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体验新版 GitCode,发现更多精彩内容 >>
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6e2424e4
编写于
4月 08, 2018
作者:
A
Abhinav Arora
浏览文件
操作
浏览文件
下载
差异文件
Merge remote-tracking branch 'origin/develop' into cpplint_ops_a
上级
11487de9
31464f34
变更
26
隐藏空白更改
内联
并排
Showing
26 changed file
with
571 addition
and
262 deletion
+571
-262
benchmark/fluid/machine_translation.py
benchmark/fluid/machine_translation.py
+48
-18
benchmark/fluid/mnist.py
benchmark/fluid/mnist.py
+43
-21
benchmark/fluid/resnet.py
benchmark/fluid/resnet.py
+14
-24
benchmark/fluid/run.sh
benchmark/fluid/run.sh
+63
-7
benchmark/fluid/stacked_dynamic_lstm.py
benchmark/fluid/stacked_dynamic_lstm.py
+58
-31
benchmark/fluid/vgg.py
benchmark/fluid/vgg.py
+10
-6
paddle/.gitignore
paddle/.gitignore
+1
-0
paddle/fluid/framework/executor.cc
paddle/fluid/framework/executor.cc
+42
-30
paddle/fluid/framework/executor.h
paddle/fluid/framework/executor.h
+4
-2
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+56
-47
paddle/fluid/framework/parallel_executor.h
paddle/fluid/framework/parallel_executor.h
+5
-2
paddle/fluid/framework/scope.h
paddle/fluid/framework/scope.h
+1
-1
paddle/fluid/inference/tests/book/test_inference_image_classification.cc
...ference/tests/book/test_inference_image_classification.cc
+4
-4
paddle/fluid/inference/tests/test_helper.h
paddle/fluid/inference/tests/test_helper.h
+12
-3
paddle/fluid/operators/go_op.cc
paddle/fluid/operators/go_op.cc
+2
-2
paddle/fluid/operators/lod_reset_op.h
paddle/fluid/operators/lod_reset_op.h
+3
-1
paddle/fluid/platform/float16_test.cc
paddle/fluid/platform/float16_test.cc
+22
-18
paddle/fluid/platform/float16_test.cu
paddle/fluid/platform/float16_test.cu
+21
-21
paddle/fluid/pybind/.gitignore
paddle/fluid/pybind/.gitignore
+1
-0
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+12
-5
python/.gitignore
python/.gitignore
+1
-0
python/paddle/.gitignore
python/paddle/.gitignore
+1
-0
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+11
-4
python/paddle/fluid/parallel_executor.py
python/paddle/fluid/parallel_executor.py
+57
-6
python/paddle/fluid/tests/unittests/test_activation_op.py
python/paddle/fluid/tests/unittests/test_activation_op.py
+36
-8
python/paddle/fluid/tests/unittests/test_parallel_executor.py
...on/paddle/fluid/tests/unittests/test_parallel_executor.py
+43
-1
未找到文件。
benchmark/fluid/machine_translation.py
浏览文件 @
6e2424e4
...
@@ -48,6 +48,13 @@ parser.add_argument(
...
@@ -48,6 +48,13 @@ parser.add_argument(
type
=
int
,
type
=
int
,
default
=
16
,
default
=
16
,
help
=
"The sequence number of a mini-batch data. (default: %(default)d)"
)
help
=
"The sequence number of a mini-batch data. (default: %(default)d)"
)
parser
.
add_argument
(
'--skip_batch_num'
,
type
=
int
,
default
=
5
,
help
=
'The first num of minibatch num to skip, for better performance test'
)
parser
.
add_argument
(
'--iterations'
,
type
=
int
,
default
=
80
,
help
=
'The number of minibatches.'
)
parser
.
add_argument
(
parser
.
add_argument
(
"--dict_size"
,
"--dict_size"
,
type
=
int
,
type
=
int
,
...
@@ -72,16 +79,21 @@ parser.add_argument(
...
@@ -72,16 +79,21 @@ parser.add_argument(
default
=
3
,
default
=
3
,
help
=
"The width for beam searching. (default: %(default)d)"
)
help
=
"The width for beam searching. (default: %(default)d)"
)
parser
.
add_argument
(
parser
.
add_argument
(
"--use_gpu"
,
'--device'
,
type
=
distutils
.
util
.
strtobool
,
type
=
str
,
default
=
True
,
default
=
'GPU'
,
help
=
"Whether to use gpu. (default: %(default)d)"
)
choices
=
[
'CPU'
,
'GPU'
],
help
=
"The device type."
)
parser
.
add_argument
(
parser
.
add_argument
(
"--max_length"
,
"--max_length"
,
type
=
int
,
type
=
int
,
default
=
250
,
default
=
250
,
help
=
"The maximum length of sequence when doing generation. "
help
=
"The maximum length of sequence when doing generation. "
"(default: %(default)d)"
)
"(default: %(default)d)"
)
parser
.
add_argument
(
'--with_test'
,
action
=
'store_true'
,
help
=
'If set, test the testset during training.'
)
def
lstm_step
(
x_t
,
hidden_t_prev
,
cell_t_prev
,
size
):
def
lstm_step
(
x_t
,
hidden_t_prev
,
cell_t_prev
,
size
):
...
@@ -281,7 +293,7 @@ def train():
...
@@ -281,7 +293,7 @@ def train():
paddle
.
dataset
.
wmt14
.
test
(
args
.
dict_size
),
buf_size
=
1000
),
paddle
.
dataset
.
wmt14
.
test
(
args
.
dict_size
),
buf_size
=
1000
),
batch_size
=
args
.
batch_size
)
batch_size
=
args
.
batch_size
)
place
=
core
.
C
UDAPlace
(
0
)
if
args
.
use_gpu
else
core
.
CPUPlace
(
)
place
=
core
.
C
PUPlace
()
if
args
.
device
==
'CPU'
else
core
.
CUDAPlace
(
0
)
exe
=
Executor
(
place
)
exe
=
Executor
(
place
)
exe
.
run
(
framework
.
default_startup_program
())
exe
.
run
(
framework
.
default_startup_program
())
...
@@ -307,14 +319,20 @@ def train():
...
@@ -307,14 +319,20 @@ def train():
return
total_loss
/
count
return
total_loss
/
count
iters
,
num_samples
,
start_time
=
0
,
0
,
time
.
time
()
for
pass_id
in
xrange
(
args
.
pass_num
):
for
pass_id
in
xrange
(
args
.
pass_num
):
pass_start_time
=
time
.
time
()
train_accs
=
[]
words_seen
=
0
train_losses
=
[]
for
batch_id
,
data
in
enumerate
(
train_batch_generator
()):
for
batch_id
,
data
in
enumerate
(
train_batch_generator
()):
if
iters
==
args
.
skip_batch_num
:
start_time
=
time
.
time
()
num_samples
=
0
if
iters
==
args
.
iterations
:
break
src_seq
,
word_num
=
to_lodtensor
(
map
(
lambda
x
:
x
[
0
],
data
),
place
)
src_seq
,
word_num
=
to_lodtensor
(
map
(
lambda
x
:
x
[
0
],
data
),
place
)
words_seen
+=
word_num
num_samples
+=
word_num
trg_seq
,
word_num
=
to_lodtensor
(
map
(
lambda
x
:
x
[
1
],
data
),
place
)
trg_seq
,
word_num
=
to_lodtensor
(
map
(
lambda
x
:
x
[
1
],
data
),
place
)
words_seen
+=
word_num
num_samples
+=
word_num
lbl_seq
,
_
=
to_lodtensor
(
map
(
lambda
x
:
x
[
2
],
data
),
place
)
lbl_seq
,
_
=
to_lodtensor
(
map
(
lambda
x
:
x
[
2
],
data
),
place
)
fetch_outs
=
exe
.
run
(
framework
.
default_main_program
(),
fetch_outs
=
exe
.
run
(
framework
.
default_main_program
(),
...
@@ -325,24 +343,36 @@ def train():
...
@@ -325,24 +343,36 @@ def train():
},
},
fetch_list
=
[
avg_cost
])
fetch_list
=
[
avg_cost
])
avg_cost_val
=
np
.
array
(
fetch_outs
[
0
])
iters
+=
1
print
(
'pass_id=%d, batch_id=%d, train_loss: %f'
%
loss
=
np
.
array
(
fetch_outs
[
0
])
(
pass_id
,
batch_id
,
avg_cost_val
))
print
(
"Pass = %d, Iter = %d, Loss = %f"
%
(
pass_id
,
iters
,
loss
)
)
# The accuracy is the accumulation of batches, but not the current batch.
pass_end_time
=
time
.
time
()
train_elapsed
=
time
.
time
()
-
start_time
test_loss
=
do_validation
()
examples_per_sec
=
num_samples
/
train_elapsed
time_consumed
=
pass_end_time
-
pass_start_time
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
words_per_sec
=
words_seen
/
time_consumed
(
num_samples
,
train_elapsed
,
examples_per_sec
))
print
(
"pass_id=%d, test_loss: %f, words/s: %f, sec/pass: %f"
%
# evaluation
(
pass_id
,
test_loss
,
words_per_sec
,
time_consumed
))
if
args
.
with_test
:
test_loss
=
do_validation
()
exit
(
0
)
def
infer
():
def
infer
():
pass
pass
def
print_arguments
(
args
):
print
(
'----------- seq2seq Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
args
=
parser
.
parse_args
()
args
=
parser
.
parse_args
()
print_arguments
(
args
)
if
args
.
infer_only
:
if
args
.
infer_only
:
infer
()
infer
()
else
:
else
:
...
...
benchmark/fluid/mnist.py
浏览文件 @
6e2424e4
...
@@ -35,6 +35,12 @@ def parse_args():
...
@@ -35,6 +35,12 @@ def parse_args():
parser
=
argparse
.
ArgumentParser
(
"mnist model benchmark."
)
parser
=
argparse
.
ArgumentParser
(
"mnist model benchmark."
)
parser
.
add_argument
(
parser
.
add_argument
(
'--batch_size'
,
type
=
int
,
default
=
128
,
help
=
'The minibatch size.'
)
'--batch_size'
,
type
=
int
,
default
=
128
,
help
=
'The minibatch size.'
)
parser
.
add_argument
(
'--skip_batch_num'
,
type
=
int
,
default
=
5
,
help
=
'The first num of minibatch num to skip, for better performance test'
)
parser
.
add_argument
(
parser
.
add_argument
(
'--iterations'
,
type
=
int
,
default
=
35
,
help
=
'The number of minibatches.'
)
'--iterations'
,
type
=
int
,
default
=
35
,
help
=
'The number of minibatches.'
)
parser
.
add_argument
(
parser
.
add_argument
(
...
