ColossalAI/tests/test_shardformer/test_model/_utils.py

65 lines
2.4 KiB
Python

import copy
from contextlib import nullcontext
from colossalai.lazy import LazyInitContext
from colossalai.pipeline.stage_manager import PipelineStageManager
from colossalai.shardformer import ShardConfig, ShardFormer
def build_model(model_fn, enable_fused_normalization=True, enable_tensor_parallelism=True, use_lazy_init: bool = False):
ctx = LazyInitContext() if use_lazy_init else nullcontext()
with ctx:
# create new model
org_model = model_fn()
model_copy = copy.deepcopy(org_model)
if use_lazy_init:
ctx.materialize(org_model)
# shard model
shard_config = ShardConfig(enable_fused_normalization=enable_fused_normalization,
enable_tensor_parallelism=enable_tensor_parallelism)
shard_former = ShardFormer(shard_config=shard_config)
sharded_model, shared_params = shard_former.optimize(model_copy)
return org_model.cuda(), sharded_model.cuda()
def build_pipeline_model(model_fn,
stage_manager=None,
enable_fused_normalization=False,
enable_tensor_parallelism=False,
use_lazy_init: bool = False):
ctx = LazyInitContext() if use_lazy_init else nullcontext()
with ctx:
# create new model
org_model = model_fn()
model_copy = copy.deepcopy(org_model)
if use_lazy_init:
ctx.materialize(org_model)
# shard model
shard_config = ShardConfig(enable_fused_normalization=enable_fused_normalization,
enable_tensor_parallelism=enable_tensor_parallelism,
pipeline_stage_manager=stage_manager)
shard_former = ShardFormer(shard_config=shard_config)
sharded_model, shared_params = shard_former.optimize(model_copy)
return org_model.cuda(), sharded_model.cuda()
def run_forward(original_model, sharded_model, data_gen_fn, output_transform_fn, loss_fn):
# prepare input
data = data_gen_fn()
data = {k: v.cuda() for k, v in data.items()}
# switch to train mode
original_model.train()
sharded_model.train()
# run forward
org_output = original_model(**data)
org_output = output_transform_fn(org_output)
org_loss = loss_fn(org_output)
shard_output = sharded_model(**data)
shard_output = output_transform_fn(shard_output)
shard_loss = loss_fn(shard_output)
return org_output, org_loss, shard_output, shard_loss