ColossalAI/colossalai/inference/tensor_parallel/policies/chatglm2.py

75 lines
2.6 KiB
Python

from functools import partial
from colossalai.shardformer.modeling.chatglm2_6b.modeling_chatglm import (
ChatGLMForConditionalGeneration,
ChatGLMModel,
GLMBlock,
GLMTransformer,
SelfAttention,
)
# import colossalai
from colossalai.shardformer.policies.chatglm2 import ChatGLMModelPolicy
from ..modeling._utils import init_to_get_rotary
from ..modeling.chatglm2 import ChatGLM2InferenceForwards
try:
HAS_TRITON_RMSNORM = True
except:
print("you should install triton from https://github.com/openai/triton")
HAS_TRITON_RMSNORM = False
class ChatGLM2InferPolicy(ChatGLMModelPolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
policy = super().module_policy()
self.shard_config._infer()
model_infer_forward = ChatGLM2InferenceForwards.chatglm_model_forward
method_replacement = {"forward": model_infer_forward}
self.append_or_create_method_replacement(description=method_replacement, policy=policy, target_key=ChatGLMModel)
encoder_infer_forward = ChatGLM2InferenceForwards.chatglm_encoder_forward
method_replacement = {"forward": encoder_infer_forward}
self.append_or_create_method_replacement(
description=method_replacement, policy=policy, target_key=GLMTransformer
)
encoder_layer_infer_forward = ChatGLM2InferenceForwards.chatglm_glmblock_forward
method_replacement = {"forward": encoder_layer_infer_forward}
self.append_or_create_method_replacement(description=method_replacement, policy=policy, target_key=GLMBlock)
attn_infer_forward = ChatGLM2InferenceForwards.chatglm_flash_attn_kvcache_forward
method_replacement = {"forward": attn_infer_forward}
self.append_or_create_method_replacement(
description=method_replacement, policy=policy, target_key=SelfAttention
)
# for rmsnorm and others, we need to check the shape
return policy
def postprocess(self):
init_to_get_rotary(self.model)
return self.model
class ChatGLM2ForConditionalGenerationInferPolicy(ChatGLM2InferPolicy):
def __init__(self) -> None:
super().__init__()
def module_policy(self):
policy = super().module_policy()
model_infer_forward = ChatGLM2InferenceForwards.chatglm_for_conditional_generation_forward
method_replacement = {"forward": partial(model_infer_forward)}
self.append_or_create_method_replacement(
description=method_replacement, policy=policy, target_key=ChatGLMForConditionalGeneration
)
return policy
def postprocess(self):
return super().postprocess()