[ci] fixed booster test (#5251)

* [ci] fixed booster test

* [ci] fixed booster test

* [ci] fixed booster test
pull/5272/head
Frank Lee 2024-01-11 16:04:45 +08:00 committed by GitHub
parent edf94a35c3
commit d5eeeb1416
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5 changed files with 12 additions and 14 deletions

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@ -90,7 +90,7 @@ jobs:
runs-on: [self-hosted, gpu]
container:
image: hpcaitech/pytorch-cuda:2.1.0-12.1.0
options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
options: --gpus all --rm -v /dev/shm -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
timeout-minutes: 60
defaults:
run:
@ -165,7 +165,6 @@ jobs:
--ignore tests/test_checkpoint_io \
tests/
env:
NCCL_SHM_DISABLE: 1
LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
LLAMA_PATH: /data/scratch/llama-tiny
@ -205,4 +204,3 @@ jobs:
with:
name: report
path: report/

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@ -13,15 +13,16 @@ jobs:
runs-on: [self-hosted, gpu]
container:
image: hpcaitech/pytorch-cuda:2.0.0-11.7.0
options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10 -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
options: --gpus all --rm -v /dev/shm -v /data/scratch/llama-tiny:/data/scratch/llama-tiny
timeout-minutes: 90
steps:
- name: Check GPU Availability # ensure all GPUs have enough memory
id: check-avai
run: |
avai=true
for i in $(seq 0 3);
do
ngpu=$(nvidia-smi --query-gpu=name --format=csv,noheader | wc -l)
endIndex=$(($ngpu-1))
for i in $(seq 0 $endIndex);
gpu_used=$(nvidia-smi -i $i --query-gpu=memory.used --format=csv,noheader,nounits)
[ "$gpu_used" -gt "2000" ] && avai=false
done
@ -74,7 +75,7 @@ jobs:
if: ${{ failure() }}
run: |
url=$SERVER_URL/$REPO/actions/runs/$RUN_ID
msg="Scheduled Build and Test failed on 8 GPUs, please visit $url for details"
msg="Scheduled Build and Test failed, please visit $url for details"
echo $msg
python .github/workflows/scripts/send_message_to_lark.py -m "$msg" -u $WEBHOOK_URL
env:

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@ -2,7 +2,6 @@ import torch
from colossalai.shardformer.modeling.chatglm2_6b.configuration_chatglm import ChatGLMConfig
from colossalai.shardformer.modeling.chatglm2_6b.modeling_chatglm import ChatGLMForConditionalGeneration, ChatGLMModel
from ..registry import ModelAttribute, model_zoo
# ================================

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@ -10,10 +10,11 @@ from colossalai.booster.plugin import HybridParallelPlugin
from colossalai.fx import is_compatible_with_meta
from colossalai.lazy.lazy_init import LazyInitContext
from colossalai.nn.optimizer import HybridAdam
from colossalai.testing import parameterize, rerun_if_address_is_in_use, spawn
from colossalai.testing import clear_cache_before_run, parameterize, rerun_if_address_is_in_use, spawn
from tests.kit.model_zoo import model_zoo
@clear_cache_before_run()
def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn) -> Optional[str]:
try:
if init_method == "lazy":
@ -69,7 +70,6 @@ def check_3d_plugin(init_method: str = "none", early_stop: bool = True):
"transformers_llama_for_casual_lm"
).items():
err = run_fn(init_method, model_fn, data_gen_fn, output_transform_fn)
torch.cuda.empty_cache()
if err is None:
passed_models.append(name)

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@ -12,10 +12,11 @@ from colossalai.fx import is_compatible_with_meta
from colossalai.lazy.lazy_init import LazyInitContext
from colossalai.nn.optimizer import HybridAdam
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, COMMON_MODELS, IS_FAST_TEST
from colossalai.testing import clear_cache_before_run, parameterize, rerun_if_address_is_in_use, spawn
from tests.kit.model_zoo import COMMON_MODELS, IS_FAST_TEST, model_zoo
@clear_cache_before_run()
def run_fn(init_method, model_fn, data_gen_fn, output_transform_fn, zero_size, tp_size) -> Optional[str]:
try:
if init_method == "lazy":
@ -116,7 +117,7 @@ def check_gemini_plugin(
"transformers_falcon_for_sequence_classification",
"transformers_falcon_for_token_classification",
"transformers_falcon_for_question_answering",
"transformers_gptj_lm", # lead to OOM when running in ci
"transformers_gptj_lm", # lead to OOM when running in ci
"transformers_gptj_for_question_answering",
"transformers_gptj_for_sequence_classification",
]:
@ -145,7 +146,6 @@ def check_gemini_plugin(
tp_size = 1
err = run_fn(init_method, model_fn, data_gen_fn, output_transform_fn, zero_size, tp_size)
torch.cuda.empty_cache()
if err is None:
passed_models.append(name)
else: