ColossalAI/applications/ColossalChat/tests/test_train.sh
Wang Binluo eea37da6fa
[fp8] Merge feature/fp8_comm to main branch of Colossalai (#6016)
* add SimPO

* fix dataloader

* remove debug code

* add orpo

* fix style

* fix colossalai, transformers version

* fix colossalai, transformers version

* fix colossalai, transformers version

* fix torch colossalai version

* update transformers version

* [shardformer] DeepseekMoE support (#5871)

* [Feature] deepseek moe expert parallel implement

* [misc] fix typo, remove redundant file (#5867)

* [misc] fix typo

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [Feature] deepseek support & unit test

* [misc] remove debug code & useless print

* [misc] fix typos (#5872)

* [Feature] remove modeling file, use auto config. (#5884)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [Deepseek] remove redundant code (#5888)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [misc] remove redundant code

* [Feature/deepseek] resolve comment. (#5889)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [misc] remove redundant code

* [misc] mv module replacement into if branch

* [misc] add some warning message and modify some code in unit test

* [misc] fix typos

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* [Feat] Diffusion Model(PixArtAlpha/StableDiffusion3) Support (#5838)

* Diffusion Model Inference support

* Stable Diffusion 3 Support

* pixartalpha support

* [HotFix] CI,import,requirements-test for #5838 (#5892)

* [Hot Fix] CI,import,requirements-test

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [Feature] Enable PP + SP for llama (#5868)

* fix cross-PP-stage position id length diff bug

* fix typo

* fix typo

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* use a one cross entropy func for all shardformer models

---------

Co-authored-by: Edenzzzz <wtan45@wisc.edu>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [ShardFormer] Add Ulysses Sequence Parallelism support for Command-R, Qwen2 and ChatGLM (#5897)

* add benchmark for sft, dpo, simpo, orpo. Add benchmarking result. Support lora with gradient checkpoint

* fix style

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix eval

* hotfix citation

* [zero] support all-gather overlap (#5898)

* [zero] support all-gather overlap

* [zero] add overlap all-gather flag

* [misc] fix typo

* [zero] update api

* fix orpo cross entropy loss

* [Auto Parallel]: Speed up intra-op plan generation by 44% (#5446)

* Remove unnecessary calls to deepcopy

* Build DimSpec's difference dict only once

This change considerably speeds up construction speed of DimSpec objects. The difference_dict is the same for each DimSpec object, so a single copy of it is enough.

* Fix documentation of DimSpec's difference method

* [ShardFormer] fix qwen2 sp (#5903)

* [compatibility] support torch 2.2 (#5875)

* Support Pytorch 2.2.2

* keep build_on_pr file and update .compatibility

* fix object_to_tensor usage when torch>=2.3.0 (#5820)

* [misc] support torch2.3 (#5893)

* [misc] support torch2.3

* [devops] update compatibility ci

* [devops] update compatibility ci

* [devops] add debug

* [devops] add debug

* [devops] add debug

* [devops] add debug

* [devops] remove debug

* [devops] remove debug

* [release] update version (#5912)

* [plugin] support all-gather overlap for hybrid parallel (#5919)

* [plugin] fixed all-gather overlap support for hybrid parallel

* add kto

* fix style, add kto data sample

* [Examples] Add lazy init to OPT and GPT examples (#5924)

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* [ColossalChat] Hotfix for ColossalChat (#5910)

* add ignore and tiny llama

* fix path issue

* run style

* fix issue

* update bash

* add ignore and tiny llama

* fix path issue

* run style

* fix issue

* update bash

* fix ddp issue

* add Qwen 1.5 32B

* refactor tokenization

* [FIX BUG] UnboundLocalError: cannot access local variable 'default_conversation' where it is not associated with a value (#5931)

* cannot access local variable 'default_conversation' where it is not associated with a value

set default value for 'default_conversation'

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* fix test data

* refactor evaluation

* remove real data path

* remove real data path

* Add n_fused as an input from native_module (#5894)

* [FIX BUG] convert env param to int in (#5934)

