github/ColossalAI
1
0
Fork 0
mirror of https://github.com/hpcaitech/ColossalAI.git synced 2025-09-15 14:12:02 +00:00
Code Issues Packages Projects Releases Wiki Activity

Update metainfo patch branch (#2517)

Browse Source 
* init

* rename and remove useless func

* basic chunk

* add evoformer

* align evoformer

* add meta

* basic chunk

* basic memory

* finish basic inference memory estimation

* finish memory estimation

* fix bug

* finish memory estimation

* add part of index tracer

* finish basic index tracer

* add doc string

* add doc str

* polish code

* polish code

* update active log

* polish code

* add possible region search

* finish region search loop

* finish chunk define

* support new op

* rename index tracer

* finishi codegen on msa

* redesign index tracer, add source and change compute

* pass outproduct mean

* code format

* code format

* work with outerproductmean and msa

* code style

* code style

* code style

* code style

* change threshold

* support check_index_duplicate

* support index dupilictae and update loop

* support output

* update memory estimate

* optimise search

* fix layernorm

* move flow tracer

* refactor flow tracer

* format code

* refactor flow search

* code style

* adapt codegen to prepose node

* code style

* remove abandoned function

* remove flow tracer

* code style

* code style

* reorder nodes

* finish node reorder

* update run

* code style

* add chunk select class

* add chunk select

* code style

* add chunksize in emit, fix bug in reassgin shape

* code style

* turn off print mem

* add evoformer openfold init

* init openfold

* add benchmark

* add print

* code style

* code style

* init openfold

* update openfold

* align openfold

* use max_mem to control stratge

* update source add

* add reorder in mem estimator

* improve reorder efficeincy

* support ones_like, add prompt if fit mode search fail

* fix a bug in ones like, dont gen chunk if dim size is 1

* fix bug again

* update min memory stratege, reduce mem usage by 30%

* last version of benchmark

* refactor structure

* restruct dir

* update test

* rename

* take apart chunk code gen

* close mem and code print

* code format

* rename ambiguous variable

* seperate flow tracer

* seperate input node dim search

* seperate prepose_nodes

* seperate non chunk input

* seperate reorder

* rename

* ad reorder graph

* seperate trace flow

* code style

* code style

* fix typo

* set benchmark

* rename test

* update codegen test

* Fix state_dict key missing issue of the ZeroDDP (#2363)

* Fix state_dict output for ZeroDDP duplicated parameters

* Rewrite state_dict based on get_static_torch_model

* Modify get_static_torch_model to be compatible with the lower version (ZeroDDP)

* update codegen test

* update codegen test

* add chunk search test

* code style

* add available

* [hotfix] fix gpt gemini example (#2404)

* [hotfix] fix gpt gemini example

* [example] add new assertions

* remove autochunk_available

* [workflow] added nightly release to pypi (#2403)

* add comments

* code style

* add doc for search chunk

* [doc] updated readme regarding pypi installation (#2406)

* add doc for search

* [doc] updated kernel-related optimisers' docstring (#2385)

* [doc] updated kernel-related optimisers' docstring

* polish doc

* rename trace_index to trace_indice

* rename function from index to indice

* rename

* rename in doc

* [polish] polish code for get_static_torch_model (#2405)

* [gemini] polish code

* [testing] remove code

* [gemini] make more robust

* rename

* rename

* remove useless function

* [worfklow] added coverage test (#2399)

* [worfklow] added coverage test

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* add doc for trace indice

* [docker] updated Dockerfile and release workflow (#2410)

* add doc

* update doc

* add available

* change imports

* add test in import

* [workflow] refactored the example check workflow (#2411)

* [workflow] refactored the example check workflow

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* Update parallel_context.py (#2408)

* [hotfix] add DISTPAN argument for benchmark (#2412)

* change the benchmark config file

* change config

* revert config file

* rename distpan to distplan

* [workflow] added precommit check for code consistency (#2401)

* [workflow] added precommit check for code consistency

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* polish code

* adapt new fx

* [workflow] added translation for non-english comments (#2414)

* [setup] refactored setup.py for dependency graph (#2413)

* change import

* update doc

* [workflow] auto comment if precommit check fails (#2417)

* [hotfix] add norm clearing for the overflow step (#2416)

* [examples] adding tflops to PaLM (#2365)

* [workflow]auto comment with test coverage report (#2419)

* [workflow]auto comment with test coverage report

* polish code

* polish yaml

* [doc] added documentation for CI/CD (#2420)

* [doc] added documentation for CI/CD

* polish markdown

* polish markdown

* polish markdown

* [example] removed duplicated stable diffusion example (#2424)

* [zero] add inference mode and its unit test (#2418)

* [workflow] report test coverage even if below threshold (#2431)

* [example] improved the clarity yof the example readme (#2427)

* [example] improved the clarity yof the example readme

* polish workflow

* polish workflow

* polish workflow

* polish workflow

* polish workflow

* polish workflow

* [ddp] add is_ddp_ignored (#2434)

[ddp] rename to is_ddp_ignored

* [workflow] make test coverage report collapsable (#2436)

