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15de2dff
编写于
2月 26, 2019
作者:
D
dzhwinter
提交者:
GitHub
2月 26, 2019
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Merge pull request #15926 from dzhwinter/test/add_ir_mem_opt_tests
add ir memory optimize test base
上级
e00c7a2e
48d9fd08
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4
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Showing
4 changed file
with
207 addition
and
3 deletion
+207
-3
python/paddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
...ddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
+150
-0
python/paddle/fluid/tests/unittests/test_eager_deletion_dynamic_rnn_base.py
...d/tests/unittests/test_eager_deletion_dynamic_rnn_base.py
+2
-0
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_nlp.py
...ddle/fluid/tests/unittests/test_ir_memory_optimize_nlp.py
+55
-0
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py
...id/tests/unittests/test_ir_memory_optimize_transformer.py
+0
-3
未找到文件。
python/paddle/fluid/tests/unittests/ir_memory_optimize_net_base.py
0 → 100644
浏览文件 @
15de2dff
# Copyright (c) 2019 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.
import
os
import
six
import
unittest
import
time
import
math
import
multiprocessing
import
numpy
as
np
import
paddle
import
paddle.fluid.core
as
core
import
paddle.fluid
as
fluid
from
paddle.fluid
import
compiler
# open eager delete mode
os
.
environ
[
'FLAGS_eager_delete_tensor_gb'
]
=
'0.0'
os
.
environ
[
'FLAGS_fast_eager_deletion_mode'
]
=
'true'
os
.
environ
[
'CPU_NUM'
]
=
'2'
class
BuildIrMemOptBase
(
unittest
.
TestCase
):
def
check_network_convergence
(
self
,
network
,
use_cuda
=
True
,
memory_opt
=
True
,
use_ir_memory_optimize
=
True
,
enable_inplace
=
True
,
iter
=
5
):
if
use_cuda
and
not
core
.
is_compiled_with_cuda
():
print
(
'Skip use_cuda=True because Paddle is not compiled with cuda'
)
return
if
os
.
name
==
'nt'
:
print
(
'Skip use_parallel_executor=True because Paddle comes without parallel support on windows'
)
return
fluid
.
default_startup_program
().
random_seed
=
100
fluid
.
default_main_program
().
random_seed
=
100
batch_size
=
32
batch_size
*=
fluid
.
core
.
get_cuda_device_count
()
if
use_cuda
else
int
(
os
.
environ
.
get
(
'CPU_NUM'
,
multiprocessing
.
cpu_count
()))
# build network
word_dict
=
paddle
.
dataset
.
imdb
.
word_dict
()
train_reader
=
paddle
.
batch
(
paddle
.
dataset
.
imdb
.
train
(
word_dict
),
batch_size
=
batch_size
)
data
=
fluid
.
layers
.
data
(
name
=
"words"
,
shape
=
[
1
],
dtype
=
"int64"
,
lod_level
=
1
)
label
=
fluid
.
layers
.
data
(
name
=
"label"
,
shape
=
[
1
],
dtype
=
"int64"
)
cost
=
network
(
data
,
label
,
len
(
word_dict
))
optimizer
=
fluid
.
optimizer
.
Adam
(
learning_rate
=
0.001
)
optimizer
.
minimize
(
cost
)
if
memory_opt
:
fluid
.
memory_optimize
(
fluid
.
default_main_program
())
# execution
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
feed_list
=
[
data
,
label
],
place
=
place
)
reader
=
feeder
.
decorate_reader
(
train_reader
,
multi_devices
=
True
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
train_cp
=
compiler
.
CompiledProgram
(
fluid
.
default_main_program
())
train_cp
=
train_cp
.
with_data_parallel
(
loss_name
=
cost
.
name
)
fetch_list
=
[
cost
.
name
]
begin
=
time
.
time
()
first_loss
,
last_loss
=
None
,
None
step_id
=
0
custom_iter
=
getattr
(
self
,
"iter"
,
None
)
if
not
custom_iter
==
None
:
iter
=
custom_iter
for
data
in
reader
():
ret
=
exe
.
run
(
train_cp
,
feed
=
data
,
fetch_list
=
fetch_list
)
print
(
ret
)
step_id
+=
1
if
step_id
==
1
:
first_loss
=
ret
[
0
]
if
step_id
==
iter
:
last_loss
=
ret
[
0
]
break
end
=
time
.
time
()
print
(
"%.4f Instance per second"
%
(
(
batch_size
*
iter
)
/
(
end
-
begin
)))
print
(
first_loss
,
last_loss
)
avg_last_loss_val
=
np
.
array
(
last_loss
).
mean
()
avg_first_loss_val
=
np
.
array
(
first_loss
).
mean
()
if
math
.
isnan
(
float
(
avg_last_loss_val
))
or
math
.
isnan
(
float
(
avg_first_loss_val
)):
sys
.
exit
(
"got NaN loss, training failed."
