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[gemini] gemini support tensor parallelism. (#4942)

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* [colossalai]fix typo

* [inference] Add smmoothquant for llama (#4904)

* [inference] add int8 rotary embedding kernel for smoothquant (#4843)

* [inference] add smoothquant llama attention (#4850)

* add smoothquant llama attention

* remove uselss code

* remove useless code

* fix import error

* rename file name

* [inference] add silu linear fusion for smoothquant llama mlp  (#4853)

* add silu linear

* update skip condition

* catch smoothquant cuda lib exception

* prcocess exception for tests

* [inference] add llama mlp for smoothquant (#4854)

* add llama mlp for smoothquant

* fix down out scale

* remove duplicate lines

* add llama mlp check

* delete useless code

* [inference] add smoothquant llama (#4861)

* add smoothquant llama

* fix attention accuracy

* fix accuracy

* add kv cache and save pretrained

* refactor example

* delete smooth

* refactor code

* [inference] add smooth function and delete useless code for smoothquant (#4895)

* add smooth function and delete useless code

* update datasets

* remove duplicate import

* delete useless file

* refactor codes (#4902)

* rafactor code

* add license

* add torch-int and smoothquant license

* Update flash_attention_patch.py

To be compatible with the new change in the Transformers library, where a new argument 'padding_mask' was added to forward function of attention layer.
https://github.com/huggingface/transformers/pull/25598

* [kernel] support pure fp16 for cpu adam and update gemini optim tests (#4921)

* [kernel] support pure fp16 for cpu adam (#4896)

* [kernel] fix cpu adam kernel for pure fp16 and update tests (#4919)

* [kernel] fix cpu adam

* [test] update gemini optim test

* [format] applied code formatting on changed files in pull request 4908 (#4918)

Co-authored-by: github-actions <github-actions@github.com>

* [gemini] support gradient accumulation (#4869)

* add test

* fix no_sync bug in low level zero plugin

* fix test

* add argument for grad accum

* add grad accum in backward hook for gemini

* finish implementation, rewrite tests

* fix test

* skip stuck model in low level zero test

* update doc

* optimize communication & fix gradient checkpoint

* modify doc

* cleaning codes

* update cpu adam fp16 case

* [hotfix] fix torch 2.0 compatibility (#4936)

* [hotfix] fix launch

* [test] fix test gemini optim

* [shardformer] fix vit

* [test] add no master test for low level zero plugin (#4934)

* [format] applied code formatting on changed files in pull request 4820 (#4886)

Co-authored-by: github-actions <github-actions@github.com>

* [nfc] fix some typo with colossalai/ docs/ etc. (#4920)

* [Refactor] Integrated some lightllm kernels into token-attention  (#4946)

* add some req for inference

* clean codes

* add codes

* add some lightllm deps

* clean codes

* hello

* delete rms files

* add some comments

* add comments

* add doc

* add lightllm deps

* add lightllm cahtglm2 kernels

* add lightllm cahtglm2 kernels

* replace rotary embedding with lightllm kernel

* add some commnets

* add some comments

* add some comments

* add

* replace fwd kernel att1

* fix a arg

* add

* add

* fix token attention

* add some comments

* clean codes

* modify comments

* fix readme

* fix bug

* fix bug

---------

Co-authored-by: cuiqing.li <lixx336@gmail.com>
Co-authored-by: CjhHa1 <cjh18671720497@outlook.com>

* [test] merge old components to test to model zoo (#4945)

* [test] add custom models in model zoo

* [test] update legacy test

* [test] update model zoo

* [test] update gemini test

* [test] remove components to test

* [inference] add reference and fix some bugs (#4937)

* add reference and fix some bugs

* update gptq init

---------

Co-authored-by: Xu Kai <xukai16@foxamil.com>

* [Inference]ADD Bench Chatglm2 script (#4963)

* add bench chatglm

* fix bug and make utils

---------

Co-authored-by: CjhHa1 <cjh18671720497outlook.com>

* [Pipeline inference] Combine kvcache with pipeline inference (#4938)