@@ -53,19 +59,14 @@ def parse_args():
...
@@ -53,19 +59,14 @@ def parse_args():
'--use_nvprof'
,
'--use_nvprof'
,
action
=
'store_true'
,
action
=
'store_true'
,
help
=
'If set, use nvprof for CUDA.'
)
help
=
'If set, use nvprof for CUDA.'
)
parser
.
add_argument
(
'--with_test'
,
action
=
'store_true'
,
help
=
'If set, test the testset during training.'
)
args
=
parser
.
parse_args
()
args
=
parser
.
parse_args
()
return
args
return
args
def
print_arguments
(
args
):
vars
(
args
)[
'use_nvprof'
]
=
(
vars
(
args
)[
'use_nvprof'
]
and
vars
(
args
)[
'device'
]
==
'GPU'
)
print
(
'----------- Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
def
cnn_model
(
data
):
def
cnn_model
(
data
):
conv_pool_1
=
fluid
.
nets
.
simple_img_conv_pool
(
conv_pool_1
=
fluid
.
nets
.
simple_img_conv_pool
(
input
=
data
,
input
=
data
,
...
@@ -161,16 +162,22 @@ def run_benchmark(model, args):
...
@@ -161,16 +162,22 @@ def run_benchmark(model, args):
paddle
.
dataset
.
mnist
.
train
(),
batch_size
=
args
.
batch_size
)
paddle
.
dataset
.
mnist
.
train
(),
batch_size
=
args
.
batch_size
)
accuracy
=
fluid
.
average
.
WeightedAverage
()
accuracy
=
fluid
.
average
.
WeightedAverage
()
iters
,
num_samples
,
start_time
=
0
,
0
,
time
.
time
()
for
pass_id
in
range
(
args
.
pass_num
):
for
pass_id
in
range
(
args
.
pass_num
):
accuracy
.
reset
()
accuracy
.
reset
()
pass_start
=
time
.
time
()
train_accs
=
[]
train_losses
=
[]
for
batch_id
,
data
in
enumerate
(
train_reader
()):
for
batch_id
,
data
in
enumerate
(
train_reader
()):
if
iters
==
args
.
skip_batch_num
:
start_time
=
time
.
time
()
num_samples
=
0
if
iters
==
args
.
iterations
:
break
img_data
=
np
.
array
(
img_data
=
np
.
array
(
map
(
lambda
x
:
x
[
0
].
reshape
([
1
,
28
,
28
]),
data
)).
astype
(
DTYPE
)
map
(
lambda
x
:
x
[
0
].
reshape
([
1
,
28
,
28
]),
data
)).
astype
(
DTYPE
)
y_data
=
np
.
array
(
map
(
lambda
x
:
x
[
1
],
data
)).
astype
(
"int64"
)
y_data
=
np
.
array
(
map
(
lambda
x
:
x
[
1
],
data
)).
astype
(
"int64"
)
y_data
=
y_data
.
reshape
([
len
(
y_data
),
1
])
y_data
=
y_data
.
reshape
([
len
(
y_data
),
1
])
start
=
time
.
time
()
outs
=
exe
.
run
(
outs
=
exe
.
run
(
fluid
.
default_main_program
(),
fluid
.
default_main_program
(),
feed
=
{
"pixel"
:
img_data
,
feed
=
{
"pixel"
:
img_data
,
...
@@ -178,21 +185,36 @@ def run_benchmark(model, args):
...
@@ -178,21 +185,36 @@ def run_benchmark(model, args):
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
]
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
]
)
# The accuracy is the accumulation of batches, but not the current batch.
)
# The accuracy is the accumulation of batches, but not the current batch.
accuracy
.
add
(
value
=
outs
[
1
],
weight
=
outs
[
2
])
accuracy
.
add
(
value
=
outs
[
1
],
weight
=
outs
[
2
])
end
=
time
.
time
()
iters
+=
1
num_samples
+=
len
(
y_data
)
loss
=
np
.
array
(
outs
[
0
])
loss
=
np
.
array
(
outs
[
0
])
acc
=
np
.
array
(
outs
[
1
])
acc
=
np
.
array
(
outs
[
1
])
print
(
"pass=%d, batch=%d, loss=%f, error=%f, elapse=%f"
%
train_losses
.
append
(
loss
)
(
pass_id
,
batch_id
,
loss
,
1
-
acc
,
(
end
-
start
)
/
1000
))
train_accs
.
append
(
acc
)
print
(
"Pass: %d, Iter: %d, Loss: %f, Accuracy: %f"
%
(
pass_id
,
iters
,
loss
,
acc
))
print
(
"Pass: %d, Loss: %f, Train Accuray: %f
\n
"
%
(
pass_id
,
np
.
mean
(
train_losses
),
np
.
mean
(
train_accs
)))
train_elapsed
=
time
.
time
()
-
start_time
examples_per_sec
=
num_samples
/
train_elapsed
pass_end
=
time
.
time
()
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
(
num_samples
,
train_elapsed
,
examples_per_sec
))
# evaluation
if
args
.
with_test
:
test_avg_acc
=
eval_test
(
exe
,
batch_acc
,
batch_size_tensor
,
inference_program
)
exit
(
0
)
train_avg_acc
=
accuracy
.
eval
()
test_avg_acc
=
eval_test
(
exe
,
batch_acc
,
batch_size_tensor
,
inference_program
)
print
(
"pass=%d, train_avg_acc=%f, test_avg_acc=%f, elapse=%f"
%
def
print_arguments
(
args
):
(
pass_id
,
train_avg_acc
,
test_avg_acc
,
vars
(
args
)[
'use_nvprof'
]
=
(
vars
(
args
)[
'use_nvprof'
]
and
(
pass_end
-
pass_start
)
/
1000
))
vars
(
args
)[
'device'
]
==
'GPU'
)
print
(
'----------- mnist Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
...
...
benchmark/fluid/resnet.py
浏览文件 @
6e2424e4
...
@@ -87,15 +87,6 @@ def parse_args():
...
@@ -87,15 +87,6 @@ def parse_args():
return
args
return
args
def
print_arguments
(
args
):
vars
(
args
)[
'use_nvprof'
]
=
(
vars
(
args
)[
'use_nvprof'
]
and
vars
(
args
)[
'device'
]
==
'GPU'
)
print
(
'----------- Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
def
conv_bn_layer
(
input
,
ch_out
,
filter_size
,
stride
,
padding
,
act
=
'relu'
):
def
conv_bn_layer
(
input
,
ch_out
,
filter_size
,
stride
,
padding
,
act
=
'relu'
):
conv1
=
fluid
.
layers
.
conv2d
(
conv1
=
fluid
.
layers
.
conv2d
(
input
=
input
,
input
=
input
,
...
@@ -279,32 +270,31 @@ def run_benchmark(model, args):
...
@@ -279,32 +270,31 @@ def run_benchmark(model, args):
'label'
:
label
},
'label'
:
label
},
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
iters
+=
1
iters
+=
1
num_samples
+=
l
abel
[
0
]
num_samples
+=
l
en
(
label
)
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
train_losses
.
append
(
loss
)
train_losses
.
append
(
loss
)
train_accs
.
append
(
acc
)
train_accs
.
append
(
acc
)
print
(
"Pass: %d, Iter: %d, Loss: %f, Accuracy: %f"
%
print
(
"Pass: %d, Iter: %d, Loss: %f, Accuracy: %f"
%
(
pass_id
,
iters
,
loss
,
acc
))
(
pass_id
,
iters
,
loss
,
acc
))
pass_train_acc
=
accuracy
.
eval
()
# evaluation
if
args
.
with_test
:
pass_test_acc
=
test
(
exe
)
train_elapsed
=
time
.
time
()
-
start_time
print
(
"Pass: %d, Loss: %f, Train Accuray: %f
\n
"
%
print
(
"Pass: %d, Loss: %f, Train Accuray: %f
\n
"
%
(
pass_id
,
np
.
mean
(
train_losses
),
np
.
mean
(
train_accs
)))
(
pass_id
,
np
.
mean
(
train_losses
),
np
.
mean
(
train_accs
)))
train_elapsed
=
time
.
time
()
-
start_time
examples_per_sec
=
num_samples
/
train_elapsed
examples_per_sec
=
num_samples
/
train_elapsed
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
(
num_samples
,
train_elapsed
,
examples_per_sec
))
(
num_samples
,
train_elapsed
,
examples_per_sec
))
# evaluation
if
args
.
with_test
:
pass_test_acc
=
test
(
exe
)
exit
(
0
)
if
args
.
use_cprof
:
pr
.
disable
()
def
print_arguments
(
args
):
s
=
StringIO
.
StringIO
()
vars
(
args
)[
'use_nvprof'
]
=
(
vars
(
args
)[
'use_nvprof'
]
and
sortby
=
'cumulative'
vars
(
args
)[
'device'
]
==
'GPU'
)
ps
=
pstats
.
Stats
(
pr
,
stream
=
s
).
sort_stats
(
sortby
)
print
(
'----------- resnet Configuration Arguments -----------'
)
ps
.
print_stats
()
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
s
.
getvalue
())
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
...
...
benchmark/fluid/run.sh
浏览文件 @
6e2424e4
#!/bin/bash
#!/bin/bash
# This script benchmarking the PaddlePaddle Fluid on
# This script benchmarking the PaddlePaddle Fluid on
# single thread single GPU.
# single thread single GPU.
export
CUDNN_PATH
=
/paddle/cudnn_v5/cuda/lib
#export FLAGS_fraction_of_gpu_memory_to_use=0.0
export
CUDNN_PATH
=
/paddle/cudnn_v5
# disable openmp and mkl parallel
# disable openmp and mkl parallel
#https://github.com/PaddlePaddle/Paddle/issues/7199
#https://github.com/PaddlePaddle/Paddle/issues/7199
...
@@ -25,25 +27,79 @@ export CUDA_VISIBLE_DEVICES=0
...
