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fix qwen&baichaun&gpt ci error #9650

Merged
1 change: 1 addition & 0 deletions llm/auto_parallel/qwen/run_pretrain_3D_auto.py
Original file line number Diff line number Diff line change
Expand Up @@ -356,6 +356,7 @@ def get_train_data_file(args):
class PretrainingTrainer(AutoTrainer):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.is_pretraining = True

def _wrap_for_dist_loader(self, train_dataloader):
dist_loader = super()._wrap_for_dist_loader(train_dataloader)
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1 change: 1 addition & 0 deletions paddlenlp/transformers/gpt/configuration.py
Original file line number Diff line number Diff line change
Expand Up @@ -86,6 +86,7 @@
"eol_token_id": 198,
},
"gpt3-13B-en": { # 13B
"architectures": ["GPTForCausalLM"],
"vocab_size": 50304,
"hidden_size": 5120,
"num_hidden_layers": 40,
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62 changes: 45 additions & 17 deletions paddlenlp/transformers/qwen/modeling_3D_auto.py
Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,8 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import math
import os
import warnings
from functools import partial
from typing import List
Expand Down Expand Up @@ -84,6 +84,22 @@ def get_triangle_upper_mask(x, mask=None):
return mask


def enable_fuse_ffn_qkv_pass():
if os.getenv("FLAGS_enable_fused_ffn_qkv_pass") in [
"True",
"true",
"1",
]:
return True
else:
return False


def get_use_casual_mask():
"""Get the value of the 'USE_CASUAL_MASK' environment variable."""
return os.getenv("USE_CASUAL_MASK", "False") == "True"


attention_cnt = 0


Expand Down Expand Up @@ -304,12 +320,20 @@ def __init__(self, config, ipp=None):
super().__init__()
ff_dim_in = config.intermediate_size // 2
self.fuse_attention_ffn = config.fuse_attention_ffn
self.w1 = nn.Linear(config.hidden_size, ff_dim_in, bias_attr=not config.no_bias)
self.w2 = nn.Linear(config.hidden_size, ff_dim_in, bias_attr=not config.no_bias)
self.c_proj = nn.Linear(ff_dim_in, config.hidden_size, bias_attr=not config.no_bias)
self.ipp = ipp
self.w1.weight = dist.shard_tensor(self.w1.weight, get_mesh(self.ipp), [dist.Replicate(), dist.Shard(1)])
self.w2.weight = dist.shard_tensor(self.w2.weight, get_mesh(self.ipp), [dist.Replicate(), dist.Shard(1)])
if config.fuse_attention_ffn and not enable_fuse_ffn_qkv_pass():
self.gate_up_fused_proj = nn.Linear(config.hidden_size, ff_dim_in * 2, bias_attr=not config.no_bias)
self.gate_up_fused_proj.weight = dist.shard_tensor(
self.gate_up_fused_proj.weight,
get_mesh(self.ipp),
[dist.Replicate(), dist.Shard(1)],
)
else:
self.w1 = nn.Linear(config.hidden_size, ff_dim_in, bias_attr=not config.no_bias)
self.w2 = nn.Linear(config.hidden_size, ff_dim_in, bias_attr=not config.no_bias)
self.w1.weight = dist.shard_tensor(self.w1.weight, get_mesh(self.ipp), [dist.Replicate(), dist.Shard(1)])
self.w2.weight = dist.shard_tensor(self.w2.weight, get_mesh(self.ipp), [dist.Replicate(), dist.Shard(1)])
self.c_proj = nn.Linear(ff_dim_in, config.hidden_size, bias_attr=not config.no_bias)
self.c_proj.weight = dist.shard_tensor(
self.c_proj.weight, get_mesh(self.ipp), [dist.Replicate(), dist.Shard(0)]
)
Expand All @@ -321,7 +345,7 @@ def forward(self, hidden_states):
# a2 = self.w2(hidden_states)
# intermediate_parallel = a1 * F.silu(a2)
# down
if self.fuse_attention_ffn:
if self.fuse_attention_ffn and not enable_fuse_ffn_qkv_pass():
intermediate_parallel = swiglu(self.gate_up_fused_proj(hidden_states))
else:
intermediate_parallel = swiglu(self.w2(hidden_states), self.w1(hidden_states))
Expand Down Expand Up @@ -652,16 +676,20 @@ def forward(