* [Hotfix] Fix ZeRO typo #5936

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* [Feature] Add a switch to control whether the model checkpoint needs to be saved after each epoch ends (#5941)

* Add a switch to control whether the model checkpoint needs to be saved after each epoch ends

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* fix style

* fix style

* fix style

* [shardformer] hotfix attn mask (#5945)

* [shardformer] hotfix attn mask (#5947)

* [Feat] Distrifusion Acceleration Support for Diffusion Inference (#5895)

* Distrifusion Support source

* comp comm overlap optimization

* sd3 benchmark

* pixart distrifusion bug fix

* sd3 bug fix and benchmark

* generation bug fix

* naming fix

* add docstring, fix counter and shape error

* add reference

* readme and requirement

* [zero] hotfix update master params (#5951)

* [release] update version (#5952)

* [Chat] Fix lora (#5946)

* fix merging

* remove filepath

* fix style

* Update README.md (#5958)

* [hotfix] Remove unused plan section (#5957)

* remove readme

* fix readme

* update

* [test] add mixtral for sequence classification

* [test] add mixtral transformer test

* [moe] fix plugin

* [test] mixtra pp shard test

* [chore] handle non member group

* [zero] solve hang

* [test] pass mixtral shardformer test

* [moe] implement transit between non moe tp and ep

* [zero] solve hang

* [misc] solve booster hang by rename the variable

* solve hang when parallel mode = pp + dp

* [moe] implement submesh initialization

* [moe] add mixtral dp grad scaling when not all experts are activated

* [chore] manually revert unintended commit

* [chore] trivial fix

* [chore] arg pass & remove drop token

* [test] add mixtral modelling test

* [moe] implement tp

* [moe] test deepseek

* [moe] clean legacy code

* [Feature] MoE Ulysses Support (#5918)

* moe sp support

* moe sp bug solve

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [chore] minor fix

* [moe] init moe plugin comm setting with sp

* moe sp + ep bug fix

* [moe] finalize test (no pp)

* [moe] full test for deepseek and mixtral (pp + sp to fix)

* [chore] minor fix after rebase

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* [chore] solve moe ckpt test failure and some other arg pass failure

* [moe] remove ops

* [test] fix test: test_zero1_2

* [bug] fix: somehow logger hangs the program

* [moe] deepseek moe sp support

* [test] add check

* [deepseek] replace attn (a workaround for bug in transformers)

* [misc] skip redunant test

* [misc] remove debug/print code

* [moe] refactor mesh assignment

* Revert "[moe] implement submesh initialization"

This reverts commit 2f9bce6686.

* [chore] change moe_pg_mesh to private

* [misc] remove incompatible test config

* [misc] fix ci failure: change default value to false in moe plugin

* [misc] remove useless condition

* [chore] docstring

* [moe] remove force_overlap_comm flag and add warning instead

* [doc] add MoeHybridParallelPlugin docstring

* [moe] solve dp axis issue

* [chore] remove redundant test case, print string & reduce test tokens

* [feat] Dist Loader for Eval (#5950)

* support auto distributed data loader

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* support auto distributed data loader

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix tp error

* remove unused parameters

* remove unused

* update inference

* update docs

* update inference

---------

Co-authored-by: Michelle <qianranma8@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [lora] lora support hybrid parallel plugin (#5956)

* lora support hybrid plugin

* fix

* fix

* fix

* fix

* Support overall loss, update KTO logging

* [Docs] clarify launch port

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* [Hotfix] README link (#5966)

* update ignore

* update readme

* run style

* update readme

* [Hotfix] Avoid fused RMSnorm import error without apex (#5985)

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* [Chat] fix readme (#5989)

* fix readme

* fix readme, tokenization fully tested

* fix readme, tokenization fully tested

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: root <root@notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9-0.notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9.colossal-ai.svc.cluster.local>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* fix sync condition (#6000)

* [plugin] add cast inputs option for zero (#6003)