@@ -25,25 +27,79 @@ export CUDA_VISIBLE_DEVICES=0
export
LD_LIBRARY_PATH
=
/usr/local/lib:
$LD_LIBRARY_PATH
export
LD_LIBRARY_PATH
=
/usr/local/lib:
$LD_LIBRARY_PATH
export
LD_LIBRARY_PATH
=
$CUDNN_PATH
:
$LD_LIBRARY_PATH
export
LD_LIBRARY_PATH
=
$CUDNN_PATH
:
$LD_LIBRARY_PATH
# only query the gpu used
nohup stdbuf
-oL
nvidia-smi
\
--id
=
${
CUDA_VISIBLE_DEVICES
}
\
--query-gpu
=
timestamp
\
--query-compute-apps
=
pid,process_name,used_memory
\
--format
=
csv
\
--filename
=
mem.log
\
-l
1 &
# mnist
# mnist gpu mnist 128
FLAGS_benchmark
=
true stdbuf
-oL
python fluid/mnist.py
\
--device
=
GPU
\
--batch_size
=
128
\
--skip_batch_num
=
5
\
--iterations
=
500
\
2>&1 |
tee
-a
mnist_gpu_128.log
# vgg16
# vgg16
#
cifar10
gpu cifar10 128
# gpu cifar10 128
FLAGS_benchmark
=
true
python fluid/vgg
.py
\
FLAGS_benchmark
=
true
stdbuf
-oL
python fluid/vgg16
.py
\
--device
=
GPU
\
--device
=
GPU
\
--batch_size
=
128
\
--batch_size
=
128
\
--skip_batch_num
=
5
\
--skip_batch_num
=
5
\
--iterations
=
30
\
--iterations
=
30
\
2>&1
>
vgg16_gpu_128.log
2>&1 |
tee
-a
vgg16_gpu_128.log
# flowers gpu 128
FLAGS_benchmark
=
true stdbuf
-oL
python fluid/vgg16.py
\
--device
=
GPU
\
--batch_size
=
32
\
--data_set
=
flowers
\
--skip_batch_num
=
5
\
--iterations
=
30
\
2>&1 |
tee
-a
vgg16_gpu_flowers_32.log
# resnet50
# resnet50
# resnet50 gpu cifar10 128
# resnet50 gpu cifar10 128
FLAGS_benchmark
=
true
python fluid/resnet
.py
\
FLAGS_benchmark
=
true
stdbuf
-oL
python fluid/resnet50
.py
\
--device
=
GPU
\
--device
=
GPU
\
--batch_size
=
128
\
--batch_size
=
128
\
--data_set
=
cifar10
\
--data_set
=
cifar10
\
--model
=
resnet_cifar10
\
--model
=
resnet_cifar10
\
--skip_batch_num
=
5
\
--skip_batch_num
=
5
\
--iterations
=
30
\
--iterations
=
30
\
2>&1
>
resnet50_gpu_128.log
2>&1 |
tee
-a
resnet50_gpu_128.log
# resnet50 gpu flowers 64
FLAGS_benchmark
=
true stdbuf
-oL
python fluid/resnet50.py
\
--device
=
GPU
\
--batch_size
=
64
\
--data_set
=
flowers
\
--model
=
resnet_imagenet
\
--skip_batch_num
=
5
\
--iterations
=
30
\
2>&1 |
tee
-a
resnet50_gpu_flowers_64.log
# lstm
# lstm
# lstm gpu imdb 32 # tensorflow only support batch=32
FLAGS_benchmark
=
true stdbuf
-oL
python fluid/stacked_dynamic_lstm.py
\
--device
=
GPU
\
--batch_size
=
32
\
--skip_batch_num
=
5
\
--iterations
=
30
\
--hidden_dim
=
512
\
--emb_dim
=
512
\
--crop_size
=
1500
\
2>&1 |
tee
-a
lstm_gpu_32.log
# seq2seq
# seq2seq gpu wmb 128
FLAGS_benchmark
=
true stdbuf
-oL
python fluid/machine_translation.py
\
--device
=
GPU
\
--batch_size
=
128
\
--skip_batch_num
=
5
\
--iterations
=
30
\
2>&1 |
tee
-a
lstm_gpu_128.log
benchmark/fluid/stacked_dynamic_lstm.py
浏览文件 @
6e2424e4
...
@@ -37,6 +37,14 @@ def parse_args():
...
@@ -37,6 +37,14 @@ def parse_args():
type
=
int
,
type
=
int
,
default
=
32
,
default
=
32
,
help
=
'The sequence number of a batch data. (default: %(default)d)'
)
help
=
'The sequence number of a batch data. (default: %(default)d)'
)
parser
.
add_argument
(
'--skip_batch_num'
,
type
=
int
,
default
=
5
,
help
=
'The first num of minibatch num to skip, for better performance test'
)
parser
.
add_argument
(
'--iterations'
,
type
=
int
,
default
=
80
,
help
=
'The number of minibatches.'
)
parser
.
add_argument
(
parser
.
add_argument
(
'--emb_dim'
,
'--emb_dim'
,
type
=
int
,
type
=
int
,
...
@@ -64,6 +72,10 @@ def parse_args():
...
@@ -64,6 +72,10 @@ def parse_args():
default
=
int
(
os
.
environ
.
get
(
'CROP_SIZE'
,
'1500'
)),
default
=
int
(
os
.
environ
.
get
(
'CROP_SIZE'
,
'1500'
)),
help
=
'The max sentence length of input. Since this model use plain RNN,'
help
=
'The max sentence length of input. Since this model use plain RNN,'
' Gradient could be explored if sentence is too long'
)
' Gradient could be explored if sentence is too long'
)
parser
.
add_argument
(
'--with_test'
,
action
=
'store_true'
,
help
=
'If set, test the testset during training.'
)
args
=
parser
.
parse_args
()
args
=
parser
.
parse_args
()
return
args
return
args
...
@@ -157,37 +169,43 @@ def main():
...
@@ -157,37 +169,43 @@ def main():
exe
=
fluid
.
Executor
(
place
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
exe
.
run
(
fluid
.
default_startup_program
())
def
train_loop
(
pass_num
,
crop_size
):
train_reader
=
batch
(
with
profiler
.
profiler
(
args
.
device
,
'total'
)
as
prof
:
paddle
.
reader
.
shuffle
(
for
pass_id
in
range
(
pass_num
):
crop_sentence
(
imdb
.
train
(
word_dict
),
args
.
crop_size
),
train_reader
=
batch
(
buf_size
=
25000
),
paddle
.
reader
.
shuffle
(
batch_size
=
args
.
batch_size
)
crop_sentence
(
imdb
.
train
(
word_dict
),
crop_size
),
buf_size
=
25000
),
iters
,
num_samples
,
start_time
=
0
,
0
,
time
.
time
()
batch_size
=
args
.
batch_size
)
for
pass_id
in
range
(
args
.
pass_num
):
word_nums
=
0
train_accs
=
[]
pass_start_time
=
time
.
time
()
train_losses
=
[]
for
batch_id
,
data
in
enumerate
(
train_reader
()):
for
batch_id
,
data
in
enumerate
(
train_reader
()):
tensor_words
=
to_lodtensor
([
x
[
0
]
for
x
in
data
],
place
)
if
iters
==
args
.
skip_batch_num
:
for
x
in
data
:
start_time
=
time
.
time
()
word_nums
+=
len
(
x
[
0
])
num_samples
=
0
label
=
numpy
.
array
([
x
[
1
]
for
x
in
data
]).
astype
(
"int64"
)
if
iters
==
args
.
iterations
:
label
=
label
.
reshape
((
-
1
,
1
))
break
loss_np
,
acc
,
weight
=
exe
.
run
(
tensor_words
=
to_lodtensor
([
x
[
0
]
for
x
in
data
],
place
)
fluid
.
default_main_program
(),
label
=
numpy
.
array
([
x
[
1
]
for
x
in
data
]).
astype
(
"int64"
)
feed
=
{
"words"
:
tensor_words
,
label
=
label
.
reshape
((
-
1
,
1
))
"label"
:
label
},
loss_np
,
acc
,
weight
=
exe
.
run
(
fetch_list
=
[
loss
,
batch_acc
,
batch_size_tensor
])
fluid
.
default_main_program
(),
print
(
"pass_id=%d, batch_id=%d, loss=%f, acc=%f"
%
feed
=
{
"words"
:
tensor_words
,
(
pass_id
,
batch_id
,
loss_np
,
acc
))
"label"
:
label
},
fetch_list
=
[
loss
,
batch_acc
,
batch_size_tensor
])
pass_end_time
=
time
.
time
()
iters
+=
1
time_consumed
=
pass_end_time
-
pass_start_time
for
x
in
data
:
words_per_sec
=
word_nums
/
time_consumed
num_samples
+=
len
(
x
[
0
])
print
(
"pass_id=%d, sec/pass: %f, words/s: %f"
%
print
(
(
pass_id
,
time_consumed
,
words_per_sec
))
"Pass = %d, Iter = %d, Loss = %f, Accuracy = %f"
%
(
pass_id
,
iters
,
loss_np
,
acc
)
train_loop
(
args
.
pass_num
,
args
.
crop_size
)
)
# The accuracy is the accumulation of batches, but not the current batch.
train_elapsed
=
time
.
time
()
-
start_time
examples_per_sec
=
num_samples
/
train_elapsed
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
(
num_samples
,
train_elapsed
,
examples_per_sec
))
exit
(
0
)
def
to_lodtensor
(
data
,
place
):
def
to_lodtensor
(
data
,
place
):
...
@@ -205,5 +223,14 @@ def to_lodtensor(data, place):
...
@@ -205,5 +223,14 @@ def to_lodtensor(data, place):
return
res
return
res
def
print_arguments
(
args
):
print
(
'----------- lstm Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
if
__name__
==
'__main__'
:
if
__name__
==
'__main__'
:
args
=
parse_args
()
print_arguments
(
args
)
main
()
main
()
benchmark/fluid/vgg.py
浏览文件 @
6e2424e4
...
@@ -191,25 +191,29 @@ def main():
...
@@ -191,25 +191,29 @@ def main():
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
iters
+=
1
iters
+=
1
num_samples
+=
len
(
data
)
num_samples
+=
len
(
y_
data
)
print
(
print
(
"Pass = %d, Iter = %d, Loss = %f, Accuracy = %f"
%
"Pass = %d, Iter = %d, Loss = %f, Accuracy = %f"
%
(
pass_id
,
iters
,
loss
,
acc
)
(
pass_id
,
iters
,
loss
,
acc
)
)
# The accuracy is the accumulation of batches, but not the current batch.
)
# The accuracy is the accumulation of batches, but not the current batch.
pass_train_acc
=
accuracy
.
eval
()
#
pass_train_acc = accuracy.eval()
train_losses
.
append
(
loss
)
train_losses
.
append
(
loss
)
train_accs
.
append
(
acc
)
train_accs
.
append
(
acc
)
print
(
"Pass: %d, Loss: %f, Train Accuray: %f
\n
"
%
(
pass_id
,
np
.
mean
(
train_losses
),
np
.
mean
(
train_accs
)))
train_elapsed
=
time
.
time
()
-
start_time
examples_per_sec
=
num_samples
/
train_elapsed
print
(
'
\n
Total examples: %d, total time: %.5f, %.5f examples/sed
\n
'
%
(
num_samples
,
train_elapsed
,
examples_per_sec
))
# evaluation
# evaluation
if
args
.
with_test
:
if
args
.
with_test
:
pass_test_acc
=
test
(
exe
)
pass_test_acc
=
test
(
exe
)
train_elapsed
=
time
.
time
()
-
start_time
exit
(
0
)
print
(
"Pass: %d, Loss: %f, Train Accuray: %f
\n
"
%
(
pass_id
,
np
.
mean
(
train_losses
),
np
.
mean
(
train_accs
)))
def
print_arguments
():
def
print_arguments
():
print
(
'----------- Configuration Arguments -----------'
)
print
(
'-----------
vgg
Configuration Arguments -----------'
)
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
for
arg
,
value
in
sorted
(
vars
(
args
).
iteritems
()):
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'%s: %s'
%
(
arg
,
value
))
print
(
'------------------------------------------------'
)
print
(
'------------------------------------------------'
)
...
