import copy from colossalai.shardformer import ShardConfig, ShardFormer def build_model(world_size, model_fn): # create new model org_model = model_fn().cuda() # shard model shard_config = ShardConfig(tensor_parallel_size=world_size, enable_fused_normalization=True) model_copy = copy.deepcopy(org_model) shard_former = ShardFormer(shard_config=shard_config) shard_former.init_distributed() sharded_model = shard_former.shard_model(model_copy).cuda() return org_model, sharded_model 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