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体验新版 GitCode,发现更多精彩内容 >>
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2b56b1b0
编写于
6月 09, 2021
作者:
L
lilong12
提交者:
GitHub
6月 09, 2021
浏览文件
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电子邮件补丁
差异文件
fix the bug in the creation of pp groups to avoid hang (#32890)
* update, test=develop
上级
f249a5f0
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
188 addition
and
4 deletion
+188
-4
python/paddle/distributed/fleet/meta_optimizers/common.py
python/paddle/distributed/fleet/meta_optimizers/common.py
+12
-3
python/paddle/distributed/fleet/meta_optimizers/pipeline_optimizer.py
...e/distributed/fleet/meta_optimizers/pipeline_optimizer.py
+3
-0
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+5
-1
python/paddle/fluid/tests/unittests/pipeline_mnist_multi_device.py
...ddle/fluid/tests/unittests/pipeline_mnist_multi_device.py
+159
-0
python/paddle/fluid/tests/unittests/test_pipeline.py
python/paddle/fluid/tests/unittests/test_pipeline.py
+9
-0
未找到文件。
python/paddle/distributed/fleet/meta_optimizers/common.py
浏览文件 @
2b56b1b0
...
...
@@ -77,9 +77,12 @@ class CollectiveHelper(object):
wait_port
,
global_ring_id
=
None
,
sync
=
True
):
nranks
=
len
(
endpoints
)
other_endpoints
=
endpoints
[:]
other_endpoints
.
remove
(
current_endpoint
)
# if current_endpoint is None, it means just for sync,
# no group is created.
if
current_endpoint
:
nranks
=
len
(
endpoints
)
other_endpoints
=
endpoints
[:]
other_endpoints
.
remove
(
current_endpoint
)
if
rank
==
0
and
wait_port
:
wait_server_ready
(
other_endpoints
)
...
...
@@ -117,6 +120,12 @@ class CollectiveHelper(object):
attrs
=
{
OP_ROLE_KEY
:
OpRole
.
Forward
})
block
=
program
.
global_block
()
if
current_endpoint
is
None
:
assert
endpoints
is
None
assert
sync
_add_sync_by_allreduce
(
block
)
return
if
core
.
is_compiled_with_cuda
():
comm_id_var
=
block
.
create_var
(
name
=
unique_name
.
generate
(
'nccl_id'
),
...
...
python/paddle/distributed/fleet/meta_optimizers/pipeline_optimizer.py
浏览文件 @
2b56b1b0
...
...
@@ -138,6 +138,9 @@ class PipelineOptimizer(MetaOptimizerBase):
first_node
=
pair
[
0
]
+
start_index
second_node
=
pair
[
1
]
+
start_index
if
self
.
rank
!=
first_node
and
self
.
rank
!=
second_node
:
collective_helper
.
_init_communicator
(
self
.
startup_program
,
None
,
None
,
None
,
None
,
False
,
self
.
global_ring_id
,
True
)
continue
pipeline_endpoints
=
[
self
.
endpoints
[
first_node
],
self
.
endpoints
[
second_node
]
...
...
python/paddle/fluid/optimizer.py
浏览文件 @
2b56b1b0
...
...
@@ -4084,6 +4084,7 @@ class PipelineOptimizer(object):
'out_dtype'
:
out_var
.
dtype
,
self
.
_op_role_key
:
self
.
_op_role
.
Optimize
})
offset
+=
1
return
offset
def
_create_vars
(
self
,
block
,
ori_block
):
...
...
@@ -4596,12 +4597,15 @@ class PipelineOptimizer(object):
'ring_id'
:
ring_id
})
extra_index_info
[
'index'
]
+=
1
var_shape
=
list
(
var
.
shape
)
var_shape
[
0
]
=
self
.
micro_batch_size
if
var_shape
[
0
]
<
0
else
var_shape
[
0
]
block
.
_insert_op_without_sync
(
index
=
index
+
extra_index_info
[
'index'
],
type
=
'recv_v2'
,
outputs
=
{
'Out'
:
[
var
]},
attrs
=
{
'out_shape'
:
var
.
shape
,
'out_shape'
:
var
_
shape
,
'dtype'
:
var
.
dtype
,
self
.
_op_device_key
:
cur_dev
,
self
.
_op_role_key
:
op_role
,
...
...
python/paddle/fluid/tests/unittests/pipeline_mnist_multi_device.py
0 → 100644
浏览文件 @
2b56b1b0
# Copyright (c) 2018 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
print_function
import
numpy
as
np
import
argparse
import
time
import
math
import
paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.profiler
as
profiler
from
paddle.fluid
import
core
import
unittest
from
multiprocessing
import
Process
import
os
import
signal
from
functools
import
reduce
from
test_dist_base
import
TestDistRunnerBase
,
runtime_main
import
paddle.distributed.fleet
as
fleet
paddle
.
enable_static
()
DTYPE
=
"float32"
paddle
.
dataset
.
mnist
.
fetch
()
# Fix seed for test
fluid
.
default_startup_program
().
random_seed
=
1
fluid
.
default_main_program
().
random_seed
=
1
def
cnn_model
(
data
):
conv_pool_1
=
fluid
.
nets
.
simple_img_conv_pool
(
input
=
data
,
filter_size
=
5
,
num_filters
=
20
,
pool_size
=
2
,
pool_stride
=
2
,
act
=
"relu"
,
param_attr
=
fluid
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
0.01
)))
conv_pool_2
=
fluid
.
nets
.
