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[gemini] improve compatibility and add static placement policy (#4479)

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* [gemini] remove distributed-related part from colotensor (#4379)

* [gemini] remove process group dependency

* [gemini] remove tp part from colo tensor

* [gemini] patch inplace op

* [gemini] fix param op hook and update tests

* [test] remove useless tests

* [test] remove useless tests

* [misc] fix requirements

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [test] fix model zoo

* [misc] update requirements

* [gemini] refactor gemini optimizer and gemini ddp (#4398)

* [gemini] update optimizer interface

* [gemini] renaming gemini optimizer

* [gemini] refactor gemini ddp class

* [example] update gemini related example

* [example] update gemini related example

* [plugin] fix gemini plugin args

* [test] update gemini ckpt tests

* [gemini] fix checkpoint io

* [example] fix opt example requirements

* [example] fix opt example

* [example] fix opt example

* [example] fix opt example

* [gemini] add static placement policy (#4443)

* [gemini] add static placement policy

* [gemini] fix param offload

* [test] update gemini tests

* [plugin] update gemini plugin

* [plugin] update gemini plugin docstr

* [misc] fix flash attn requirement

* [test] fix gemini checkpoint io test

* [example] update resnet example result (#4457)

* [example] update bert example result (#4458)

* [doc] update gemini doc (#4468)

* [example] update gemini related examples (#4473)

* [example] update gpt example

* [example] update dreambooth example

* [example] update vit

* [example] update opt

* [example] update palm

* [example] update vit and opt benchmark

* [hotfix] fix bert in model zoo (#4480)

* [hotfix] fix bert in model zoo

* [test] remove chatglm gemini test

* [test] remove sam gemini test

* [test] remove vit gemini test

* [hotfix] fix opt tutorial example (#4497)

* [hotfix] fix opt tutorial example

* [hotfix] fix opt tutorial example
This commit is contained in:
Hongxin Liu
2023-08-24 09:29:25 +08:00
committed by GitHub
parent 285fe7ba71
commit 27061426f7
82 changed files with 1008 additions and 4036 deletions
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47
examples/language/opt/opt_benchmark.py
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@@ -1,22 +1,18 @@
import time
import torch
import tqdm
import transformers
from args import parse_benchmark_args
from transformers import AutoConfig, OPTForCausalLM
from transformers.utils.versions import require_version
import tqdm
import colossalai
from colossalai.nn.optimizer import HybridAdam
from colossalai.logging import disable_existing_loggers, get_dist_logger
from colossalai.tensor import ProcessGroup, ShardSpec
from colossalai.utils import get_current_device
from colossalai.zero import ColoInitContext
from colossalai.booster import Booster
from colossalai.booster.plugin import GeminiPlugin, LowLevelZeroPlugin, TorchDDPPlugin
from colossalai.cluster import DistCoordinator
from args import parse_benchmark_args
from colossalai.logging import disable_existing_loggers, get_dist_logger
from colossalai.nn.optimizer import HybridAdam
require_version("transformers>=4.20.0", "To fix: pip install -r requirements.txt")
@@ -61,11 +57,11 @@ def main():
transformers.utils.logging.set_verbosity_info()
else:
transformers.utils.logging.set_verbosity_error()
# Whether to set limit of memory capacity
if args.mem_cap > 0:
colo_memory_cap(args.mem_cap)
# Build OPT model
config = AutoConfig.from_pretrained(args.model_name_or_path)
model = OPTForCausalLM(config=config)
@@ -81,11 +77,7 @@ def main():
if args.plugin.startswith('torch_ddp'):
plugin = TorchDDPPlugin()
elif args.plugin == 'gemini':
plugin = GeminiPlugin(device=get_current_device(),
placement_policy='cpu',
pin_memory=True,
strict_ddp_mode=True,
initial_scale=2**5)
plugin = GeminiPlugin(offload_optim_frac=1.0, pin_memory=True, initial_scale=2**5)
elif args.plugin == 'low_level_zero':
plugin = LowLevelZeroPlugin(initial_scale=2**5)
logger.info(f"Set plugin as {args.plugin}", ranks=[0])
@@ -96,18 +88,18 @@ def main():
# Set booster
booster = Booster(plugin=plugin, **booster_kwargs)
model, optimizer, _, _, _ = booster.boost(model, optimizer)
SEQ_LEN = 1024
VOCAB_SIZE = 50257
# Start training.
logger.info(f"Start testing", ranks=[0])
progress_bar = tqdm.tqdm(total=args.max_train_steps, desc="Training Step", disable=not coordinator.is_master())
torch.cuda.synchronize()
model.train()
start_time = time.time()
for _ in range(args.max_train_steps):
input_ids, attn_mask = get_data(args.batch_size, SEQ_LEN, VOCAB_SIZE)
@@ -119,18 +111,19 @@ def main():
torch.cuda.synchronize()
progress_bar.update(1)
# Compute Statistics
# Compute Statistics
end_time = time.time()
throughput = "{:.4f}".format((world_size * args.max_train_steps * args.batch_size) / (end_time - start_time))
max_mem = format_num(torch.cuda.max_memory_allocated(device=torch.cuda.current_device()), bytes=True)
logger.info(f"Testing finished, "
f"batch size per gpu: {args.batch_size}, "
f"plugin: {args.plugin}, "
f"throughput: {throughput}, "
f"maximum memory usage per gpu: {max_mem}.",
ranks=[0])
logger.info(
f"Testing finished, "
f"batch size per gpu: {args.batch_size}, "
f"plugin: {args.plugin}, "
f"throughput: {throughput}, "
f"maximum memory usage per gpu: {max_mem}.",
ranks=[0])
if __name__ == "__main__":