* [pre-commit.ci] pre-commit autoupdate (#5995)

updates:
- [github.com/psf/black-pre-commit-mirror: 24.4.2 → 24.8.0](https://github.com/psf/black-pre-commit-mirror/compare/24.4.2...24.8.0)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [misc] Bypass the huggingface bug to solve the mask mismatch problem (#5991)

* [Feature] Zigzag Ring attention (#5905)

* halfway

* fix cross-PP-stage position id length diff bug

* fix typo

* fix typo

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* unified cross entropy func for all shardformer models

* remove redundant lines

* add basic ring attn; debug cross entropy

* fwd bwd logic complete

* fwd bwd logic complete; add experimental triton rescale

* precision tests passed

* precision tests passed

* fix typos and remove misc files

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add sp_mode to benchmark; fix varlen interface

* update softmax_lse shape by new interface

* change tester name

* remove buffer clone; support packed seq layout

* add varlen tests

* fix typo

* all tests passed

* add dkv_group; fix mask

* remove debug statements

---------

Co-authored-by: Edenzzzz <wtan45@wisc.edu>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* [misc] update compatibility (#6008)

* [misc] update compatibility

* [misc] update requirements

* [devops] disable requirements cache

* [test] fix torch ddp test

* [test] fix rerun on address in use

* [test] fix lazy init

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix the merge

* fix the merge

* overlap kv comm with output rescale (#6017)

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* fix the merge

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix the merge

* fix

* fix

* fix the merge

* fix

* [misc] Use dist logger in plugins (#6011)

* use dist logger in plugins

* remove trash

* print on rank 0

---------

Co-authored-by: Edenzzzz <wtan45@wisc.edu>

* fix

* fix

* fix

* fix

* fix the merge

* fix

* fix

* fix

* fix

---------

Co-authored-by: YeAnbang <anbangy2@outlook.com>
Co-authored-by: Haze188 <haze188@qq.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Edenzzzz <wenxuan.tan@wisc.edu>
Co-authored-by: Edenzzzz <wtan45@wisc.edu>
Co-authored-by: Runyu Lu <77330637+LRY89757@users.noreply.github.com>
Co-authored-by: Guangyao Zhang <xjtu521@qq.com>
Co-authored-by: YeAnbang <44796419+YeAnbang@users.noreply.github.com>
Co-authored-by: Hongxin Liu <lhx0217@gmail.com>
Co-authored-by: Stephan Kö <stephankoe@users.noreply.github.com>
Co-authored-by: アマデウス <kurisusnowdeng@users.noreply.github.com>
Co-authored-by: Tong Li <tong.li352711588@gmail.com>
Co-authored-by: zhurunhua <1281592874@qq.com>
Co-authored-by: Insu Jang <insujang@umich.edu>
Co-authored-by: Gao, Ruiyuan <905370712@qq.com>
Co-authored-by: hxwang <wang1570@e.ntu.edu.sg>
Co-authored-by: Michelle <qianranma8@gmail.com>
Co-authored-by: root <root@notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9-0.notebook-8f919155-6035-47b4-9c6f-1be133b9e2c9.colossal-ai.svc.cluster.local>
2024-08-22 09:21:34 +08:00

