama import LlamaAttention, LlamaDecoderLayer, LlamaModel, LlamaRMSNorm
# import colossalai
from colossalai.shardformer.policies.llama import LlamaForCausalLMPolicy
from ..modeling.llama import LlamaInferenceForwards, get_llama_vllm_rmsnorm_forward
try:
from colossalai.kernel.triton import rmsnorm_forward
HAS_TRITON_RMSNORM = True
except:
print("you should install triton from https://github.com/openai/triton")
HAS_TRITON_RMSNORM = False
def get_triton_rmsnorm_forward():
if HAS_TRITON_RMSNORM:
def _triton_rmsnorm_forward(self: LlamaRMSNorm, hidden_states: torch.Tensor):
return rmsnorm_forward(hidden_states, self.weight.data, self.variance_epsilon)
return _triton_rmsnorm_forward
else:
return None
class LlamaModelInferPolicy(LlamaForCausalLMPolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
policy = super().module_policy()
self.shard_config._infer()
infer_forward = LlamaInferenceForwards.llama_model_forward
method_replacement = {'forward': partial(infer_forward)}
self.append_or_create_method_replacement(description=method_replacement, policy=policy, target_key=LlamaModel)
infer_forward = LlamaInferenceForwards.llama_decoder_layer_forward
method_replacement = {'forward': partial(infer_forward)}
self.append_or_create_method_replacement(description=method_replacement,
policy=policy,
target_key=LlamaDecoderLayer)
infer_forward = LlamaInferenceForwards.llama_flash_attn_kvcache_forward
method_replacement = {'forward': partial(infer_forward)}
self.append_or_create_method_replacement(description=method_replacement,
policy=policy,
target_key=LlamaAttention)
infer_forward = None
if HAS_TRITON_RMSNORM:
infer_forward = get_triton_rmsnorm_forward()
else:
# NOTE: adding rms_norm from cuda kernels caused precision issue, fix @tiandiao123
infer_forward = get_llama_vllm_rmsnorm_forward()
if infer_forward is not None:
method_replacement = {'forward': partial(infer_forward)}
self.append_or_create_method_replacement(description=method_replacement,
policy=policy,
target_key=LlamaRMSNorm)
return policy