* [autoparallel] add shard option (#2423)

* [fx] allow native ckpt trace and codegen. (#2438)

* [cli] provided more details if colossalai run fail (#2442)

* [autoparallel] integrate device mesh initialization into autoparallelize (#2393)

* [autoparallel] integrate device mesh initialization into autoparallelize

* add megatron solution

* update gpt autoparallel examples with latest api

* adapt beta value to fit the current computation cost

* [zero] fix state_dict and load_state_dict for ddp ignored parameters (#2443)

* [ddp] add is_ddp_ignored

[ddp] rename to is_ddp_ignored

* [zero] fix state_dict and load_state_dict

* fix bugs

* [zero] update unit test for ZeroDDP

* [example] updated the hybrid parallel tutorial (#2444)

* [example] updated the hybrid parallel tutorial

* polish code

* [zero] add warning for ignored parameters (#2446)

* [example] updated large-batch optimizer tutorial (#2448)

* [example] updated large-batch optimizer tutorial

* polish code

* polish code

* [example] fixed seed error in train_dreambooth_colossalai.py (#2445)

* [workflow] fixed the on-merge condition check (#2452)

* [workflow] automated the compatiblity test (#2453)

* [workflow] automated the compatiblity test

* polish code

* [autoparallel] update binary elementwise handler (#2451)

* [autoparallel] update binary elementwise handler

* polish

* [workflow] automated bdist wheel build (#2459)

* [workflow] automated bdist wheel build

* polish workflow

* polish readme

* polish readme

* Fix False warning in initialize.py (#2456)

* Update initialize.py

* pre-commit run check

* [examples] update autoparallel tutorial demo (#2449)

* [examples] update autoparallel tutorial demo

* add test_ci.sh

* polish

* add conda yaml

* [cli] fixed hostname mismatch error (#2465)

* [example] integrate autoparallel demo with CI (#2466)

* [example] integrate autoparallel demo with CI

* polish code

* polish code

* polish code

* polish code

* [zero] low level optim supports ProcessGroup (#2464)

* [example] update vit ci script (#2469)

* [example] update vit ci script

* [example] update requirements

* [example] update requirements

* [example] integrate seq-parallel tutorial with CI (#2463)

* [zero] polish low level optimizer (#2473)

* polish pp middleware (#2476)

Co-authored-by: Ziyue Jiang <ziyue.jiang@gmail.com>

* [example] update gpt gemini example ci test (#2477)

* [zero] add unit test for low-level zero init (#2474)

* [workflow] fixed the skip condition of  example weekly check workflow (#2481)

* [example] stable diffusion add roadmap

* add dummy test_ci.sh

* [example] stable diffusion add roadmap (#2482)

* [CI] add test_ci.sh for palm, opt and gpt (#2475)

* polish code

* [example] titans for gpt

* polish readme

* remove license

* polish code

* update readme

* [example] titans for gpt (#2484)

* [autoparallel] support origin activation ckpt on autoprallel system (#2468)

* [autochunk] support evoformer tracer (#2485)

support full evoformer tracer, which is a main module of alphafold. previously we just support a simplifed version of it.
1. support some evoformer's op in fx
2. support evoformer test
3. add repos for test code

* [example] fix requirements (#2488)

* [zero] add unit testings for hybrid parallelism  (#2486)

* [hotfix] gpt example titans bug #2493

* polish code and fix dataloader bugs

* [hotfix] gpt example titans bug #2493 (#2494)

* [fx] allow control of ckpt_codegen init (#2498)

* [fx] allow control of ckpt_codegen init

Currently in ColoGraphModule, ActivationCheckpointCodeGen will be set automatically in __init__. But other codegen can't be set if so. 
So I add an arg to control whether to set ActivationCheckpointCodeGen in __init__.

* code style

* [example] dreambooth example

* add test_ci.sh to dreambooth

* [autochunk] support autochunk on evoformer (#2497)

* Revert "Update parallel_context.py (#2408)"

This reverts commit 7d5640b9db.

* add avg partition (#2483)

Co-authored-by: Ziyue Jiang <ziyue.jiang@gmail.com>

* [auto-chunk] support extramsa (#3) (#2504)

* [utils] lazy init. (#2148)

* [utils] lazy init.

* [utils] remove description.

* [utils] complete.

* [utils] finalize.

* [utils] fix names.