hidden_states = inputs_embeds

# bool 4D mask
attention_mask = self.get_masks(
input_shape[0], input_shape[1], past_length, dtype=hidden_states.dtype, padding_mask=attention_mask
)
# TODO(GhostScreaming): how to fix paddle.finfo?
zero = paddle.zeros(attention_mask.shape, dtype=paddle.bfloat16)
neg_inf = paddle.full_like(attention_mask, paddle.finfo(paddle.bfloat16).min, dtype=paddle.bfloat16)
# dtype 4D mask
attention_mask = paddle.where(attention_mask, zero, neg_inf)
attention_mask = dist.shard_tensor(attention_mask, get_mesh(), [dist.Replicate(), dist.Replicate()])
use_casual_mask = get_use_casual_mask()
if use_casual_mask:
attention_mask = None
else:
# bool 4D mask
attention_mask = self.get_masks(
input_shape[0], input_shape[1], past_length, dtype=hidden_states.dtype, padding_mask=attention_mask
)
# TODO(GhostScreaming): how to fix paddle.finfo?
zero = paddle.zeros(attention_mask.shape, dtype=paddle.bfloat16)
neg_inf = paddle.full_like(attention_mask, paddle.finfo(paddle.bfloat16).min, dtype=paddle.bfloat16)
# dtype 4D mask
attention_mask = paddle.where(attention_mask, zero, neg_inf)
attention_mask = dist.shard_tensor(attention_mask, get_mesh(), [dist.Replicate(), dist.Replicate()])
hidden_states = self.drop(hidden_states)
hidden_states = dist.reshard(hidden_states, get_mesh(), [dist.Shard(0), dist.Replicate()])
output_shape = input_shape + [
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
"tensor_parallel_degree": 4,
"pipeline_parallel_degree": 1,
"virtual_pp_degree": 1,
"sequence_parallel": 1,
"sequence_parallel": 1,
"sharding_parallel_degree": 8,
"sharding": "stage1",
"pipeline_parallel_config": "enable_sharding_comm_overlap enable_release_grads ",
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Original file line number Diff line number Diff line change
@@ -0,0 +1,25 @@
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

param="model_item=gpt3-13b_pretrain "
param+="run_mode=DP1_MP2_PP4_VPP5_Sharding4_Stage1 "
param+="device_num=N4C32 "
param+="global_batch_size=128 "
param+="nnodes=4 "
param+="model_type=gpt3_13b "

cd ./tests
bash ./test_tipc/dygraph/hybrid_parallelism/gpt3/benchmark_common/prepare.sh

bash -c "${param} bash ./test_tipc/dygraph/hybrid_parallelism/gpt3/benchmark_common/run_benchmark.sh"
Original file line number Diff line number Diff line change
@@ -0,0 +1,45 @@
{
"model_name_or_path": "gpt3-13B-en",
"tokenizer_name_or_path": "gpt3-13B-en",
"input_dir": "./data",
"output_dir": "./output/gpt3-13b_pretrain_ckpts",
"split": "949,50,1",
"max_seq_length": 4096,
"gradient_accumulation_steps": 32,
"tensor_parallel_degree": 2,
"pipeline_parallel_degree": 4,
"virtual_pp_degree": 5,
"sequence_parallel": 0,
"sharding": "stage1",
"pipeline_parallel_config": "enable_sharding_comm_overlap enable_release_grads ",
"tensor_parallel_config": "enable_mp_async_allreduce enable_sp_async_reduce_scatter enable_mp_skip_c_identity enable_mp_fused_linear_param_grad_add",
"per_device_train_batch_size": 1,
"use_flash_attention": true,
"use_fused_rms_norm": true,
"fuse_attention_qkv": true,
"use_fused_rope": true,
"fuse_attention_ffn": true,
"enable_linear_fused_grad_add": true,
"bf16": true,
"fp16_opt_level": "O2",
"scale_loss": 1024,
"learning_rate": 1e-05,
"min_learning_rate": 5e-06,
"max_steps": 200,
"save_steps": 5000,
"weight_decay": 0.01,
"warmup_ratio": 0.01,
"max_grad_norm": 1.0,
"logging_steps": 2,
"dataloader_num_workers": 1,
"eval_steps": 1000,
"disable_tqdm": true,
"continue_training": 0,
"recompute": false,
"recompute_granularity": "full_attn",
"do_train": true,
"pp_recompute_interval": 1,
"device": "gpu",
"amp_master_grad": true,
"sharding_parallel_config": "split_param enable_stage1_overlap enable_stage1_allgather_overlap"
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,37 @@
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

python -m pip install -r ../requirements.txt
python -m pip install -r ../requirements-dev.txt