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Executable File

#!/usr/bin/env bash
set_n_least_used_CUDA_VISIBLE_DEVICES() {
local n=${1:-"9999"}
echo "GPU Memory Usage:"
local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv |
tail -n +2 |
nl -v 0 |
tee /dev/tty |
sort -g -k 2 |
awk '{print $1}' |
head -n $n)
export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
echo "Now CUDA_VISIBLE_DEVICES is set to:"
echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
}
set_n_least_used_CUDA_VISIBLE_DEVICES 2
set -xu
NUM_RETRY=3
BASE_DIR=$(dirname $(dirname $(realpath $BASH_SOURCE)))
EXAMPLES_DIR=$BASE_DIR/examples
CONFIG_DIR=$BASE_DIR/config
TEMP_DIR=$BASE_DIR/temp
TEST_DIR=$BASE_DIR/tests
MODEL_SAVE_PATH=$TEMP_DIR/rlhf_models
MODELS_DIR=$TEMP_DIR/models_config
# Skip those tests due to CI tests timeout
MODELS=('llama')
ADVANCED_PLUGINS=('zero2' 'sp_split_gather' 'sp_ring' 'sp_all_to_all' 'tp_zero2' '3d' 'gemini' 'gemini_auto' 'zero2_cpu') # pp is still buggy
PLUGINS=('zero2' '3d' 'gemini' 'gemini_auto' 'zero2_cpu')
LORA_RANK=('0') # skip to reduce CI execution time, can pass all locally
LORA_CONFIG_ENABLE="--lora_config $BASE_DIR/examples/training_scripts/lora_config.json"
export OMP_NUM_THREADS=8
get_pretrain() {
local model=$1
if [[ $model == "llama" ]]; then
echo "nickypro/tinyllama-110M"
elif [[ $model == "opt" ]]; then
echo "facebook/opt-125m"
else
echo "Unknown model $model"
exit 1
fi
}
get_tokenizer_dirs() {
local model=$1
if [[ $model == "llama" ]]; then
echo "hf-internal-testing/llama-tokenizer"
elif [[ $model == "opt" ]]; then
echo "facebook/opt-125m"
else
echo "Unknown model $model"
exit 1
fi
}
get_conversation_template_config() {
local model=$1
if [[ $model == "llama" ]]; then
echo "$TEST_DIR/llama.json"
elif [[ $model == "opt" ]]; then
echo "$TEST_DIR/opt.json"
else
echo "Unknown model $model"
exit 1
fi
}
random_choice() {
local arr=("$@")
local len=${#arr[@]}
local idx=$((RANDOM % len))
echo ${arr[$idx]}
}
echo "[Test]: testing sft ..."
SKIPPED_TESTS=(
llama-3d-20 # 3d plugin doesn't support lora
llama-gemini_auto-20 # gemini_auto plugin doesn't support lora
llama-gemini-20 # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${ADVANCED_PLUGINS[@]}; do
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='2'
pp='1'
zero_stage='0'
sp='1'
sp_mode='split_gather'
enable_sequence_parallelism=''
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
if [[ $plugin == "3d" ]]; then
tp='2'
bs='8'
fi
if [[ $plugin == "tp_zero2" ]]; then
tp='2'
bs='8'
zero_stage='2'
plugin='3d'
fi
if [[ $plugin == "tp_pp" ]]; then
tp='2'
bs='8'
pp='2'
plugin='3d'
fi
if [[ $plugin == "pp" ]]; then
bs='8'
pp='2'
plugin='3d'
fi
if [[ $plugin == "sp_split_gather" ]]; then
enable_sequence_parallelism='--enable_sequence_parallelism'
sp_mode='split_gather'
tp='2'
sp='1'
bs='8'
plugin='3d'
fi
if [[ $plugin == "sp_ring" ]]; then
enable_sequence_parallelism='--enable_sequence_parallelism'
sp_mode='ring'
tp='2'
sp='1'
bs='8'
plugin='3d'
fi
if [[ $plugin == "sp_all_to_all" ]]; then
enable_sequence_parallelism='--enable_sequence_parallelism'
sp_mode='all_to_all'
tp='1'
sp='2'
bs='8'
plugin='3d'
fi
grad_accu='2'
# Check if the plugin is either "gemini_auto" or "gemini" and set grad_accu to '1'
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a dataset=()
for split in $(seq -f "%05g" 0 0); do
dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_sft/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_sft.py \
--pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--dataset ${dataset[@]} \
--eval_dataset ${dataset[@]} \
--save_path $MODEL_SAVE_PATH \
--config_file $MODELS_DIR/config.jsonl \
$lora_config \
--plugin $plugin \
--batch_size $bs \
--max_epochs 1 \
--accumulation_steps $grad_accu \
--tp $tp \
--pp $pp \
--zero_stage $zero_stage \
--sp $sp \
--sp_mode $sp_mode \
$enable_sequence_parallelism \
--lr 2e-5 \
$grad_ckpt \
--max_len 400 \