* [autochunk] support parsing blocks (#2506)

* [zero] add strict ddp mode (#2508)

* [zero] add strict ddp mode

* [polish] add comments for strict ddp mode

* [zero] fix test error

* [doc] update opt and tutorial links (#2509)

* [workflow] fixed changed file detection (#2515)

Co-authored-by: oahzxl <xuanlei.zhao@gmail.com>
Co-authored-by: eric8607242 <e0928021388@gmail.com>
Co-authored-by: HELSON <c2h214748@gmail.com>
Co-authored-by: Frank Lee <somerlee.9@gmail.com>
Co-authored-by: Haofan Wang <haofanwang.ai@gmail.com>
Co-authored-by: Jiarui Fang <fangjiarui123@gmail.com>
Co-authored-by: ZijianYY <119492445+ZijianYY@users.noreply.github.com>
Co-authored-by: YuliangLiu0306 <72588413+YuliangLiu0306@users.noreply.github.com>
Co-authored-by: Super Daniel <78588128+super-dainiu@users.noreply.github.com>
Co-authored-by: ver217 <lhx0217@gmail.com>
Co-authored-by: Ziyue Jiang <ziyue.jiang97@gmail.com>
Co-authored-by: Ziyue Jiang <ziyue.jiang@gmail.com>
Co-authored-by: oahzxl <43881818+oahzxl@users.noreply.github.com>
Co-authored-by: binmakeswell <binmakeswell@gmail.com>
Co-authored-by: Fazzie-Maqianli <55798671+Fazziekey@users.noreply.github.com>
Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com>
This commit is contained in:
Boyuan Yao
2023-01-27 09:52:21 +08:00
committed by GitHub
parent ce08661eb1
commit 7a58dc5ad2
215 changed files with 8523 additions and 14916 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
examples/images/dreambooth/train_dreambooth_colossalai.py
View File

@@ -153,7 +153,8 @@ def parse_args(input_args=None):
"--gradient_accumulation_steps",
type=int,
default=1,
help="Number of updates steps to accumulate before performing a backward/update pass.",
help=
"Number of updates steps to accumulate before performing a backward/update pass. If using Gemini, it must be 1",
)
parser.add_argument(
"--gradient_checkpointing",
@@ -355,10 +356,14 @@ def gemini_zero_dpp(model: torch.nn.Module, placememt_policy: str = "auto"):
def main(args):
colossalai.launch_from_torch(config={})
if args.seed is not None:
gpc.set_seed(args.seed)
if args.seed is None:
colossalai.launch_from_torch(config={})
else:
colossalai.launch_from_torch(config={}, seed=args.seed)
local_rank = gpc.get_local_rank(ParallelMode.DATA)
world_size = gpc.get_world_size(ParallelMode.DATA)
if args.with_prior_preservation:
class_images_dir = Path(args.class_data_dir)
@@ -387,7 +392,7 @@ def main(args):
for example in tqdm(
sample_dataloader,
desc="Generating class images",
disable=not gpc.get_local_rank(ParallelMode.DATA) == 0,
disable=not local_rank == 0,
):
images = pipeline(example["prompt"]).images
@@ -399,7 +404,7 @@ def main(args):
del pipeline
# Handle the repository creation
if gpc.get_local_rank(ParallelMode.DATA) == 0:
if local_rank == 0:
if args.push_to_hub:
if args.hub_model_id is None:
repo_name = get_full_repo_name(Path(args.output_dir).name, token=args.hub_token)
@@ -464,8 +469,9 @@ def main(args):
if args.gradient_checkpointing:
unet.enable_gradient_checkpointing()
assert args.gradient_accumulation_steps == 1, "if using ColossalAI gradient_accumulation_steps must be set to 1."
if args.scale_lr:
args.learning_rate = args.learning_rate * args.gradient_accumulation_steps * args.train_batch_size * gpc.get_world_size(ParallelMode.DATA)
args.learning_rate = args.learning_rate * args.gradient_accumulation_steps * args.train_batch_size * world_size
unet = gemini_zero_dpp(unet, args.placement)
@@ -554,7 +560,7 @@ def main(args):
args.num_train_epochs = math.ceil(args.max_train_steps / num_update_steps_per_epoch)
# Train!
total_batch_size = args.train_batch_size * gpc.get_world_size(ParallelMode.DATA) * args.gradient_accumulation_steps
total_batch_size = args.train_batch_size * world_size * args.gradient_accumulation_steps
logger.info("***** Running training *****", ranks=[0])
logger.info(f" Num examples = {len(train_dataset)}", ranks=[0])
@@ -566,7 +572,7 @@ def main(args):
logger.info(f" Total optimization steps = {args.max_train_steps}", ranks=[0])
# Only show the progress bar once on each machine.
progress_bar = tqdm(range(args.max_train_steps), disable=not gpc.get_local_rank(ParallelMode.DATA) == 0)
progress_bar = tqdm(range(args.max_train_steps), disable=not local_rank == 0)
progress_bar.set_description("Steps")
global_step = 0
@@ -643,7 +649,7 @@ def main(args):
if global_step % args.save_steps == 0:
torch.cuda.synchronize()
torch_unet = get_static_torch_model(unet)
if gpc.get_local_rank(ParallelMode.DATA) == 0:
if local_rank == 0:
pipeline = DiffusionPipeline.from_pretrained(
args.pretrained_model_name_or_path,
unet=torch_unet,
@@ -658,7 +664,7 @@ def main(args):
torch.cuda.synchronize()
unet = get_static_torch_model(unet)
if gpc.get_local_rank(ParallelMode.DATA) == 0:
if local_rank == 0:
pipeline = DiffusionPipeline.from_pretrained(
args.pretrained_model_name_or_path,
unet=unet,