# install fused_ln custom ops
cd ../slm/model_zoo/gpt-3/external_ops/
python setup.py install
cd -

python -m pip install tiktoken

# install fast_dataindex
cd ../llm/
rm -rf data
mkdir data
cd data
# download data
wget https://bj.bcebos.com/paddlenlp/models/transformers/gpt/data/gpt_en_dataset_300m_ids.npy
wget https://bj.bcebos.com/paddlenlp/models/transformers/gpt/data/gpt_en_dataset_300m_idx.npz
cd -

# mv autoconfig
rm -rf auto_config_*
cp -r ../tests/test_tipc/dygraph/hybrid_parallelism/gpt3/auto_config_* ./
Original file line number Diff line number Diff line change
@@ -0,0 +1,134 @@
#!/usr/bin/env bash

# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Test training benchmark for a model.
# Usage:bash benchmark/run_benchmark.sh ${model_name_or_path} ${per_device_train_batch_size} ${tensor_parallel_degree} ${pipeline_parallel_degree} ${virtual_pp_degree} ${sequence_parallel} ${sharding_parallel_degree} ${sharding} ${recompute} ${run_mode} ${device_num}
function _set_params(){
model_item=${model_item:-"gpt3-13b_pretrain"}
run_mode=${run_mode:-"MP2-PP1"}
device_num=${device_num:-"N1C8"}
global_batch_size=${global_batch_size:-64}
fp_item="bf16"
MODEL_TYPE=${model_type:-"gpt3_13b"}

ip_lists=($(echo $TRAINER_INSTANCES | tr ',' ' '))
master_ip=${ip_lists[0]}
nnodes=${nnodes:-1}

base_batch_size=${global_batch_size}
profiling=${PROFILING:-"false"} # (必选) Profiling 开关,默认关闭,通过全局变量传递
model_repo="PaddleNLP" # (必选) 模型套件的名字
speed_unit="tokens/s" # (必选)速度指标单位
skip_steps=10 # (必选)解析日志,跳过模型前几个性能不稳定的step
keyword="interval_tokens_per_second_per_device:" # (必选)解析日志,筛选出性能数据所在行的关键字
convergence_key="loss:" # (可选)解析日志,筛选出收敛数据所在行的关键字 如:convergence_key="loss:"
model_mode=5 # 获取ips数据及单位,仅跳过skip_steps后计算均值,单位保持token/s不变

# 以下为通用执行命令,无特殊可不用修改
model_name=${model_item}_bs${global_batch_size}_${fp_item}_${run_mode} # (必填) 且格式不要改动,与竞品名称对齐
device=${CUDA_VISIBLE_DEVICES//,/ }
arr=(${device})
num_gpu_devices=${#arr[*]}
run_log_path=${TRAIN_LOG_DIR:-$(pwd)} # (必填) TRAIN_LOG_DIR benchmark框架设置该参数为全局变量
profiling_log_path=${PROFILING_LOG_DIR:-$(pwd)} # (必填) PROFILING_LOG_DIR benchmark框架设置该参数为全局变量
speed_log_path=${LOG_PATH_INDEX_DIR:-$(pwd)}
train_log_file=${run_log_path}/${model_repo}_${model_name}_${device_num}_log
mkdir -p $(dirname ${train_log_file})

profiling_log_file=${profiling_log_path}/${model_repo}_${model_name}_${device_num}_profiling
mkdir -p $(dirname ${profiling_log_file})

speed_log_file=${speed_log_path}/${model_repo}_${model_name}_${device_num}_speed
mkdir -p $(dirname ${speed_log_file})