...
paddle/.gitignore
浏览文件 @
6e2424e4
.timestamp
*.o
*.o
*.a
*.a
.svn
.svn
...
...
paddle/fluid/framework/executor.cc
浏览文件 @
6e2424e4
...
@@ -93,6 +93,43 @@ static void CheckTensorNANOrInf(const std::string& name,
...
@@ -93,6 +93,43 @@ static void CheckTensorNANOrInf(const std::string& name,
"Tensor %s contains NAN"
,
name
);
"Tensor %s contains NAN"
,
name
);
}
}
void
Executor
::
CreateVariables
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
)
{
auto
&
global_block
=
pdesc
.
Block
(
block_id
);
const
Scope
*
ancestor_scope
=
scope
;
while
(
ancestor_scope
->
parent
())
{
ancestor_scope
=
ancestor_scope
->
parent
();
}
if
(
ancestor_scope
!=
scope
)
{
for
(
auto
&
var
:
global_block
.
AllVars
())
{
if
(
var
->
Name
()
==
framework
::
kEmptyVarName
)
{
continue
;
}
if
(
var
->
Persistable
())
{
auto
*
ptr
=
const_cast
<
Scope
*>
(
ancestor_scope
)
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create Variable "
<<
var
->
Name
()
<<
" global, which pointer is "
<<
ptr
;
}
else
{
auto
*
ptr
=
scope
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create Variable "
<<
var
->
Name
()
<<
" locally, which pointer is "
<<
ptr
;
}
}
}
else
{
for
(
auto
&
var
:
global_block
.
AllVars
())
{
auto
*
ptr
=
scope
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create variable "
<<
var
->
Name
()
<<
", which pointer is "
<<
ptr
;
}
}
}
void
Executor
::
Run
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
,
void
Executor
::
Run
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
,
bool
create_local_scope
,
bool
create_vars
)
{
bool
create_local_scope
,
bool
create_vars
)
{
platform
::
RecordBlock
b
(
block_id
);
platform
::
RecordBlock
b
(
block_id
);
...
@@ -184,8 +221,8 @@ static bool has_fetch_operators(
...
@@ -184,8 +221,8 @@ static bool has_fetch_operators(
void
Executor
::
Run
(
const
ProgramDesc
&
program
,
Scope
*
scope
,
void
Executor
::
Run
(
const
ProgramDesc
&
program
,
Scope
*
scope
,
std
::
map
<
std
::
string
,
const
LoDTensor
*>&
feed_targets
,
std
::
map
<
std
::
string
,
const
LoDTensor
*>&
feed_targets
,
std
::
map
<
std
::
string
,
LoDTensor
*>&
fetch_targets
,
std
::
map
<
std
::
string
,
LoDTensor
*>&
fetch_targets
,
const
std
::
string
&
feed_holder_name
,
bool
create_vars
,
const
std
::
string
&
feed_holder_name
,
const
std
::
string
&
fetch_holder_name
,
bool
create_vars
)
{
const
std
::
string
&
fetch_holder_name
)
{
platform
::
RecordBlock
b
(
kProgramId
);
platform
::
RecordBlock
b
(
kProgramId
);
bool
has_feed_ops
=
bool
has_feed_ops
=
has_feed_operators
(
program
.
Block
(
0
),
feed_targets
,
feed_holder_name
);
has_feed_operators
(
program
.
Block
(
0
),
feed_targets
,
feed_holder_name
);
...
@@ -296,38 +333,13 @@ std::vector<std::shared_ptr<ExecutorPrepareContext>> Executor::Prepare(
...
@@ -296,38 +333,13 @@ std::vector<std::shared_ptr<ExecutorPrepareContext>> Executor::Prepare(
void
Executor
::
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
void
Executor
::
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
bool
create_local_scope
,
bool
create_vars
)
{
bool
create_local_scope
,
bool
create_vars
)
{
auto
&
block
=
ctx
->
prog_
.
Block
(
ctx
->
block_id_
);
Scope
*
local_scope
=
scope
;
Scope
*
local_scope
=
scope
;
if
(
create_vars
)
{
if
(
create_vars
)
{
if
(
create_local_scope
)
{
if
(
create_local_scope
)
{
local_scope
=
&
scope
->
NewScope
();
local_scope
=
&
scope
->
NewScope
();
for
(
auto
&
var
:
block
.
AllVars
())
{
}
if
(
var
->
Name
()
==
framework
::
kEmptyVarName
)
{
CreateVariables
(
ctx
->
prog_
,
local_scope
,
ctx
->
block_id_
);
continue
;
}
}
if
(
var
->
Persistable
())
{
auto
*
ptr
=
scope
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create Variable "
<<
var
->
Name
()
<<
" global, which pointer is "
<<
ptr
;
}
else
{
auto
*
ptr
=
local_scope
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create Variable "
<<
var
->
Name
()
<<
" locally, which pointer is "
<<
ptr
;
}
}
}
else
{
for
(
auto
&
var
:
block
.
AllVars
())
{
auto
*
ptr
=
local_scope
->
Var
(
var
->
Name
());
InitializeVariable
(
ptr
,
var
->
GetType
());
VLOG
(
3
)
<<
"Create variable "
<<
var
->
Name
()
<<
", which pointer is "
<<
ptr
;
}
}
// if (create_local_scope)
}
// if (create_vars)
for
(
auto
&
op
:
ctx
->
ops_
)
{
for
(
auto
&
op
:
ctx
->
ops_
)
{
VLOG
(
3
)
<<
place_
<<
" "
<<
op
->
DebugStringEx
(
local_scope
);
VLOG
(
3
)
<<
place_
<<
" "
<<
op
->
DebugStringEx
(
local_scope
);
...
...
paddle/fluid/framework/executor.h
浏览文件 @
6e2424e4
...
@@ -54,9 +54,9 @@ class Executor {
...
@@ -54,9 +54,9 @@ class Executor {
void
Run
(
const
ProgramDesc
&
program
,
Scope
*
scope
,
void
Run
(
const
ProgramDesc
&
program
,
Scope
*
scope
,
std
::
map
<
std
::
string
,
const
LoDTensor
*>&
feed_targets
,
std
::
map
<
std
::
string
,
const
LoDTensor
*>&
feed_targets
,
std
::
map
<
std
::
string
,
LoDTensor
*>&
fetch_targets
,
std
::
map
<
std
::
string
,
LoDTensor
*>&
fetch_targets
,
bool
create_vars
=
true
,
const
std
::
string
&
feed_holder_name
=
"feed"
,
const
std
::
string
&
feed_holder_name
=
"feed"
,
const
std
::
string
&
fetch_holder_name
=
"fetch"
,
const
std
::
string
&
fetch_holder_name
=
"fetch"
);
bool
create_vars
=
true
);
static
std
::
unique_ptr
<
ExecutorPrepareContext
>
Prepare
(
static
std
::
unique_ptr
<
ExecutorPrepareContext
>
Prepare
(
const
ProgramDesc
&
program
,
int
block_id
);
const
ProgramDesc
&
program
,
int
block_id
);
...
@@ -64,6 +64,8 @@ class Executor {
...
@@ -64,6 +64,8 @@ class Executor {
static
std
::
vector
<
std
::
shared_ptr
<
ExecutorPrepareContext
>>
Prepare
(
static
std
::
vector
<
std
::
shared_ptr
<
ExecutorPrepareContext
>>
Prepare
(
const
ProgramDesc
&
program
,
const
std
::
vector
<
int
>&
block_ids
);
const
ProgramDesc
&
program
,
const
std
::
vector
<
int
>&
block_ids
);
void
CreateVariables
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
);
void
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
void
RunPreparedContext
(
ExecutorPrepareContext
*
ctx
,
Scope
*
scope
,
bool
create_local_scope
=
true
,
bool
create_local_scope
=
true
,
bool
create_vars
=
true
);
bool
create_vars
=
true
);
...
...
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
6e2424e4
...
@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
...
@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/framework/parallel_executor.h"
#include "paddle/fluid/framework/parallel_executor.h"
#include "paddle/fluid/platform/profiler.h"
#include <string>
#include <string>
#include <vector>
#include <vector>
...
@@ -24,6 +23,7 @@ limitations under the License. */
...
@@ -24,6 +23,7 @@ limitations under the License. */
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
#include "paddle/fluid/platform/profiler.h"
namespace
paddle
{
namespace
paddle
{
namespace
framework
{
namespace
framework
{
...
@@ -43,30 +43,40 @@ class ParallelExecutorPrivate {
...
@@ -43,30 +43,40 @@ class ParallelExecutorPrivate {
#endif
#endif
};
};
std
::
vector
<
Scope
*>
&
ParallelExecutor
::
GetLocalScopes
()
{
return
member_
->
local_scopes_
;
}
ParallelExecutor
::
ParallelExecutor
(
ParallelExecutor
::
ParallelExecutor
(
size_t
num_threads
,
bool
use_event
,
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
unordered_set
<
std
::
string
>
&
params
,
const
std
::
unordered_set
<
std
::
string
>
&
params
,
const
ProgramDesc
&
startup_program
,
const
ProgramDesc
&
main_program
,
const
std
::
unordered_set
<
std
::
string
>
&
bcast_vars
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
bool
allow_op_delay
)
const
ProgramDesc
&
main_program
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
bool
allow_op_delay
)
:
member_
(
new
ParallelExecutorPrivate
(
places
))
{
:
member_
(
new
ParallelExecutorPrivate
(
places
))
{
member_
->
global_scope_
=
scope
;
member_
->
global_scope_
=
scope
;
// Step 1. RunStartupProgram and Bcast the params to devs.
// Step 1. Bcast the params to devs.
Executor
exe
(
places
[
0
]);
exe
.