* merge kvcache with pipeline inference and refactor the code structure

* support ppsize > 2

* refactor pipeline code

* do pre-commit

* modify benchmark

* fix bench mark

* polish code

* add docstring and update readme

* refactor the code

* fix some logic bug of ppinfer

* polish readme

* fix typo

* skip infer test

* updated c++17 compiler flags (#4983)

* [Inference] Dynamic Batching Inference, online and offline (#4953)

* [inference] Dynamic Batching for Single and Multiple GPUs (#4831)

* finish batch manager

* 1

* first

* fix

* fix dynamic batching

* llama infer

* finish test

* support different lengths generating

* del prints

* del prints

* fix

* fix bug

---------

Co-authored-by: CjhHa1 <cjh18671720497outlook.com>

* [inference] Async dynamic batching  (#4894)

* finish input and output logic

* add generate

* test forward

* 1

* [inference]Re push async dynamic batching (#4901)

* adapt to ray server

* finish async

* finish test

* del test

---------

Co-authored-by: yuehuayingxueluo <867460659@qq.com>

* Revert "[inference]Re push async dynamic batching (#4901)" (#4905)

This reverts commit fbf3c09e67.

* Revert "[inference] Async dynamic batching  (#4894)"

This reverts commit fced140250.

* Revert "[inference] Async dynamic batching  (#4894)" (#4909)

This reverts commit fced140250.

* Add Ray Distributed Environment Init Scripts

* support DynamicBatchManager base function

* revert _set_tokenizer version

* add driver async generate

* add async test

* fix bugs in test_ray_dist.py

* add get_tokenizer.py

* fix code style

* fix bugs about No module named 'pydantic' in ci test

* fix bugs in ci test

* fix bugs in ci test

* fix bugs in ci test

* [infer]Add Ray Distributed Environment Init Scripts (#4911)

* Revert "[inference] Async dynamic batching  (#4894)"

This reverts commit fced140250.

* Add Ray Distributed Environment Init Scripts

* support DynamicBatchManager base function

* revert _set_tokenizer version

* add driver async generate

* add async test

* fix bugs in test_ray_dist.py

* add get_tokenizer.py

* fix code style

* fix bugs about No module named 'pydantic' in ci test

* fix bugs in ci test

* fix bugs in ci test

* fix bugs in ci test

* support dynamic batch for bloom model and is_running function

* [Inference]Test for new Async engine (#4935)

* infer engine

* infer engine

* test engine

* test engine

* new manager

* change step

* add

* test

* fix

* fix

* finish test

* finish test

* finish test

* finish test

* add license

---------

Co-authored-by: yuehuayingxueluo <867460659@qq.com>

* add assertion for config (#4947)

* [Inference] Finish dynamic batching offline test (#4948)

* test

* fix test

* fix quant

* add default

* fix

* fix some bugs

* fix some bugs

* fix

* fix bug

* fix bugs

* reset param

---------

Co-authored-by: yuehuayingxueluo <867460659@qq.com>
Co-authored-by: Cuiqing Li <lixx3527@gmail.com>
Co-authored-by: CjhHa1 <cjh18671720497outlook.com>

* [Kernels]Updated Triton kernels into 2.1.0 and adding flash-decoding for llama token attention  (#4965)

* adding flash-decoding

* clean

* adding kernel

* adding flash-decoding

* add integration

* add

* adding kernel

* adding kernel

* adding triton 2.1.0 features for inference

* update bloom triton kernel

* remove useless vllm kernels

* clean codes

* fix

* adding files

* fix readme

* update llama flash-decoding

---------

Co-authored-by: cuiqing.li <lixx336@gmail.com>

* fix ColossalEval (#4992)

Co-authored-by: Xu Yuanchen <yuanchen.xu00@gmail.com>

* [doc]Update doc for colossal-inference (#4989)

* update doc

* Update README.md

---------

Co-authored-by: cuiqing.li <lixx336@gmail.com>

* [hotfix] Fix the bug where process groups were not being properly released. (#4940)

* Fix the bug where process groups were not being properly released.

* test

* Revert "test"

This reverts commit 479900c139.

* [hotfix] fix the bug of repeatedly storing param group (#4951)

* [doc] add supported feature diagram for hybrid parallel plugin (#4996)

* [Pipeline Inference] Merge pp with tp (#4993)

* refactor pipeline into new CaiInferEngine

* updata llama modeling forward

* merge tp with pp

* update docstring

* optimize test workflow and example

* fix typo

* add assert and todo

* [release] update version (#4995)

* [release] update version

* [hotfix] fix ci

* [gemini] gemini support tp

[gemini] gemini support tp

[gemini] gemini support tp

[gemini] gemini support tp

[gemini] gemini support tp

* fix

fix

fix

* update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

update checkpointIO

* support fused layernorm

support fused layernorm

support fused layernorm

* update fusedlayernorm

update fusedlayernorm

update fusedlayernorm

* add sequence parallel to gemini

add sequence parallel to gemini

* fix

* fix comments

fix comments

fix comments

* fix

* fix t5

* clear cache

* fix

* activate ci

* activate ci

* fix

* fix

* fix

* fix

* revert

* modify tp gather method

modify tp gather method

modify tp gather method

modify tp gather method

* fix test

---------

Co-authored-by: Xu Kai <xukai16@foxmail.com>
Co-authored-by: Zian(Andy) Zheng <62330719+Orion-Zheng@users.noreply.github.com>
Co-authored-by: Hongxin Liu <lhx0217@gmail.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: Baizhou Zhang <eddiezhang@pku.edu.cn>
Co-authored-by: Zhongkai Zhao <kanezz620@gmail.com>
Co-authored-by: digger yu <digger-yu@outlook.com>
Co-authored-by: Cuiqing Li <lixx3527@gmail.com>
Co-authored-by: cuiqing.li <lixx336@gmail.com>
Co-authored-by: CjhHa1 <cjh18671720497@outlook.com>
Co-authored-by: Xu Kai <xukai16@foxamil.com>
Co-authored-by: Jianghai <72591262+CjhHa1@users.noreply.github.com>
Co-authored-by: Bin Jia <45593998+FoolPlayer@users.noreply.github.com>
Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com>
Co-authored-by: yuehuayingxueluo <867460659@qq.com>
Co-authored-by: Yuanchen <70520919+chengeharrison@users.noreply.github.com>
Co-authored-by: Xu Yuanchen <yuanchen.xu00@gmail.com>
Co-authored-by: littsk <1214689160@qq.com>
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This commit is contained in:
flybird11111
2023-11-10 10:15:16 +08:00
committed by GitHub
parent a4489384d5
commit 576a2f7b10
13 changed files with 390 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
tests/test_booster/test_plugin/test_gemini_plugin.py
View File

@@ -10,18 +10,21 @@ from colossalai.booster.plugin import GeminiPlugin
from colossalai.fx import is_compatible_with_meta
from colossalai.lazy.lazy_init import LazyInitContext
from colossalai.nn.optimizer import HybridAdam
from colossalai.tensor.d_tensor.api import clear_layout_converter
from colossalai.shardformer.layer.utils import Randomizer
from colossalai.tensor.colo_parameter import ColoParameter
from colossalai.testing import parameterize, rerun_if_address_is_in_use, spawn
from tests.kit.model_zoo import model_zoo
def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn) -> Optional[str]:
def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn, enable_tensor_parallelism) -> Optional[str]:
try:
if init_method == "lazy":
ctx = LazyInitContext()
else:
ctx = nullcontext()
plugin = GeminiPlugin(max_norm=1.0, initial_scale=2**5)
enable_all_optimization = True if enable_tensor_parallelism else False
plugin = GeminiPlugin(max_norm=1.0, initial_scale=2**5, enable_tensor_parallelism=enable_tensor_parallelism, enable_all_optimization=enable_all_optimization)
booster = Booster(plugin=plugin)
with ctx:
model = model_fn()
@@ -46,6 +49,8 @@ def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn) -> Optional[
booster.backward(loss, optimizer)
optimizer.step()
except NotImplementedError:
print(f"Tensor Parallelism policy for {model.__class__} is not implemented yet\n.")
except Exception as e:
# raise e
return repr(e)
@@ -57,7 +62,8 @@ def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn) -> Optional[
@parameterize("subset", ["torchvision", "transformers", "diffusers"])
@parameterize("init_method", ["none"])
def check_gemini_plugin(subset: str, init_method: str = "none", early_stop: bool = True):
@parameterize("enable_tensor_parallelism", [True, False])
def check_gemini_plugin(subset: str, init_method: str = "none", enable_tensor_parallelism: bool = True, early_stop: bool = True):
"""check gemini plugin over model zoo
Args:
@@ -116,7 +122,12 @@ def check_gemini_plugin(subset: str, init_method: str = "none", early_stop: bool
"torchvision_efficientnet_v2_s",
]:
continue
err = run_fn(init_method, model_fn, data_gen_fn, output_transform_fn)
# TODO debug blip2 when using tp, something wrong with shift_logits's shape
if "transformers_blip2" in name:
enable_tensor_parallelism = False
err = run_fn(init_method, model_fn, data_gen_fn, output_transform_fn, enable_tensor_parallelism)
torch.cuda.empty_cache()
if err is None:
passed_models.append(name)

