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7c90d7a3
编写于
5月 02, 2018
作者:
X
Xin Pan
提交者:
GitHub
5月 02, 2018
浏览文件
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差异文件
Merge pull request #10128 from panyx0718/dist0423
add some instructions for running vgg distributedly
上级
c7e23bb7
f0917740
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
29 addition
and
7 deletion
+29
-7
benchmark/cluster/vgg16/run_vgg_dist.sh
benchmark/cluster/vgg16/run_vgg_dist.sh
+21
-0
benchmark/cluster/vgg16/vgg16_fluid.py
benchmark/cluster/vgg16/vgg16_fluid.py
+8
-7
未找到文件。
benchmark/cluster/vgg16/run_vgg_dist.sh
0 → 100644
浏览文件 @
7c90d7a3
#!/bin/bash
# Update to point to the source file.
VGG_SRC
=
"vgg16_fluid.py"
export
TRAINING_ROLE
=
PSERVER
export
TRAINERS
=
2
export
POD_IP
=
127.0.0.1
export
PADDLE_INIT_PORT
=
6174
MKL_NUM_THREADS
=
1 python
-u
${
VGG_SRC
}
--local
0
--ps_host
=
127.0.0.1:6174
--trainer_hosts
=
127.0.0.1:6174 &
# Need to wait for the ps to start first.
sleep
10
echo
"done start ps"
export
TRAINING_ROLE
=
TRAINER
export
TRAINERS
=
2
export
POD_IP
=
127.0.0.1
export
PADDLE_INIT_PORT
=
6174
CUDA_VISIBLE_DEVICES
=
4
MKL_NUM_THREADS
=
1 python
-u
${
VGG_SRC
}
--local
0
--ps_host
=
127.0.0.1:6174
--trainer_hosts
=
127.0.0.1:6174
--device
=
GPU
--task_index
=
0 &
CUDA_VISIBLE_DEVICES
=
5
MKL_NUM_THREADS
=
1 python
-u
${
VGG_SRC
}
--local
0
--ps_host
=
127.0.0.1:6174
--trainer_hosts
=
127.0.0.1:6174
--device
=
GPU
--task_index
=
1 &
benchmark/cluster/vgg16/vgg16_fluid.py
浏览文件 @
7c90d7a3
...
@@ -200,18 +200,19 @@ def main():
...
@@ -200,18 +200,19 @@ def main():
num_samples
+=
len
(
data
)
num_samples
+=
len
(
data
)
train_pass_acc
.
add
(
value
=
acc
,
weight
=
b_size
)
train_pass_acc
.
add
(
value
=
acc
,
weight
=
b_size
)
print
(
print
(
"Pass = %d, Iters = %d, Loss = %f, Accuracy = %f, Speed = %.2f img/s"
"Task:%d Pass = %d, Iters = %d, Loss = %f, Accuracy = %f, "
%
(
pass_id
,
iters
,
loss
,
acc
,
"Speed = %.2f img/s "
%
(
args
.
task_index
,
pass_id
,
iters
,
len
(
data
)
/
(
time
.
time
()
-
ts
))
loss
,
acc
,
len
(
data
)
/
(
time
.
time
()
-
ts
))
)
# 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_elapsed
=
time
.
time
()
-
start_time
pass_elapsed
=
time
.
time
()
-
start_time
pass_train_acc
=
train_pass_acc
.
eval
()
pass_train_acc
=
train_pass_acc
.
eval
()
pass_test_acc
=
test
(
exe
)
pass_test_acc
=
test
(
exe
)
print
(
print
(
"Task:%d Pass = %d, Training performance = %f imgs/s, "
"Pass = %d, Training performance = %f imgs/s, Train accuracy = %f, Test accuracy = %f
\n
"
"Train accuracy = %f, Test accuracy = %f
\n
"
%
%
(
pass_id
,
num_samples
/
pass_elapsed
,
pass_train_acc
,
(
args
.
task_index
,
pass_id
,
num_samples
/
pass_elapsed
,
pass_test_acc
))
pass_t
rain_acc
,
pass_t
est_acc
))
if
args
.
local
:
if
args
.
local
:
# Parameter initialization
# Parameter initialization
...
...
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