--use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done
echo "[Test]: testing reward model ..."
SKIPPED_TESTS=(
llama-3d-20 # 3d plugin doesn't support lora
llama-gemini_auto-20 # gemini_auto plugin doesn't support lora
llama-gemini-20 # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${PLUGINS[@]}; do
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='2'
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
if [[ $plugin == "3d" ]]; then
tp='2'
bs='8'
fi
grad_accu='2'
# gemini_auto and gemini doesn't support gradient accumulation
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a dataset=()
for split in $(seq -f "%05g" 0 0); do
dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_preference/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_rm.py \
--pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--dataset ${dataset[@]} \
--eval_dataset ${dataset[@]} \
--save_dir $MODEL_SAVE_PATH \
--config_file $MODELS_DIR/config.jsonl \
$lora_config \
--plugin $plugin \
--batch_size $bs \
--max_epochs 1 \
--accumulation_steps $grad_accu \
--tp $tp \
--lr 2e-5 \
$grad_ckpt \
--max_len 400 \
--use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done
echo "[Test]: testing ppo ..."
SKIPPED_TESTS=(
llama-3d # 3d plugin doesn't support lora
llama-gemini # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${PLUGINS[@]}; do
if [[ $plugin == "gemini_auto" ]]; then
echo "[Test]: Skipped $model-$plugin"
continue # gemini_auto plugin doesn't support generation
fi
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='4'
ebs='8'
conversation_template=$(get_conversation_template_config $model)
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
if [[ $plugin == "3d" ]]; then
tp='2'
bs='16'
ebs='32'
fi
grad_accu='2'
# gemini_auto and gemini doesn't support gradient accumulation
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
# gemini_auto and gemini doesn't support generation
if [[ $plugin == "gemini_auto" ]]; then
# gemini-auto doesn't support generation
echo "[Test]: Skipped $model-$plugin"
continue
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a prompt_dataset=()
for split in $(seq -f "%05g" 0 0); do
prompt_dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_prompt/arrow/part-$split")
done
declare -a ptx_dataset=()
for split in $(seq -f "%05g" 0 0); do
ptx_dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_sft/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_ppo.py \
--pretrain $pretrain \
--rm_pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--conversation_template_config $conversation_template \
--prompt_dataset ${prompt_dataset[@]} \
--ptx_dataset ${ptx_dataset[@]} \
--ptx_batch_size 1 \
--ptx_coef 0.2 \
--save_path $MODEL_SAVE_PATH \
$lora_config \
--plugin $plugin \
--num_episodes 5 \
--num_collect_steps 1 \
--num_update_steps 1 \
--experience_batch_size $ebs \
--train_batch_size $bs \
--accumulation_steps $grad_accu \
--lr 9e-6 \
--mixed_precision "bf16" \
--grad_clip 1.0 \
--tp $tp \
--lr 2e-5 \
$grad_ckpt \
--max_len 400 \
--max_seq_len 10 \
# --use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done
echo "[Test]: testing DPO ..."
SKIPPED_TESTS=(
llama-3d-20 # 3d plugin doesn't support lora
llama-gemini_auto-20 # gemini_auto plugin doesn't support lora
llama-gemini-20 # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${PLUGINS[@]}; do
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='2'
if [[ $plugin == "3d" ]]; then
tp='2'
bs='8'
fi
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
grad_accu='2'
# gemini_auto and gemini doesn't support gradient accumulation
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
# gemini_auto doesn't support generation
# (need to calculate ref_model logits through forwarding in inference mode)
if [[ $plugin == "gemini_auto" ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a dataset=()
for split in $(seq -f "%05g" 0 0); do
dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_preference/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_dpo.py \
--pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--dataset ${dataset[@]} \
--eval_dataset ${dataset[@]} \
--save_dir $MODEL_SAVE_PATH \
--config_file $MODELS_DIR/config.jsonl \
$lora_config \
--plugin $plugin \
--batch_size $bs \
--max_epochs 1 \
--accumulation_steps $grad_accu \
--tp $tp \
--lr 2e-5 \
$grad_ckpt \
--max_len 400 \
--use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done
echo "[Test]: testing ORPO ..."
SKIPPED_TESTS=(
llama-3d-20 # 3d plugin doesn't support lora
llama-gemini_auto-20 # gemini_auto plugin doesn't support lora
llama-gemini-20 # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${PLUGINS[@]}; do
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='2'
if [[ $plugin == "3d" ]]; then
tp='2'
bs='8'
fi
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
grad_accu='2'
# gemini_auto and gemini doesn't support gradient accumulation
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
# gemini_auto doesn't support generation
# (need to calculate ref_model logits through forwarding in inference mode)
if [[ $plugin == "gemini_auto" ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a dataset=()
for split in $(seq -f "%05g" 0 0); do
dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_preference/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_orpo.py \
--pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--dataset ${dataset[@]} \
--eval_dataset ${dataset[@]} \
--save_dir $MODEL_SAVE_PATH \
--config_file $MODELS_DIR/config.jsonl \
$lora_config \
--plugin $plugin \
--batch_size $bs \
--max_epochs 1 \
--accumulation_steps $grad_accu \
--tp $tp \
--lr 2e-5 \
$grad_ckpt \
--max_len 400 \
--use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done
echo "[Test]: testing KTO ..."
SKIPPED_TESTS=(
llama-3d-20 # 3d plugin doesn't support lora
llama-gemini_auto-20 # gemini_auto plugin doesn't support lora
llama-gemini-20 # gemini doesn't support lora
)
GRAD_CKPTS=('--grad_checkpoint')
for lora_rank in ${LORA_RANK[@]}; do
for model in ${MODELS[@]}; do
for plugin in ${PLUGINS[@]}; do
if [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin-$lora_rank " ]]; then
echo "[Test]: Skipped $model-$plugin-$lora_rank"
continue
elif [[ " ${SKIPPED_TESTS[*]} " =~ " $model-$plugin " ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
pretrain=$(get_pretrain $model)
tokenizer_dir=$(get_tokenizer_dirs $model)
grad_ckpt=$(random_choice "${GRAD_CKPTS[@]}")
tp='1'
bs='2'
if [[ $plugin == "3d" ]]; then
tp='2'
bs='8'
fi
if [[ $plugin == "zero2" ]]; then
lora_config=$LORA_CONFIG_ENABLE
else
lora_config=""
fi
grad_accu='2'
# gemini_auto and gemini doesn't support gradient accumulation
if [[ $plugin == "gemini_auto" ]]; then
grad_accu='1'
fi
# gemini_auto doesn't support generation
# (need to calculate ref_model logits through forwarding in inference mode)
if [[ $plugin == "gemini_auto" ]]; then
echo "[Test]: Skipped $model-$plugin"
continue
fi
for i in $(seq $NUM_RETRY); do
echo "[Test]: $model-$plugin-$lora_rank, attempt $i"
declare -a dataset=()
for split in $(seq -f "%05g" 0 0); do
dataset+=("$TEMP_DIR/rlhf_data/tokenized_${model}_kto/arrow/part-$split")
done
colossalai run --nproc_per_node 2 --master_port 31332 $EXAMPLES_DIR/training_scripts/train_kto.py \
--pretrain $pretrain \
--tokenizer_dir $tokenizer_dir \
--dataset ${dataset[@]} \
--eval_dataset ${dataset[@]} \
--save_dir $MODEL_SAVE_PATH \
--config_file $MODELS_DIR/config.jsonl \
$lora_config \
--plugin $plugin \
--batch_size $bs \
--max_epochs 1 \
--accumulation_steps $grad_accu \
--tp $tp \
--lr 2e-5 \
--auto_weight \
--desirable_weight 1.2 \
$grad_ckpt \
--max_len 400 \
--use_flash_attn
passed=$?
if [ $passed -eq 0 ]; then
rm -rf ${MODEL_SAVE_PATH:?}/*
rm -rf ${MODELS_DIR:?}/*
break
fi
done
if [ $passed -ne 0 ]; then
echo "[Test]: Failed $model-$plugin-$lora_rank"
exit 1
fi
done
done
done