18
tests/test_checkpoint_io/test_gemini_checkpoint_io.py
View File

@@ -37,17 +37,20 @@ OPTIM_PLACEMENT_CONFIGS = [
@parameterize("placement_config", MODEL_PLACEMENT_CONFIGS)
@parameterize("model_name", ["transformers_bert_for_sequence_classification"])
@parameterize("use_safetensors", [False, True])
def exam_state_dict_with_origin(placement_config, model_name, use_safetensors: bool):
@parameterize("enable_tensor_parallelism", [True, False])
@parameterize("tp_size", [2])
def exam_state_dict_with_origin(placement_config, model_name, use_safetensors: bool, enable_tensor_parallelism: bool, tp_size: int):
from transformers import BertForSequenceClassification
(model_fn, data_gen_fn, output_transform_fn, _, _) = next(iter(model_zoo.get_sub_registry(model_name).values()))
bert_model = model_fn()
enable_all_optimization = True if enable_tensor_parallelism else False
with shared_tempdir() as tempdir:
pretrained_path = os.path.join(tempdir, "pretrained")
bert_model.config.save_pretrained(save_directory=pretrained_path)
plugin = GeminiPlugin(**placement_config)
plugin = GeminiPlugin(**placement_config, enable_tensor_parallelism=enable_tensor_parallelism, tp_size=tp_size, enable_all_optimization=enable_all_optimization)
booster = Booster(plugin=plugin)
bert_model, _, _, _, _ = booster.boost(bert_model)
model_size = sum(p.numel() * p.element_size() for p in bert_model.parameters()) / 1024**2
@@ -63,13 +66,16 @@ def exam_state_dict_with_origin(placement_config, model_name, use_safetensors: b
@clear_cache_before_run()
@parameterize("placement_config", OPTIM_PLACEMENT_CONFIGS)
@parameterize("shard", [False, True])
@parameterize("shard", [True, False])
@parameterize("model_name", ["transformers_gpt"])
@parameterize("size_per_shard", [32])
def exam_state_dict(placement_config, shard: bool, model_name: str, size_per_shard: int):
@parameterize("enable_tensor_parallelism", [True, False])
@parameterize("tp_size", [2])
def exam_state_dict(placement_config, shard: bool, model_name: str, size_per_shard: int, enable_tensor_parallelism: bool, tp_size: int):
(model_fn, data_gen_fn, output_transform_fn, _, _) = next(iter(model_zoo.get_sub_registry(model_name).values()))
criterion = lambda x: x.mean()
plugin = GeminiPlugin(**placement_config, precision="fp16", initial_scale=(2**14))
enable_all_optimization = True if enable_tensor_parallelism else False
plugin = GeminiPlugin(**placement_config, precision="fp16", initial_scale=(2**14), enable_tensor_parallelism=enable_tensor_parallelism, tp_size=tp_size, enable_all_optimization=enable_all_optimization)
booster = Booster(plugin=plugin)
model = model_fn()
@@ -148,7 +154,7 @@ def run_dist(rank, world_size, port):
@pytest.mark.dist
@pytest.mark.parametrize("world_size", [2])
@pytest.mark.parametrize("world_size", [4])
@rerun_if_address_is_in_use()
def test_gemini_ckpIO(world_size):
spawn(run_dist, world_size)