Run
(
startup_program
,
scope
,
0
);
// Create local scopes
// Create local scopes
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
if
(
local_scopes
.
empty
())
{
member_
->
local_scopes_
.
push_back
(
&
scope
->
NewScope
());
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
member_
->
local_scopes_
.
push_back
(
&
scope
->
NewScope
());
}
}
else
{
PADDLE_ENFORCE_EQ
(
member_
->
places_
.
size
(),
local_scopes
.
size
());
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
member_
->
local_scopes_
.
push_back
(
local_scopes
[
i
]);
}
}
}
// Bcast Parameters to all GPUs
// Bcast Parameters to all GPUs
#ifdef PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
member_
->
nccl_ctxs_
.
reset
(
new
platform
::
NCCLContextMap
(
member_
->
places_
));
member_
->
nccl_ctxs_
.
reset
(
new
platform
::
NCCLContextMap
(
member_
->
places_
));
#endif
#endif
if
(
platform
::
is_gpu_place
(
places
[
0
])
&&
if
(
platform
::
is_gpu_place
(
places
[
0
])
&&
member_
->
local_scopes_
.
size
()
!=
1
&&
member_
->
local_scopes_
.
size
()
!=
1
)
{
// Is CUDA
local_scopes
.
empty
()
)
{
// Is CUDA
BCastParamsToGPUs
(
startup_program
);
BCastParamsToGPUs
(
bcast_vars
);
}
}
// Startup Program has been run. All local scopes has correct parameters.
// Startup Program has been run. All local scopes has correct parameters.
...
@@ -99,48 +109,47 @@ ParallelExecutor::ParallelExecutor(
...
@@ -99,48 +109,47 @@ ParallelExecutor::ParallelExecutor(
}
}
void
ParallelExecutor
::
BCastParamsToGPUs
(
void
ParallelExecutor
::
BCastParamsToGPUs
(
const
ProgramDesc
&
startup_program
)
const
{
const
std
::
unordered_set
<
std
::
string
>
&
vars
)
const
{
#ifdef PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
auto
*
main_scope
=
member_
->
local_scopes_
[
0
];
auto
*
main_scope
=
member_
->
local_scopes_
[
0
];
for
(
auto
*
var_desc
:
startup_program
.
Block
(
0
).
AllVars
())
{
for
(
auto
&
var
:
vars
)
{
size_t
idx
=
var_desc
->
Name
().
find
(
"@GRAD"
);
auto
*
main_var
=
main_scope
->
FindVar
(
var
);
if
(
idx
!=
std
::
string
::
npos
)
continue
;
if
(
!
main_var
->
IsType
<
LoDTensor
>
())
{
if
(
var_desc
->
GetType
()
==
proto
::
VarType
::
LOD_TENSOR
)
{
continue
;
auto
&
main_tensor
=
}
main_scope
->
FindVar
(
var_desc
->
Name
())
->
Get
<
LoDTensor
>
();
auto
&
main_tensor
=
main_var
->
Get
<
LoDTensor
>
();
auto
&
dims
=
main_tensor
.
dims
();
auto
&
dims
=
main_tensor
.
dims
();
if
(
paddle
::
platform
::
is_gpu_place
(
main_tensor
.
place
()))
{
size_t
numel
=
main_tensor
.
numel
();
if
(
paddle
::
platform
::
is_gpu_place
(
main_tensor
.
place
()))
{
ncclDataType_t
data_type
=
platform
::
ToNCCLDataType
(
main_tensor
.
type
());
size_t
numel
=
main_tensor
.
numel
();
platform
::
NCCLGroupGuard
guard
;
ncclDataType_t
data_type
=
platform
::
ToNCCLDataType
(
main_tensor
.
type
());
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
platform
::
NCCLGroupGuard
guard
;
auto
place
=
member_
->
places_
[
i
];
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
void
*
buffer
;
auto
place
=
member_
->
places_
[
i
];
if
(
i
==
0
)
{
void
*
buffer
;
buffer
=
const_cast
<
void
*>
(
main_tensor
.
data
<
void
>
());
if
(
i
==
0
)
{
}
else
{
buffer
=
const_cast
<
void
*>
(
main_tensor
.
data
<
void
>
());
auto
local_scope
=
member_
->
local_scopes_
[
i
];
}
else
{
auto
*
t
=
local_scope
->
Var
(
var_desc
->
Name
())
->
GetMutable
<
LoDTensor
>
();
t
->
Resize
(
dims
);
buffer
=
t
->
mutable_data
(
place
,
main_tensor
.
type
());
}
auto
&
nccl_ctx
=
member_
->
nccl_ctxs_
->
at
(
place
);
platform
::
dynload
::
ncclBcast
(
buffer
,
numel
,
data_type
,
0
,
nccl_ctx
.
comm_
,
nccl_ctx
.
stream
());
}
}
else
{
platform
::
CPUPlace
cpu
;
for
(
size_t
i
=
1
;
i
<
member_
->
places_
.
size
();
++
i
)
{
auto
local_scope
=
member_
->
local_scopes_
[
i
];
auto
local_scope
=
member_
->
local_scopes_
[
i
];
auto
*
t
=
local_scope
->
Var
(
var
_desc
->
Name
()
)
->
GetMutable
<
LoDTensor
>
();
auto
*
t
=
local_scope
->
Var
(
var
)
->
GetMutable
<
LoDTensor
>
();
t
->
Resize
(
dims
);
t
->
Resize
(
dims
);
t
->
mutable_data
(
cpu
,
main_tensor
.
type
());
buffer
=
t
->
mutable_data
(
place
,
main_tensor
.
type
());
paddle
::
framework
::
TensorCopy
(
main_tensor
,
cpu
,
t
);
}
}
auto
&
nccl_ctx
=
member_
->
nccl_ctxs_
->
at
(
place
);
platform
::
dynload
::
ncclBcast
(
buffer
,
numel
,
data_type
,
0
,
nccl_ctx
.
comm_
,
nccl_ctx
.
stream
());
}
}
else
{
platform
::
CPUPlace
cpu
;
for
(
size_t
i
=
1
;
i
<
member_
->
places_
.
size
();
++
i
)
{
auto
local_scope
=
member_
->
local_scopes_
[
i
];
auto
*
t
=
local_scope
->
Var
(
var
)
->
GetMutable
<
LoDTensor
>
();
t
->
Resize
(
dims
);
t
->
mutable_data
(
cpu
,
main_tensor
.
type
());
paddle
::
framework
::
TensorCopy
(
main_tensor
,
cpu
,
t
);
}
}
}
}
member_
->
nccl_ctxs_
->
WaitAll
();
member_
->
nccl_ctxs_
->
WaitAll
();
...
...
paddle/fluid/framework/parallel_executor.h
浏览文件 @
6e2424e4
...
@@ -36,11 +36,14 @@ class ParallelExecutor {
...
@@ -36,11 +36,14 @@ class ParallelExecutor {
explicit
ParallelExecutor
(
size_t
num_threads
,
bool
use_event
,
explicit
ParallelExecutor
(
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
platform
::
Place
>&
places
,
const
std
::
vector
<
platform
::
Place
>&
places
,
const
std
::
unordered_set
<
std
::
string
>&
params
,
const
std
::
unordered_set
<
std
::
string
>&
params
,
const
ProgramDesc
&
startup_program
,
const
std
::
unordered_set
<
std
::
string
>&
bcast_vars
,
const
ProgramDesc
&
main_program
,
const
ProgramDesc
&
main_program
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
vector
<
Scope
*>&
local_scopes
,
bool
allow_op_delay
);
bool
allow_op_delay
);
std
::
vector
<
Scope
*>&
GetLocalScopes
();
void
Run
(
const
std
::
vector
<
std
::
string
>&
fetch_tensors
,
void
Run
(
const
std
::
vector
<
std
::
string
>&
fetch_tensors
,
const
std
::
string
&
fetched_var_name
,
const
std
::
string
&
fetched_var_name
,
const
std
::
unordered_map
<
std
::
string
,
LoDTensor
>&
feed_tensors
);
const
std
::
unordered_map
<
std
::
string
,
LoDTensor
>&
feed_tensors
);
...
@@ -51,7 +54,7 @@ class ParallelExecutor {
...
@@ -51,7 +54,7 @@ class ParallelExecutor {
ParallelExecutorPrivate
*
member_
;
ParallelExecutorPrivate
*
member_
;
void
BCastParamsToGPUs
(
const
ProgramDesc
&
startup_program
)
const
;
void
BCastParamsToGPUs
(
const
std
::
unordered_set
<
std
::
string
>&
vars
)
const
;
};
};
}
// namespace framework
}
// namespace framework
...
...
paddle/fluid/framework/scope.h
浏览文件 @
6e2424e4
...
@@ -58,7 +58,7 @@ class Scope {
...
@@ -58,7 +58,7 @@ class Scope {
/// nullptr if cannot find.
/// nullptr if cannot find.
Variable
*
FindVar
(
const
std
::
string
&
name
)
const
;
Variable
*
FindVar
(
const
std
::
string
&
name
)
const
;
const
Scope
&
parent
()
const
{
return
*
parent_
;
}
const
Scope
*
parent
()
const
{
return
parent_
;
}
/// Find the scope or an ancestor scope that contains the given variable.
/// Find the scope or an ancestor scope that contains the given variable.
const
Scope
*
FindScope
(
const
Variable
*
var
)
const
;
const
Scope
*
FindScope
(
const
Variable
*
var
)
const
;
...
...
paddle/fluid/inference/tests/book/test_inference_image_classification.cc
浏览文件 @
6e2424e4
...
@@ -46,8 +46,8 @@ TEST(inference, image_classification) {
...
@@ -46,8 +46,8 @@ TEST(inference, image_classification) {
// Run inference on CPU
// Run inference on CPU
LOG
(
INFO
)
<<
"--- CPU Runs: ---"
;
LOG
(
INFO
)
<<
"--- CPU Runs: ---"
;
TestInference
<
paddle
::
platform
::
CPUPlace
>
(
dirname
,
cpu_feeds
,
cpu_fetchs1
,
TestInference
<
paddle
::
platform
::
CPUPlace
,
false
>
(
dirname
,
cpu_feeds
,
FLAGS_repeat
);
cpu_fetchs1
,
FLAGS_repeat
);
LOG
(
INFO
)
<<
output1
.
dims
();
LOG
(
INFO
)
<<
output1
.
dims
();
#ifdef PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
...
@@ -57,8 +57,8 @@ TEST(inference, image_classification) {
...
@@ -57,8 +57,8 @@ TEST(inference, image_classification) {
// Run inference on CUDA GPU
// Run inference on CUDA GPU
LOG
(
INFO
)
<<
"--- GPU Runs: ---"
;
LOG
(
INFO
)
<<
"--- GPU Runs: ---"
;
TestInference
<
paddle
::
platform
::
CUDAPlace
>
(
dirname
,
cpu_feeds
,
cpu_fetchs2
,
TestInference
<
paddle
::
platform
::
CUDAPlace
,
false
>
(
dirname
,
cpu_feeds
,
FLAGS_repeat
);
cpu_fetchs2
,
FLAGS_repeat
);
LOG
(
INFO
)
<<
output2
.
dims
();
LOG
(
INFO
)
<<
output2
.
dims
();
CheckError
<
float
>
(
output1
,
output2
);
CheckError
<
float
>
(
output1
,
output2
);
...
...
paddle/fluid/inference/tests/test_helper.h
浏览文件 @
6e2424e4
...
@@ -88,7 +88,7 @@ void CheckError(const paddle::framework::LoDTensor& output1,
...
@@ -88,7 +88,7 @@ void CheckError(const paddle::framework::LoDTensor& output1,
EXPECT_EQ
(
count
,
0U
)
<<
"There are "
<<
count
<<
" different elements."
;
EXPECT_EQ
(
count
,
0U
)
<<
"There are "
<<
count
<<
" different elements."
;
}
}
template
<
typename
Place
>
template
<
typename
Place
,
bool
CreateVars
=
true
>
void
TestInference
(
const
std
::
string
&
dirname
,
void
TestInference
(
const
std
::
string
&
dirname
,
const
std
::
vector
<
paddle
::
framework
::
LoDTensor
*>&
cpu_feeds
,
const
std
::
vector
<
paddle
::
framework
::
LoDTensor
*>&
cpu_feeds
,
const
std
::
vector
<
paddle
::
framework
::
LoDTensor
*>&
cpu_fetchs
,
const
std
::
vector
<
paddle
::
framework
::
LoDTensor
*>&
cpu_fetchs
,
...
@@ -166,8 +166,16 @@ void TestInference(const std::string& dirname,
...
@@ -166,8 +166,16 @@ void TestInference(const std::string& dirname,
// 6. Run the inference program
// 6. Run the inference program
{
{
if
(
!
CreateVars
)
{
// If users don't want to create and destroy variables every time they
// run, they need to set `create_vars` to false and manually call
// `CreateVariables` before running.
executor
.
CreateVariables
(
*
inference_program
,
scope
,
0
);
}
// Ignore the profiling results of the first run
// Ignore the profiling results of the first run
executor
.
Run
(
*
inference_program
,
scope
,
feed_targets
,
fetch_targets
);
executor
.
Run
(
*
inference_program
,
scope
,
feed_targets
,
fetch_targets
,
CreateVars
);
// Enable the profiler
// Enable the profiler
paddle
::
platform
::
EnableProfiler
(
state
);
paddle
::
platform
::
EnableProfiler
(
state
);
...
@@ -178,7 +186,8 @@ void TestInference(const std::string& dirname,
...
@@ -178,7 +186,8 @@ void TestInference(const std::string& dirname,
"run_inference"
,
"run_inference"
,
paddle
::
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
));
paddle
::
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
));
executor
.
Run
(
*
inference_program
,
scope
,
feed_targets
,
fetch_targets
);
executor
.
Run
(
*
inference_program
,
scope
,
feed_targets
,
fetch_targets
,
CreateVars
);
}
}
// Disable the profiler and print the timing information
// Disable the profiler and print the timing information
...
...
paddle/fluid/operators/go_op.cc
浏览文件 @
6e2424e4
...
@@ -56,11 +56,11 @@ class GoOp : public framework::OperatorBase {
...
@@ -56,11 +56,11 @@ class GoOp : public framework::OperatorBase {
// TODO(varunarora): Consider moving this root scope lookup to scope.h.
// TODO(varunarora): Consider moving this root scope lookup to scope.h.
const
framework
::
Scope
*
root_scope
=
&
scope
;
const
framework
::
Scope
*
root_scope
=
&
scope
;
const
framework
::
Scope
*
parent_scope
=
&
(
root_scope
->
parent
()
);
const
framework
::
Scope
*
parent_scope
=
root_scope
->
parent
(
);
while
(
parent_scope
!=
nullptr
)
{
while
(
parent_scope
!=
nullptr
)
{
root_scope
=
parent_scope
;
root_scope
=
parent_scope
;
parent_scope
=
&
(
parent_scope
->
parent
()
);
parent_scope
=
parent_scope
->
parent
(
);
}
}
framework
::
BlockDesc
*
block
=
Attr
<
framework
::
BlockDesc
*>
(
kBlock
);
framework
::
BlockDesc
*
block
=
Attr
<
framework
::
BlockDesc
*>
(
kBlock
);
...
...
paddle/fluid/operators/lod_reset_op.h
浏览文件 @
6e2424e4
...
@@ -14,6 +14,8 @@ limitations under the License. */
...
@@ -14,6 +14,8 @@ limitations under the License. */
#pragma once
#pragma once
#include <algorithm>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_registry.h"
...
@@ -35,7 +37,7 @@ class LoDResetKernel : public framework::OpKernel<T> {
...
@@ -35,7 +37,7 @@ class LoDResetKernel : public framework::OpKernel<T> {
if
(
lod_t
->
lod
().
size
()
>
0
)
{
if
(
lod_t
->
lod
().
size
()
>
0
)
{
auto
y_lod
=
lod_t
->
lod
();
auto
y_lod
=
lod_t
->
lod
();
auto
last_level
=
y_lod
[
y_lod
.
size
()
-
1
];
auto
last_level
=
y_lod
[
y_lod
.
size
()
-
1
];
PADDLE_ENFORCE_EQ
(
last_level
.
back
(
),
in
->
dims
()[
0
],
PADDLE_ENFORCE_EQ
(
(
int64_t
)(
last_level
.
back
()
),
in
->
dims
()[
0
],
"Last value of `Y`'s last level LoD should be equal "
"Last value of `Y`'s last level LoD should be equal "
"to the first dimension of `X`"
);
"to the first dimension of `X`"
);
out
->
set_lod
(
y_lod
);
out
->
set_lod
(
y_lod
);
...
...
paddle/fluid/platform/float16_test.cc
浏览文件 @
6e2424e4
...
@@ -8,13 +8,14 @@ distributed under the License is distributed on an "AS IS" BASIS,
...
@@ -8,13 +8,14 @@ distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/platform/float16.h"
#include <vector>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/init.h"
#include "paddle/fluid/framework/init.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include <gtest/gtest.h>
namespace
paddle
{
namespace
paddle
{
namespace
platform
{
namespace
platform
{
...
@@ -74,24 +75,27 @@ TEST(float16, conversion_cpu) {
...
@@ -74,24 +75,27 @@ TEST(float16, conversion_cpu) {
// Conversion operator
// Conversion operator
EXPECT_EQ
(
Eigen
::
half
(
float16
(
1.0
f
)).
x
,
0x3c00
);
EXPECT_EQ
(
Eigen
::
half
(
float16
(
1.0
f
)).
x
,
0x3c00
);
EXPECT_EQ
(
float
(
float16
(
0.5
f
)),
0.5
f
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
0.5
f
)),
0.5
f
);
EXPECT_NEAR
(
double
(
float16
(
0.33333
)),
0.33333
,
0.0001
);
EXPECT_NEAR
(
static_cast
<
double
>
(
float16
(
0.33333
)),
0.33333
,
0.0001
);
EXPECT_EQ
(
int
(
float16
(
-
1
)),
-
1
);
EXPECT_EQ
(
static_cast
<
int
>
(
float16
(
-
1
)),
-
1
);
EXPECT_EQ
(
bool
(
float16
(
true
)),
true
);
EXPECT_EQ
(
static_cast
<
bool
>
(
float16
(
true
)),
true
);
}
}
TEST
(
float16
,
arithmetic_cpu
)
{
TEST
(
float16
,
arithmetic_cpu
)
{
EXPECT_EQ
(
float
(
float16
(
1
)
+
float16
(
1
)),
2
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
1
)
+
float16
(
1
)),
2
);
EXPECT_EQ
(
float
(
float16
(
5
)
+
float16
(
-
5
)),
0
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
5
)
+
float16
(
-
5
)),
0
);
EXPECT_NEAR
(
float
(
float16
(
0.33333
f
)
+
float16
(
0.66667
f
)),
1.0
f
,
0.001
);
EXPECT_NEAR
(
static_cast
<
float
>
(
float16
(
0.33333
f
)
+
float16
(
0.66667
f
)),
1.0
f
,
EXPECT_EQ
(
float
(
float16
(
3
)
-
float16
(
5
)),
-
2
);
0.001
);
EXPECT_NEAR
(
float
(
float16
(
0.66667
f
)
-
float16
(
0.33333
f
)),
0.33334
f
,
0.001
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
3
)
-
float16
(
5
)),
-
2
);
EXPECT_NEAR
(
float
(
float16
(
3.3
f
)
*
float16
(
2.0
f
)),
6.6
f
,
0.01
);
EXPECT_NEAR
(
static_cast
<
float
>
(
float16
(
0.66667
f
)
-
float16
(
0.33333
f
)),
EXPECT_NEAR
(
float
(
float16
(
-
2.1
f
)
*
float16
(
-
3.0
f
)),
6.3
f
,
0.01
);
0.33334
f
,
0.001
);
EXPECT_NEAR
(
float
(
float16
(
2.0
f
)
/
float16
(
3.0
f
)),
0.66667
f
,
0.001
);
EXPECT_NEAR
(
static_cast
<
float
>
(
float16
(
3.3
f
)
*
float16
(
2.0
f
)),
6.6
f
,
0.01
);
EXPECT_EQ
(
float
(
float16
(
1.0
f
)
/
float16
(
2.0
f
)),
0.5
f
);
EXPECT_NEAR
(
static_cast
<
float
>
(
float16
(
-
2.1
f
)
*
float16
(
-
3.0
f
)),
6.3
f
,
0.01
);
EXPECT_EQ
(
float
(
-
float16
(
512.0
f
)),
-
512.0
f
);
EXPECT_NEAR
(
static_cast
<
float
>
(
float16
(
2.0
f
)
/
float16
(
3.0
f
)),
0.66667
f
,
EXPECT_EQ
(
float
(
-
float16
(
-
512.0
f
)),
512.0
f
);
0.001
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
1.0
f
)
/
float16
(
2.0
f
)),
0.5
f
);
EXPECT_EQ
(
static_cast
<
float
>
(
-
float16
(
512.0
f
)),
-
512.0
f
);
EXPECT_EQ
(
static_cast
<
float
>
(
-
float16
(
-
512.0
f
)),
512.0
f
);
}
}
TEST
(
float16
,
comparison_cpu
)
{
TEST
(
float16
,
comparison_cpu
)
{
...
...
paddle/fluid/platform/float16_test.cu
浏览文件 @
6e2424e4
...
@@ -36,19 +36,19 @@ limitations under the License. */
...
@@ -36,19 +36,19 @@ limitations under the License. */
half *in1, *in2, *out; \
half *in1, *in2, *out; \
half *d_in1, *d_in2, *d_out; \
half *d_in1, *d_in2, *d_out; \
int size = sizeof(half); \
int size = sizeof(half); \
cudaMalloc(
(void**)&d_in1, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in1), size);
\
cudaMalloc(
(void**)&d_in2, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in2), size);
\
cudaMalloc(
(void**)&d_out, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_out), size);
\
in1 =
(half*)malloc(size);
\
in1 =
reinterpret_cast<half*>(malloc(size));
\
in2 =
(half*)malloc(size);
\
in2 =
reinterpret_cast<half*>(malloc(size));
\
out =
(half*)malloc(size);
\
out =
reinterpret_cast<half*>(malloc(size));
\
in1[0] = half(float16(v_in1)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice); \
op_type<<<1, 1>>>(d_in1, d_in2, d_out); \
op_type<<<1, 1>>>(d_in1, d_in2, d_out); \
cudaMemcpy(out, d_out, size, cudaMemcpyDeviceToHost); \
cudaMemcpy(out, d_out, size, cudaMemcpyDeviceToHost); \
EXPECT_EQ(
float(float16(out[0])), v_out);
\
EXPECT_EQ(
static_cast<float>(float16(out[0])), v_out);
\
free(in1); \
free(in1); \
free(in2); \
free(in2); \
free(out); \
free(out); \
...
@@ -63,17 +63,17 @@ limitations under the License. */
...
@@ -63,17 +63,17 @@ limitations under the License. */
half *in1, *in2; \
half *in1, *in2; \
half *d_in1, *d_in2; \
half *d_in1, *d_in2; \
int size = sizeof(half); \
int size = sizeof(half); \
cudaMalloc(
(void**)&d_in1, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in1), size);
\
cudaMalloc(
(void**)&d_in2, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in2), size);
\
in1 =
(half*)malloc(size);
\
in1 =
reinterpret_cast<half*>(malloc(size));
\
in2 =
(half*)malloc(size);
\
in2 =
reinterpret_cast<half*>(malloc(size));
\
in1[0] = half(float16(v_in1)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in2, in2, size, cudaMemcpyHostToDevice); \
op_type<<<1, 1>>>(d_in1, d_in2); \
op_type<<<1, 1>>>(d_in1, d_in2); \
cudaMemcpy(in1, d_in1, size, cudaMemcpyDeviceToHost); \
cudaMemcpy(in1, d_in1, size, cudaMemcpyDeviceToHost); \
EXPECT_EQ(
float(float16(in1[0])), v_out);
\
EXPECT_EQ(
static_cast<float>(float16(in1[0])), v_out);
\
free(in1); \
free(in1); \
free(in2); \
free(in2); \
cudaFree(d_in1); \
cudaFree(d_in1); \
...
@@ -87,12 +87,12 @@ limitations under the License. */
...
@@ -87,12 +87,12 @@ limitations under the License. */
half *d_in1, *d_in2; \
half *d_in1, *d_in2; \
bool *out, *d_out; \
bool *out, *d_out; \
int size = sizeof(half); \
int size = sizeof(half); \
cudaMalloc(
(void**)&d_in1, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in1), size);
\
cudaMalloc(
(void**)&d_in2, size);
\
cudaMalloc(
reinterpret_cast<void**>(&d_in2), size);
\
cudaMalloc(
(void**)&d_out, 1);
\
cudaMalloc(
reinterpret_cast<void**>(&d_out), 1);
\
in1 =
(half*)malloc(size);
\
in1 =
reinterpret_cast<half*>(malloc(size));
\
in2 =
(half*)malloc(size);
\
in2 =
reinterpret_cast<half*>(malloc(size));
\
out =
(bool*)malloc(1);
\
out =
reinterpret_cast<bool*>(malloc(1));
\
in1[0] = half(float16(v_in1)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
...
@@ -130,13 +130,13 @@ void TestNeg(float v_in, float v_out) {
...
@@ -130,13 +130,13 @@ void TestNeg(float v_in, float v_out) {
LOG
(
INFO
)
<<
"Test Neg on GPU!"
;
LOG
(
INFO
)
<<
"Test Neg on GPU!"
;
half
*
in
,
*
d_in
;
half
*
in
,
*
d_in
;
int
size
=
sizeof
(
half
);
int
size
=
sizeof
(
half
);
cudaMalloc
(
(
void
**
)
&
d_in
,
size
);
cudaMalloc
(
reinterpret_cast
<
void
**>
(
&
d_in
)
,
size
);
in
=
(
half
*
)
malloc
(
size
);
in
=
reinterpret_cast
<
half
*>
(
malloc
(
size
)
);
in
[
0
]
=
half
(
float16
(
v_in
));
in
[
0
]
=
half
(
float16
(
v_in
));
cudaMemcpy
(
d_in
,
in
,
size
,
cudaMemcpyHostToDevice
);
cudaMemcpy
(
d_in
,
in
,
size
,
cudaMemcpyHostToDevice
);
Neg
<<<
1
,
1
>>>
(
d_in
);
Neg
<<<
1
,
1
>>>
(
d_in
);
cudaMemcpy
(
in
,
d_in
,
size
,
cudaMemcpyDeviceToHost
);
cudaMemcpy
(
in
,
d_in
,
size
,
cudaMemcpyDeviceToHost
);
EXPECT_EQ
(
float
(
float16
(
in
[
0
])),
v_out
);
EXPECT_EQ
(
static_cast
<
float
>
(
float16
(
in
[
0
])),
v_out
);
free
(
in
);
free
(
in
);
cudaFree
(
d_in
);
cudaFree
(
d_in
);
}
}
...
...
paddle/fluid/pybind/.gitignore
0 → 100644
浏览文件 @
6e2424e4
pybind.h
paddle/fluid/pybind/pybind.cc
浏览文件 @
6e2424e4
...
@@ -544,13 +544,20 @@ All parameter, weight, gradient are variables in Paddle.
...
@@ -544,13 +544,20 @@ All parameter, weight, gradient are variables in Paddle.
[](
ParallelExecutor
&
self
,
size_t
num_threads
,
bool
use_event
,
[](
ParallelExecutor
&
self
,
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
unordered_set
<
std
::
string
>
&
params
,
const
std
::
unordered_set
<
std
::
string
>
&
params
,
const
ProgramDesc
&
startup_program
,
const
std
::
unordered_set
<
std
::
string
>
&
bcast_vars
,
const
ProgramDesc
&
main_program
,
const
std
::
string
&
loss_var_name
,
const
ProgramDesc
&
main_program
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
bool
allow_op_delay
)
{
Scope
*
scope
,
std
::
vector
<
Scope
*>
&
local_scopes
,
new
(
&
self
)
ParallelExecutor
(
num_threads
,
use_event
,
places
,
bool
allow_op_delay
)
{
params
,
startup_program
,
main_program
,
new
(
&
self
)
loss_var_name
,
scope
,
allow_op_delay
);
ParallelExecutor
(
num_threads
,
use_event
,
places
,
params
,
bcast_vars
,
main_program
,
loss_var_name
,
scope
,
local_scopes
,
allow_op_delay
);
})
})
.
def
(
"local_scopes"
,
[](
ParallelExecutor
&
self
)
->
std
::
vector
<
Scope
*>
*
{
return
&
self
.
GetLocalScopes
();
},
py
::
return_value_policy
::
reference
)
.
def
(
"run"
,
&
ParallelExecutor
::
Run
);
.
def
(
"run"
,
&
ParallelExecutor
::
Run
);
BindRecordIOWriter
(
&
m
);
BindRecordIOWriter
(
&
m
);
...
...
python/.gitignore
浏览文件 @
6e2424e4
*pyc
*pyc
build
build
dist
dist
paddlepaddle.egg-info
paddle.egg-info
paddle.egg-info
paddlepaddle_gpu.egg-info
paddlepaddle_gpu.egg-info
.idea
.idea
...
...
python/paddle/.gitignore
0 → 100644
浏览文件 @
6e2424e4
version.py
python/paddle/fluid/framework.py
浏览文件 @
6e2424e4
...
@@ -659,7 +659,7 @@ class Block(object):
...
@@ -659,7 +659,7 @@ class Block(object):
def
__init__
(
self
,
program
,
idx
):
def
__init__
(
self
,
program
,
idx
):
self
.
desc
=
program
.
desc
.
block
(
idx
)
self
.
desc
=
program
.
desc
.
block
(
idx
)
self
.
vars
=
dict
()
# var_name --> var
self
.
vars
=
dict
()
# var_name --> var
self
.
ops
=
collections
.
deque
()
# operator list
self
.
ops
=
list
()
# operator list
self
.
program
=
program
self
.
program
=
program
self
.
removed_vars
=
dict
()
self
.
removed_vars
=
dict
()
...
@@ -831,6 +831,13 @@ class Block(object):
...
@@ -831,6 +831,13 @@ class Block(object):
self
.
ops
.
append
(
op
)
self
.
ops
.
append
(
op
)
return
op
return
op
def
insert_op
(
self
,
index
,
*
args
,
**
kwargs
):
self
.
sync_with_cpp
()
op_desc
=
self
.
desc
.
insert_op
(
index
)
op
=
Operator
(
block
=
self
,
desc
=
op_desc
,
*
args
,
**
kwargs
)
self
.
ops
.
insert
(
index
,
op
)
return
op
def
delete_ops
(
self
,
ops
):
def
delete_ops
(
self
,
ops
):
# remove from cpp
# remove from cpp
# FIXME(typhoonzero): remove only the first occurrence.
# FIXME(typhoonzero): remove only the first occurrence.
...
@@ -842,12 +849,12 @@ class Block(object):
...
@@ -842,12 +849,12 @@ class Block(object):
self
.
desc
.
remove_op
(
start
,
end
+
1
)
self
.
desc
.
remove_op
(
start
,
end
+
1
)
def
slice_ops
(
self
,
start
,
end
):
def
slice_ops
(
self
,
start
,
end
):
return
list
(
self
.
ops
)
[
start
:
end
]
return
self
.
ops
[
start
:
end
]
def
prepend_op
(
self
,
*
args
,
**
kwargs
):
def
prepend_op
(
self
,
*
args
,
**
kwargs
):
op_desc
=
self
.
desc
.
prepend_op
()
op_desc
=
self
.
desc
.
prepend_op
()
op
=
Operator
(
self
,
op_desc
,
*
args
,
**
kwargs
)
op
=
Operator
(
self
,
op_desc
,
*
args
,
**
kwargs
)
self
.
ops
.
appendleft
(
op
)
self
.
ops
.
insert
(
0
,
op
)
return
op
return
op
def
sync_with_cpp
(
self
):
def
sync_with_cpp
(
self
):
...
@@ -892,7 +899,7 @@ class Block(object):
...
@@ -892,7 +899,7 @@ class Block(object):
for
index
in
range
((
start_index
-
1
-
1
),
-
1
,
-
1
):
for
index
in
range
((
start_index
-
1
-
1
),
-
1
,
-
1
):
op_desc
=
ops_in_cpp
[
index
]
op_desc
=
ops_in_cpp
[
index
]
op
=
Operator
(
self
,
op_desc
)
op
=
Operator
(
self
,
op_desc
)
self
.
ops
.
appendleft
(
op
)
self
.
ops
.
insert
(
0
,
op
)
# sync ops append to the end of cpp_ops
# sync ops append to the end of cpp_ops
for
index
in
range
((
end_index
+
1
),
len
(
ops_in_cpp
)):
for
index
in
range
((
end_index
+
1
),
len
(
ops_in_cpp
)):
...
...
python/paddle/fluid/parallel_executor.py
浏览文件 @
6e2424e4
...
@@ -22,10 +22,49 @@ __all__ = ['ParallelExecutor']
...
@@ -22,10 +22,49 @@ __all__ = ['ParallelExecutor']
class
ParallelExecutor
(
object
):
class
ParallelExecutor
(
object
):
def
__init__
(
self
,
def
__init__
(
self
,
loss_name
,
use_cuda
,
use_cuda
,
loss_name
=
None
,
main_program
=
None
,
num_threads
=
None
,
num_threads
=
None
,
allow_op_delay
=
False
):
allow_op_delay
=
False
,
share_vars_from
=
None
):
"""
ParallelExecutor can run program in parallel.
Args:
use_cuda(bool): Whether to use CUDA or not.
loss_name(str, default None): The loss name must set in training.
main_program(Program, default None): The program that need to run,
if not provided, then default_main_program will be used.
num_threads(int, default None): How many threads are used for
training.
allow_op_delay(bool, default False): Whether to delay and buffer
some operators together for scheduling or not, which may
improve performance in some cases, defalut False.
share_vars_from(ParallelExecutor, default None): If provied,
it will share variables from the specified ParallelExecutor.
Returns:
A ParallelExecutor object.
Raises:
TypeError: If share_vars_from is provided, but not ParallelExecutor
object.
Examples:
.. code-block:: python
train_exe = fluid.ParallelExecutor(
use_cuda=True, loss_name=loss.name)
test_exe = fluid.ParallelExecutor(
use_cuda=True,
main_program=test_program,
share_vars_from=train_exe)
train_loss, = train_exe.run([loss.name], feed_dict=feed_dict)
test_loss, = test_exe.run([loss.name], feed_dict=feed_dict)
"""
self
.
_places
=
[]
self
.
_places
=
[]
self
.
_act_places
=
[]
self
.
_act_places
=
[]
if
use_cuda
:
if
use_cuda
:
...
@@ -50,10 +89,21 @@ class ParallelExecutor(object):
...
@@ -50,10 +89,21 @@ class ParallelExecutor(object):
else
:
else
:
min
(
len
(
self
.
_places
)
*
2
,
multiprocessing
.
cpu_count
())
min
(
len
(
self
.
_places
)
*
2
,
multiprocessing
.
cpu_count
())
startup
=
framework
.
default_startup_program
()
main
=
main_program
main
=
framework
.
default_main_program
()
main
=
main
if
main
else
framework
.
default_main_program
()
scope
=
executor
.
global_scope
()
scope
=
executor
.
global_scope
()
if
share_vars_from
and
not
isinstance
(
share_vars_from
,
ParallelExecutor
):
raise
TypeError
(
"share_vars_from must be ParallelExecutor."
)
local_scopes
=
share_vars_from
.
executor
.
local_scopes
(
)
if
share_vars_from
else
[]
persistable_vars
=
[
v
.
name
for
v
in
filter
(
lambda
var
:
var
.
persistable
,
main
.
list_vars
())
]
self
.
executor
=
core
.
ParallelExecutor
(
self
.
executor
=
core
.
ParallelExecutor
(
num_threads
,
num_threads
,
True
if
use_cuda
else
False
,
# use_event
True
if
use_cuda
else
False
,
# use_event
...
@@ -62,10 +112,11 @@ class ParallelExecutor(object):
...
@@ -62,10 +112,11 @@ class ParallelExecutor(object):
p
.
name
for
p
in
main
.
global_block
().
iter_parameters
()
p
.
name
for
p
in
main
.
global_block
().
iter_parameters
()
if
not
p
.
stop_gradient
if
not
p
.
stop_gradient
]),
]),
s
tartup
.
desc
,
s
et
(
persistable_vars
)
,
main
.
desc
,
main
.
desc
,
loss_name
,
loss_name
if
loss_name
else
''
,
scope
,
scope
,
local_scopes
,
allow_op_delay
)
allow_op_delay
)
self
.
scope
=
scope
self
.
scope
=
scope
...
...
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @
6e2424e4
...
@@ -535,9 +535,37 @@ class TestSwish(OpTest):
...
@@ -535,9 +535,37 @@ class TestSwish(OpTest):
#--------------------test MKLDNN--------------------
#--------------------test MKLDNN--------------------
class
TestMKLDNNRelu
(
TestRelu
):
class
TestMKLDNNRelu
Dim2
(
TestRelu
):
def
setUp
(
self
):
def
setUp
(
self
):
super
(
TestMKLDNNRelu
,
self
).
setUp
()
super
(
TestMKLDNNReluDim2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNTanhDim2
(
TestTanh
):
def
setUp
(
self
):
super
(
TestMKLDNNTanhDim2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNSqrtDim2
(
TestSqrt
):
def
setUp
(
self
):
super
(
TestMKLDNNSqrtDim2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNAbsDim2
(
TestAbs
):
def
setUp
(
self
):
super
(
TestMKLDNNAbsDim2
,
self
).
setUp
()
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNReluDim4
(
TestRelu
):
def
setUp
(
self
):
super
(
TestMKLDNNReluDim4
,
self
).
setUp
()
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
# The same reason with TestAbs
# The same reason with TestAbs
...
@@ -549,9 +577,9 @@ class TestMKLDNNRelu(TestRelu):
...
@@ -549,9 +577,9 @@ class TestMKLDNNRelu(TestRelu):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNTanh
(
TestTanh
):
class
TestMKLDNNTanh
Dim4
(
TestTanh
):
def
setUp
(
self
):
def
setUp
(
self
):
super
(
TestMKLDNNTanh
,
self
).
setUp
()
super
(
TestMKLDNNTanh
Dim4
,
self
).
setUp
()
self
.
inputs
=
{
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
...
@@ -560,9 +588,9 @@ class TestMKLDNNTanh(TestTanh):
...
@@ -560,9 +588,9 @@ class TestMKLDNNTanh(TestTanh):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNSqrt
(
TestSqrt
):
class
TestMKLDNNSqrt
Dim4
(
TestSqrt
):
def
setUp
(
self
):
def
setUp
(
self
):
super
(
TestMKLDNNSqrt
,
self
).
setUp
()
super
(
TestMKLDNNSqrt
Dim4
,
self
).
setUp
()
self
.
inputs
=
{
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
...
@@ -571,9 +599,9 @@ class TestMKLDNNSqrt(TestSqrt):
...
@@ -571,9 +599,9 @@ class TestMKLDNNSqrt(TestSqrt):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
self
.
attrs
=
{
"use_mkldnn"
:
True
}
class
TestMKLDNNAbs
(
TestAbs
):
class
TestMKLDNNAbs
Dim4
(
TestAbs
):
def
setUp
(
self
):
def
setUp
(
self
):
super
(
TestMKLDNNAbs
,
self
).
setUp
()
super
(
TestMKLDNNAbs
Dim4
,
self
).
setUp
()
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
"float32"
)
# The same reason with TestAbs
# The same reason with TestAbs
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor.py
浏览文件 @
6e2424e4
...
@@ -207,7 +207,11 @@ class TestParallelExecutorBase(unittest.TestCase):
...
@@ -207,7 +207,11 @@ class TestParallelExecutorBase(unittest.TestCase):
if
memory_opt
:
if
memory_opt
:
fluid
.
memory_optimize
(
main
)
fluid
.
memory_optimize
(
main
)
exe
=
fluid
.
ParallelExecutor
(
loss_name
=
loss
.
name
,
use_cuda
=
True
)
place
=
fluid
.
CUDAPlace
(
0
)
startup_exe
=
fluid
.
Executor
(
place
)
startup_exe
.
run
(
startup
)
exe
=
fluid
.
ParallelExecutor
(
True
,
loss_name
=
loss
.
name
)
if
batch_size
is
not
None
:
if
batch_size
is
not
None
:
batch_size
*=
fluid
.
core
.
get_cuda_device_count
()
batch_size
*=
fluid
.
core
.
get_cuda_device_count
()
begin
=
time
.
time
()
begin
=
time
.
time
()
...
@@ -453,3 +457,41 @@ class TestTransformer(TestParallelExecutorBase):
...
@@ -453,3 +457,41 @@ class TestTransformer(TestParallelExecutorBase):
@
unittest
.
skip
(
"transformer is buggy in multi gpu"
)
@
unittest
.
skip
(
"transformer is buggy in multi gpu"
)
def
test_main
(
self
):
def
test_main
(
self
):
self
.
check_network_convergence
(
transformer
)
self
.
check_network_convergence
(
transformer
)
class
ParallelExecutorTestingDuringTraining
(
unittest
.
TestCase
):
def
test_parallel_testing
(
self
):
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main
,
startup
):
loss
=
simple_fc_net
(
True
)
test_program
=
main
.
clone
(
for_test
=
True
)
opt
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.0001
)
opt
.
minimize
(
loss
)
batch_size
=
32
image
=
numpy
.
random
.
normal
(
size
=
(
batch_size
,
784
)).
astype
(
'float32'
)
label
=
numpy
.
random
.
randint
(
0
,
10
,
(
batch_size
,
1
),
dtype
=
"int64"
)
place
=
fluid
.
CUDAPlace
(
0
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
startup
)
feed_dict
=
{
'image'
:
image
,
'label'
:
label
}
train_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
loss
.
name
,
main_program
=
main
)
test_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
main_program
=
test_program
,
share_vars_from
=
train_exe
)
for
i
in
xrange
(
5
):
test_loss
,
=
test_exe
.
run
([
loss
.
name
],
feed_dict
=
feed_dict
)
test_loss
=
numpy
.
array
(
test_loss
)
train_loss
,
=
train_exe
.
run
([
loss
.
name
],
feed_dict
=
feed_dict
)
train_loss
=
numpy
.
array
(
train_loss
)
self
.
assertTrue
(
numpy
.
allclose
(
train_loss
,
test_loss
))
编辑
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