simple_img_conv_pool
(
input
=
conv_pool_1
,
filter_size
=
5
,
num_filters
=
50
,
pool_size
=
2
,
pool_stride
=
2
,
act
=
"relu"
,
param_attr
=
fluid
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
0.01
)))
SIZE
=
10
input_shape
=
conv_pool_2
.
shape
param_shape
=
[
reduce
(
lambda
a
,
b
:
a
*
b
,
input_shape
[
1
:],
1
)]
+
[
SIZE
]
scale
=
(
2.0
/
(
param_shape
[
0
]
**
2
*
SIZE
))
**
0.5
with
fluid
.
device_guard
(
"gpu:1"
):
predict
=
fluid
.
layers
.
fc
(
input
=
conv_pool_2
,
size
=
SIZE
,
act
=
"softmax"
,
param_attr
=
fluid
.
param_attr
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
0.01
)))
# To cover @RENAMED@GRADIENT
predict2
=
fluid
.
layers
.
fc
(
input
=
conv_pool_1
,
size
=
SIZE
,
act
=
"softmax"
,
param_attr
=
fluid
.
param_attr
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
0.01
)))
predict
+=
predict2
return
predict
class
TestDistMnist2x2
(
TestDistRunnerBase
):
def
get_model
(
self
,
batch_size
=
2
,
use_dgc
=
False
,
dist_strategy
=
None
):
# Input data
with
fluid
.
device_guard
(
"gpu:0"
):
images
=
fluid
.
layers
.
data
(
name
=
'pixel'
,
shape
=
[
1
,
28
,
28
],
dtype
=
DTYPE
)
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
if
dist_strategy
:
data_loader
=
fluid
.
io
.
DataLoader
.
from_generator
(
feed_list
=
[
images
,
label
],
capacity
=
64
,
use_double_buffer
=
False
,
iterable
=
False
)
# Train program
predict
=
cnn_model
(
images
)
with
fluid
.
device_guard
(
"gpu:1"
):
cost
=
fluid
.
layers
.
cross_entropy
(
input
=
predict
,
label
=
label
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
# Evaluator
with
fluid
.
device_guard
(
"gpu:1"
):
batch_size_tensor
=
fluid
.
layers
.
create_tensor
(
dtype
=
'int64'
)
batch_acc
=
fluid
.
layers
.
accuracy
(
input
=
predict
,
label
=
label
,
total
=
batch_size_tensor
)
inference_program
=
fluid
.
default_main_program
().
clone
()
base_lr
=
self
.
lr
passes
=
[
30
,
60
,
80
,
90
]
steps_per_pass
=
10
bd
=
[
steps_per_pass
*
p
for
p
in
passes
]
lr
=
[
base_lr
*
(
0.1
**
i
)
for
i
in
range
(
len
(
bd
)
+
1
)]
lr_val
=
fluid
.
layers
.
piecewise_decay
(
boundaries
=
bd
,
values
=
lr
)
opt
=
fluid
.
optimizer
.
Momentum
(
learning_rate
=
lr_val
,
momentum
=
0.9
,
grad_clip
=
fluid
.
clip
.
GradientClipByGlobalNorm
(
clip_norm
=
1.0
))
acc_steps
=
2
# accumulated steps for pipeline
if
dist_strategy
:
# Reader
train_reader
=
paddle
.
batch
(
paddle
.
dataset
.
mnist
.
test
(),
batch_size
=
batch_size
)
test_reader
=
paddle
.
batch
(
paddle
.
dataset
.
mnist
.
test
(),
batch_size
=
batch_size
)
fleet
.
init
(
is_collective
=
True
)
strategy
=
fleet
.
DistributedStrategy
()
strategy
.
pipeline
=
True
strategy
.
amp
=
True
strategy
.
pipeline_configs
=
{
'micro_batch_size'
:
batch_size
,
'schedule_mode'
:
'F-then-B'
,
'accumulate_steps'
:
acc_steps
}
dist_opt
=
fleet
.
distributed_optimizer
(
optimizer
=
opt
,
strategy
=
strategy
)
dist_opt
.
minimize
(
avg_cost
)
else
:
opt
.
minimize
(
avg_cost
)
# Reader
train_reader
=
paddle
.
batch
(
paddle
.
dataset
.
mnist
.
test
(),
batch_size
=
batch_size
*
acc_steps
)
test_reader
=
paddle
.
batch
(
paddle
.
dataset
.
mnist
.
test
(),
batch_size
=
batch_size
*
acc_steps
)
if
dist_strategy
:
return
inference_program
,
avg_cost
,
train_reader
,
test_reader
,
batch_acc
,
predict
,
data_loader
else
:
return
inference_program
,
avg_cost
,
train_reader
,
test_reader
,
batch_acc
,
predict
if
__name__
==
"__main__"
:
runtime_main
(
TestDistMnist2x2
)
python/paddle/fluid/tests/unittests/test_pipeline.py
浏览文件 @
2b56b1b0
...
...
@@ -44,6 +44,15 @@ class TestPipeline(TestDistBase):
check_error_log
=
True
,
log_name
=
flag_name
)
def
test_dist_train_multi_device
(
self
):
import
paddle.fluid
as
fluid
if
fluid
.
core
.
is_compiled_with_cuda
():
self
.
check_with_place
(
"pipeline_mnist_multi_device.py"
,
check_error_log
=
True
,
delta
=
1e0
,
log_name
=
flag_name
)
def
test_dist_train_one_device
(
self
):
import
paddle.fluid
as
fluid
if
fluid
.
core
.
is_compiled_with_cuda
():
...
...
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