OUTPUT_PATH=${run_log_path}/output
}

function _train(){
batch_size=${per_device_train_batch_size} # 如果模型跑多卡单进程时,请在_train函数中计算出多卡需要的bs

if [ -d $OUTPUT_PATH ]; then
rm -rf $OUTPUT_PATH
fi
mkdir $OUTPUT_PATH

echo "current CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES}, model_name=${model_name}, device_num=${device_num}, is profiling=${profiling}"

if [ ${profiling} == "true" ];then
add_options="--profiler_options=\"batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile\""
log_file=${profiling_log_file}
else
add_options=""
log_file=${train_log_file}
fi

if [ ${PADDLE_TRAINER_ID} ]; then
PADDLE_RANK_OPTION=" --rank ${PADDLE_TRAINER_ID}"
else
PADDLE_RANK_OPTION=""
fi

distributed_args="--master $master_ip:36677 --nnodes $nnodes ${PADDLE_RANK_OPTION} --run_mode=collective"

echo "==========System Env============="
env
echo "================================="

# 以下为通用执行命令,无特殊可不用修改
case ${device_num} in
N1C8) echo "Run with: device_num=${device_num}, run_mode=${run_mode}"
train_cmd="python -u -m paddle.distributed.launch --gpus=0,1,2,3,4,5,6,7 \
--nnodes 1 --nproc_per_node 8 \
--log_dir mylog run_pretrain.py \
./auto_config_${MODEL_TYPE}/pretrain-${MODEL_TYPE}-config.json"
;;
N4C32) echo "Run with: device_num=${device_num} run_mode=${run_mode}"
train_cmd="python -u -m paddle.distributed.launch --gpus=0,1,2,3,4,5,6,7 \
${distributed_args} --log_dir mylog run_pretrain.py \
./auto_config_${MODEL_TYPE}/pretrain-${MODEL_TYPE}-config.json"
;;
*) echo "Run with: device_num=${device_num}, run_mode=${run_mode}"
train_cmd="python -u -m paddle.distributed.launch --gpus=0,1,2,3,4,5,6,7 \
${distributed_args} --log_dir mylog run_pretrain.py \
./auto_config_${MODEL_TYPE}/pretrain-${MODEL_TYPE}-config.json"
;;
esac
cd ../llm
rm -rf mylog && rm -rf checkpoints

echo "train_cmd: ${train_cmd} log_file: ${log_file}"
timeout 40m ${train_cmd} > ${log_file} 2>&1

if [ $? -ne 0 ];then
echo -e "${model_name}, FAIL"
else
echo -e "${model_name}, SUCCESS"
fi

#kill -9 `ps -ef|grep 'python'|awk '{print $2}'`
if [ ${device_num} != "N1C1" -a -d mylog ]; then
case_path=$PWD && cd - && mkdir -p mylog # PaddleNLP/tests/mylog
cp -r ${case_path}/mylog/workerlog.* ./mylog/
fi
}

export FLAGS_selected_gpus="0,1,2,3,4,5,6,7"
export PYTHONPATH=$(dirname "$PWD"):$PYTHONPATH

source ${BENCHMARK_ROOT}/scripts/run_model.sh # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;如果不联调只想要产出训练log可以注掉本行,提交时需打开
_set_params $@
#_train # 如果只产出训练log,不解析,可取消注释
_run # 该函数在run_model.sh中,执行时会调用_train; 如果不联调只产出训练log可以注掉本行,提交时需打开
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
param="model_item=baichuan-inc-baichaun-2-13b_pretrain "
param+="run_mode=DP1_MP2_PP4_1F1B_Sharding8_Stage2 "
param+="device_num=N4C32 "
param+="global_batch_size=32 "
param+="global_batch_size=128 "
param+="nnodes=4 "
param+="model_type=baichuan2_13b "

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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ python -m pip install fast_dataindex
# download data
wget https://bj.bcebos.com/paddlenlp/models/transformers/llama/data/llama_openwebtext_100k_ids.npy
wget https://bj.bcebos.com/paddlenlp/models/transformers/llama/data/llama_openwebtext_100k_idx.npz
rm -rf data
mkdir data
mv llama_openwebtext_100k_ids.npy ./data
mv llama_openwebtext_100k_idx.npz ./data
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
param="model_item=gpt3-13b_pretrain_dy2st "
param+="run_mode=DP1_MP2_PP4_1F1B_Sharding4_Stage1 "
param+="device_num=N4C32 "
param+="global_batch_size=32 "
param+="global_batch_size=128 "
param+="nnodes=4 "
param+="model_type=gpt3_13b "

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