Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
Paddle
提交
a9cc0274
P
Paddle
项目概览
PaddlePaddle
/
Paddle
大约 1 年 前同步成功
通知
2298
Star
20931
Fork
5422
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1423
列表
看板
标记
里程碑
合并请求
543
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1,423
Issue
1,423
列表
看板
标记
里程碑
合并请求
543
合并请求
543
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
a9cc0274
编写于
9月 07, 2022
作者:
Y
Yuang Liu
提交者:
GitHub
9月 07, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[dygraph hybrid pp for interleave] Save/Load for interleaved pipeline. (#45797)
上级
960109af
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
188 addition
and
24 deletion
+188
-24
python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py
...tributed/fleet/meta_parallel/parallel_layers/pp_layers.py
+66
-23
python/paddle/fluid/tests/unittests/collective/fleet/hybrid_parallel_pp_save_load_with_virtual_stage.py
.../fleet/hybrid_parallel_pp_save_load_with_virtual_stage.py
+117
-0
python/paddle/fluid/tests/unittests/collective/fleet/hybrid_parallel_pp_transformer.py
...ttests/collective/fleet/hybrid_parallel_pp_transformer.py
+1
-1
python/paddle/fluid/tests/unittests/collective/fleet/test_parallel_dygraph_pipeline_parallel_with_virtual_stage.py
..._parallel_dygraph_pipeline_parallel_with_virtual_stage.py
+4
-0
未找到文件。
python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py
浏览文件 @
a9cc0274
...
...
@@ -657,21 +657,42 @@ class PipelineLayer(Layer):
if
self
.
_topo
.
get_coord
(
self
.
global_rank
).
data
!=
0
:
return
def
_offset_dirname
(
ckpt_dir
,
local_layer_idx
):
idx
=
local_layer_idx
+
self
.
_start_pos
def
_offset_dirname
(
ckpt_dir
,
local_layer_idx
,
local_chunk_id
=
None
):
if
self
.
_num_virtual_pipeline_stages
==
1
:
pos_offset
=
self
.
_start_pos
else
:
assert
hasattr
(
self
,
'_start_poss'
)
assert
local_chunk_id
<
len
(
self
.
_start_poss
)
pos_offset
=
self
.
_start_poss
[
local_chunk_id
]
idx
=
local_layer_idx
+
pos_offset
model_rank
=
self
.
_topo
.
get_coord
(
self
.
global_rank
).
model
rank_message
=
"-tensor_"
+
"{:0>2d}"
.
format
(
model_rank
)
virtual_pipeline_stage_message
=
""
if
self
.
_num_virtual_pipeline_stages
>
1
:
# add virtual pipeline info to the save path
assert
local_chunk_id
is
not
None
virtual_pipeline_stage_message
=
"-virtual_pp_stage_{:0>2d}"
.
format
(
local_chunk_id
)
layer_save_path
=
os
.
path
.
join
(
ckpt_dir
,
'layer_{:0>2d}'
.
format
(
idx
))
layer_save_path
=
layer_save_path
+
rank_message
+
'-model_states.pdparams'
layer_save_path
=
layer_save_path
+
virtual_pipeline_stage_message
+
rank_message
+
'-model_states.pdparams'
return
layer_save_path
def
_save_model
(
run_functions
,
local_chunk_id
=
None
):
for
idx
,
layer
in
enumerate
(
run_functions
):
model_save_path
=
_offset_dirname
(
path
,
idx
,
local_chunk_id
)
if
not
hasattr
(
layer
,
'state_dict'
):
continue
paddle
.
save
(
layer
.
state_dict
(),
model_save_path
)
os
.
makedirs
(
path
,
exist_ok
=
True
)
for
idx
,
layer
in
enumerate
(
self
.
run_function
):
model_save_path
=
_offset_dirname
(
path
,
idx
)
if
not
hasattr
(
layer
,
'state_dict'
):
continue
paddle
.
save
(
layer
.
state_dict
(),
model_save_path
)
if
self
.
_num_virtual_pipeline_stages
>
1
:
logger
.
info
(
"save model state for virtual pipeline stage..."
)
for
chunk_id
in
range
(
len
(
self
.
_model_chunks
)):
run_function
=
self
.
_model_chunks
[
chunk_id
].
get_run_function
()
_save_model
(
run_function
,
chunk_id
)
else
:
_save_model
(
self
.
run_function
)
logger
.
info
(
"save model state successfully..."
)
...
...
@@ -679,21 +700,43 @@ class PipelineLayer(Layer):
assert
os
.
path
.
exists
(
path
),
"{} not found, please check the path"
.
format
(
path
)
for
idx
,
layer
in
enumerate
(
self
.
run_function
):
if
not
hasattr
(
layer
,
'set_state_dict'
):
continue
layer_idx
=
idx
+
self
.
_start_pos
layer_save_path
=
os
.
path
.
join
(
path
,
'layer_{0:0>2d}'
.
format
(
layer_idx
))
model_files
=
glob
.
glob
(
layer_save_path
+
"*model_states.pdparams"
)
model_files
.
sort
()
mp_rank
=
self
.
_topo
.
get_coord
(
self
.
global_rank
).
model
mp_world_size
=
self
.
_topo
.
get_dim
(
'model'
)
num_files
=
len
(
model_files
)
load_param_path
=
model_files
[
mp_rank
*
num_files
//
mp_world_size
]
model_state_dict
=
paddle
.
load
(
load_param_path
)
layer
.
set_state_dict
(
model_state_dict
)
def
_load_model
(
run_functions
,
local_chunk_id
=
None
):
for
idx
,
layer
in
enumerate
(
run_functions
):
if
not
hasattr
(
layer
,
'set_state_dict'
):
continue
if
self
.
_num_virtual_pipeline_stages
==
1
:
pos_offset
=
self
.
_start_pos
else
:
assert
hasattr
(
self
,
'_start_poss'
)
assert
local_chunk_id
<
len
(
self
.
_start_poss
)
pos_offset
=
self
.
_start_poss
[
local_chunk_id
]
layer_idx
=
idx
+
pos_offset
layer_save_path
=
os
.
path
.
join
(
path
,
'layer_{0:0>2d}'
.
format
(
layer_idx
))
if
self
.
_num_virtual_pipeline_stages
>
1
:
# add virtual pipeline info to the path
assert
local_chunk_id
is
not
None
layer_save_path
=
layer_save_path
+
"-virtual_pp_stage_{:0>2d}"
.
format
(
local_chunk_id
)
model_files
=
glob
.
glob
(
layer_save_path
+
"*model_states.pdparams"
)
model_files
.
sort
()
mp_rank
=
self
.
_topo
.
get_coord
(
self
.
global_rank
).
model
mp_world_size
=
self
.
_topo
.
get_dim
(
'model'
)
num_files
=
len
(
model_files
)
load_param_path
=
model_files
[
mp_rank
*
num_files
//
mp_world_size
]
model_state_dict
=
paddle
.
load
(
load_param_path
)
layer
.
set_state_dict
(
model_state_dict
)
if
self
.
_num_virtual_pipeline_stages
>
1
:
logger
.
info
(
"load model state for virtual pipeline stage..."
)
for
chunk_id
in
range
(
len
(
self
.
_model_chunks
)):
run_function
=
self
.
_model_chunks
[
chunk_id
].
get_run_function
()
_load_model
(
run_function
,
chunk_id
)
else
:
_load_model
(
self
.
run_function
)
self
.
_synchronize_shared_weights
()
logger
.
info
(
"load model state successfully..."
)
python/paddle/fluid/tests/unittests/collective/fleet/hybrid_parallel_pp_save_load_with_virtual_stage.py
0 → 100644
浏览文件 @
a9cc0274
# Copyright (c) 2022 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.
from
__future__
import
division
from
__future__
import
print_function
import
unittest
import
paddle
import
numpy
as
np
import
random
import
os
import
shutil
import
tempfile
import
paddle.distributed
as
dist
import
paddle.distributed.fleet
as
fleet
from
hybrid_parallel_pp_transformer_with_virtual_stage
import
ModelPipe
,
set_random_seed
batch_size
=
8
length
=
8
micro_batch_size
=
2
vocab_size
=
128
class
TestDistPPSaveLoadTraning
(
unittest
.
TestCase
):
def
setUp
(
self
):
strategy
=
fleet
.
DistributedStrategy
()
self
.
model_parallel_size
=
1
self
.
data_parallel_size
=
1
self
.
pipeline_parallel_size
=
2
strategy
.
hybrid_configs
=
{
"dp_degree"
:
self
.
data_parallel_size
,
"mp_degree"
:
self
.
model_parallel_size
,
"pp_degree"
:
self
.
pipeline_parallel_size
,
}
strategy
.
pipeline_configs
=
{
"accumulate_steps"
:
batch_size
//
micro_batch_size
,
"micro_batch_size"
:
micro_batch_size
}
fleet
.
init
(
is_collective
=
True
,
strategy
=
strategy
)
def
test_pp_model
(
self
):
hcg
=
fleet
.
get_hybrid_communicate_group
()
word_size
=
hcg
.
get_model_parallel_world_size
()
dp_id
=
hcg
.
get_data_parallel_rank
()
pp_id
=
hcg
.
get_stage_id
()
rank_id
=
dist
.
get_rank
()
topology
=
hcg
.
topology
()
set_random_seed
(
1024
,
dp_id
,
rank_id
)
model
=
ModelPipe
(
topology
)
scheduler
=
paddle
.
optimizer
.
lr
.
PiecewiseDecay
(
boundaries
=
[
2
],
values
=
[
0.001
,
0.002
],
verbose
=
True
)
optimizer
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
scheduler
,
parameters
=
model
.
parameters
())
model
=
fleet
.
distributed_model
(
model
)
optimizer
=
fleet
.
distributed_optimizer
(
optimizer
)
output_dir
=
tempfile
.
mkdtemp
()
# warmup step
for
step_id
in
range
(
2
):
x_data
=
np
.
random
.
randint
(
0
,
vocab_size
,
size
=
[
batch_size
,
length
])
x
=
paddle
.
to_tensor
(
x_data
)
x
.
stop_gradient
=
True
loss
=
model
.
train_batch
([
x
,
x
],
optimizer
,
scheduler
)
model
.
_layers
.
save_state_dict
(
output_dir
)
paddle
.
save
(
optimizer
.
state_dict
(),
os
.
path
.
join
(
output_dir
,
"model_state.pdopt"
))
# construct data
test_steps
=
5
np_data
=
np
.
random
.
randint
(
0
,
vocab_size
,
size
=
[
test_steps
,
batch_size
,
length
])
origin_loss
=
[]
for
step_id
in
range
(
5
):
x_data
=
np_data
[
step_id
,
:]
x
=
paddle
.
to_tensor
(
x_data
)
x
.
stop_gradient
=
True
loss
=
model
.
train_batch
([
x
,
x
],
optimizer
,
scheduler
)
origin_loss
.
append
(
loss
.
numpy
())
# test step
model
.
_layers
.
set_state_dir
(
output_dir
)
opt_dict
=
paddle
.
load
(
os
.
path
.
join
(
output_dir
,
"model_state.pdopt"
))
optimizer
.
set_state_dict
(
opt_dict
)
for
step_id
in
range
(
5
):
x_data
=
np_data
[
step_id
,
:]
x
=
paddle
.
to_tensor
(
x_data
)
x
.
stop_gradient
=
True
loss
=
model
.
train_batch
([
x
,
x
],
optimizer
,
scheduler
)
print
(
"origin loss: "
,
origin_loss
[
step_id
],
"current loss: "
,
loss
.
numpy
())
np
.
testing
.
assert_allclose
(
loss
.
numpy
(),
origin_loss
[
step_id
])
# finally, remove the model/optimizer path
shutil
.
rmtree
(
output_dir
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/collective/fleet/hybrid_parallel_pp_transformer.py
浏览文件 @
a9cc0274
# Copyright (c) 202
1
PaddlePaddle Authors. All Rights Reserved.
# Copyright (c) 202
2
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.
...
...
python/paddle/fluid/tests/unittests/collective/fleet/test_parallel_dygraph_pipeline_parallel_with_virtual_stage.py
浏览文件 @
a9cc0274
...
...
@@ -30,6 +30,10 @@ class TestHybridPipeParallelWithVirtualStage(TestMultipleGpus):
self
.
run_mnist_2gpu
(
'hybrid_parallel_pp_transformer_with_virtual_stage.py'
)
def
test_hybrid_parallel_save_load_with_virtual_stage
(
self
):
self
.
run_mnist_2gpu
(
'hybrid_parallel_pp_save_load_with_virtual_stage.py'
)
if
__name__
==
"__main__"
:
os
.
environ
[
"FLAGS_enable_eager_mode"
]
=
"1"
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录