)
return
first_loss
,
last_loss
class
TestIrMemOptBase
(
BuildIrMemOptBase
):
def
setUp
(
self
):
self
.
network
=
None
def
test_network
(
self
):
if
self
.
network
is
None
or
not
core
.
is_compiled_with_cuda
():
return
baseline_first_loss
,
baseline_last_loss
=
None
,
None
for
use_cuda
in
[
True
]:
for
use_python_mem_opt
in
[
True
,
False
]:
print
(
'network: {}, use_cuda: {}, use_python_mem_opt: {}, use_ir_mem_opt : {}'
.
format
(
self
.
network
.
__name__
,
use_cuda
,
use_python_mem_opt
,
not
use_python_mem_opt
))
with
fluid
.
program_guard
(
fluid
.
Program
(),
fluid
.
Program
()):
with
fluid
.
scope_guard
(
core
.
Scope
()):
if
use_cuda
is
True
and
use_python_mem_opt
is
True
:
baseline_first_loss
,
baseline_last_loss
=
self
.
check_network_convergence
(
self
.
network
,
use_cuda
=
use_cuda
,
memory_opt
=
use_python_mem_opt
)
else
:
cur_first_loss
,
cur_last_loss
=
self
.
check_network_convergence
(
self
.
network
,
use_cuda
=
use_cuda
,
memory_opt
=
use_python_mem_opt
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_last_loss
),
np
.
mean
(
cur_last_loss
),
delta
=
1e-2
)
self
.
assertAlmostEquals
(
np
.
mean
(
baseline_first_loss
),
np
.
mean
(
cur_first_loss
),
delta
=
1e-2
)
python/paddle/fluid/tests/unittests/test_eager_deletion_dynamic_rnn_base.py
浏览文件 @
15de2dff
...
...
@@ -56,6 +56,8 @@ def train(network, use_cuda, use_parallel_executor, batch_size=32, pass_num=2):
train_reader
,
multi_devices
=
use_parallel_executor
)
exe
=
fluid
.
Executor
(
place
)
fluid
.
default_startup_program
().
random_seed
=
1
fluid
.
default_main_program
().
random_seed
=
1
exe
.
run
(
fluid
.
default_startup_program
())
train_cp
=
compiler
.
CompiledProgram
(
fluid
.
default_main_program
())
...
...
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_nlp.py
0 → 100644
浏览文件 @
15de2dff
# Copyright (c) 2019 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.
# nlp model stack of op operate on lod. It's a classical test case in optimize pass.
from
__future__
import
print_function
import
paddle.fluid
as
fluid
import
unittest
from
ir_memory_optimize_net_base
import
TestIrMemOptBase
def
lstm_net
(
data
,
label
,
dict_dim
,
emb_dim
=
128
,
hid_dim
=
128
,
hid_dim2
=
96
,
class_dim
=
2
,
emb_lr
=
30.0
):
emb
=
fluid
.
layers
.
embedding
(
input
=
data
,
size
=
[
dict_dim
,
emb_dim
],
param_attr
=
fluid
.
ParamAttr
(
learning_rate
=
emb_lr
))
fc0
=
fluid
.
layers
.
fc
(
input
=
emb
,
size
=
hid_dim
*
4
)
lstm_h
,
c
=
fluid
.
layers
.
dynamic_lstm
(
input
=
fc0
,
size
=
hid_dim
*
4
,
is_reverse
=
False
)
lstm_max
=
fluid
.
layers
.
sequence_pool
(
input
=
lstm_h
,
pool_type
=
'max'
)
lstm_max_tanh
=
fluid
.
layers
.
tanh
(
lstm_max
)
fc1
=
fluid
.
layers
.
fc
(
input
=
lstm_max_tanh
,
size
=
hid_dim2
,
act
=
'tanh'
)
prediction
=
fluid
.
layers
.
fc
(
input
=
fc1
,
size
=
class_dim
,
act
=
'softmax'
)
cost
=
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
avg_cost
=
fluid
.
layers
.
mean
(
x
=
cost
)
return
avg_cost
class
TestIrMemOptRNN
(
TestIrMemOptBase
):
def
setUp
(
self
):
self
.
network
=
lstm_net
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py
浏览文件 @
15de2dff
...
...
@@ -28,9 +28,6 @@ os.environ[
from
test_parallel_executor_transformer
import
transformer
,
ModelHyperParams
,
transformer_model
,
transformer
,
prepare_batch_input
from
parallel_executor_test_base
import
TestParallelExecutorBase
# disable temporarily because of timeout.
sys
.
exit
(
0
)
# NOTE(dzhwinter): test diferent strategy colisions.
# open the eager delete tensor strategy by default.
...
...
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