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52a42433
编写于
3月 22, 2020
作者:
D
Dong Daxiang
提交者:
GitHub
3月 22, 2020
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差异文件
Merge pull request #299 from MRXLT/general-server-py3
add batch predict for web service
上级
8584d313
8781ca33
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
77 addition
and
31 deletion
+77
-31
python/examples/imagenet/image_classification_service.py
python/examples/imagenet/image_classification_service.py
+15
-5
python/examples/imagenet/image_classification_service_gpu.py
python/examples/imagenet/image_classification_service_gpu.py
+17
-6
python/examples/imagenet/image_http_client.py
python/examples/imagenet/image_http_client.py
+13
-4
python/paddle_serving_server/web_service.py
python/paddle_serving_server/web_service.py
+14
-7
python/paddle_serving_server_gpu/serve.py
python/paddle_serving_server_gpu/serve.py
+3
-2
python/paddle_serving_server_gpu/web_service.py
python/paddle_serving_server_gpu/web_service.py
+15
-7
未找到文件。
python/examples/imagenet/image_classification_service.py
浏览文件 @
52a42433
...
...
@@ -25,11 +25,21 @@ class ImageService(WebService):
reader
=
ImageReader
()
if
"image"
not
in
feed
:
raise
(
"feed data error!"
)
sample
=
base64
.
b64decode
(
feed
[
"image"
])
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
return
res_feed
,
fetch
if
isinstance
(
feed
[
"image"
],
list
):
feed_batch
=
[]
for
image
in
feed
[
"image"
]:
sample
=
base64
.
b64decode
(
image
)
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
feed_batch
.
append
(
res_feed
)
return
feed_batch
,
fetch
else
:
sample
=
base64
.
b64decode
(
feed
[
"image"
])
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
return
res_feed
,
fetch
image_service
=
ImageService
(
name
=
"image"
)
...
...
python/examples/imagenet/image_classification_service_gpu.py
浏览文件 @
52a42433
...
...
@@ -25,16 +25,27 @@ class ImageService(WebService):
reader
=
ImageReader
()
if
"image"
not
in
feed
:
raise
(
"feed data error!"
)
sample
=
base64
.
b64decode
(
feed
[
"image"
])
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
return
res_feed
,
fetch
print
(
type
(
feed
[
"image"
]),
isinstance
(
feed
[
"image"
],
list
))
if
isinstance
(
feed
[
"image"
],
list
):
feed_batch
=
[]
for
image
in
feed
[
"image"
]:
sample
=
base64
.
b64decode
(
image
)
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
feed_batch
.
append
(
res_feed
)
return
feed_batch
,
fetch
else
:
sample
=
base64
.
b64decode
(
feed
[
"image"
])
img
=
reader
.
process_image
(
sample
)
res_feed
=
{}
res_feed
[
"image"
]
=
img
.
reshape
(
-
1
)
return
res_feed
,
fetch
image_service
=
ImageService
(
name
=
"image"
)
image_service
.
load_model_config
(
sys
.
argv
[
1
])
image_service
.
set_gpus
(
"0,1
,2,3
"
)
image_service
.
set_gpus
(
"0,1"
)
image_service
.
prepare_server
(
workdir
=
sys
.
argv
[
2
],
port
=
int
(
sys
.
argv
[
3
]),
device
=
"gpu"
)
image_service
.
run_server
()
python/examples/imagenet/image_http_client.py
浏览文件 @
52a42433
...
...
@@ -24,17 +24,26 @@ def predict(image_path, server):
req
=
json
.
dumps
({
"image"
:
image
,
"fetch"
:
[
"score"
]})
r
=
requests
.
post
(
server
,
data
=
req
,
headers
=
{
"Content-Type"
:
"application/json"
})
print
(
r
.
json
()[
"score"
][
0
])
return
r
def
batch_predict
(
image_path
,
server
):
image
=
base64
.
b64encode
(
open
(
image_path
).
read
())
req
=
json
.
dumps
({
"image"
:
[
image
,
image
],
"fetch"
:
[
"score"
]})
r
=
requests
.
post
(
server
,
data
=
req
,
headers
=
{
"Content-Type"
:
"application/json"
})
print
(
r
.
json
()[
"result"
][
1
][
"score"
][
0
])
return
r
if
__name__
==
"__main__"
:
server
=
"http://127.0.0.1:9
295
/image/prediction"
server
=
"http://127.0.0.1:9
393
/image/prediction"
#image_path = "./data/n01440764_10026.JPEG"
image_list
=
os
.
listdir
(
"./
data/
image_data/n01440764/"
)
image_list
=
os
.
listdir
(
"./image_data/n01440764/"
)
start
=
time
.
time
()
for
img
in
image_list
:
image_file
=
"./
data/
image_data/n01440764/"
+
img
image_file
=
"./image_data/n01440764/"
+
img
res
=
predict
(
image_file
,
server
)
print
(
res
.
json
()[
"score"
][
0
])
end
=
time
.
time
()
print
(
end
-
start
)
python/paddle_serving_server/web_service.py
浏览文件 @
52a42433
...
...
@@ -64,12 +64,19 @@ class WebService(object):
if
"fetch"
not
in
request
.
json
:
abort
(
400
)
feed
,
fetch
=
self
.
preprocess
(
request
.
json
,
request
.
json
[
"fetch"
])
if
"fetch"
in
feed
:
del
feed
[
"fetch"
]
fetch_map
=
client_service
.
predict
(
feed
=
feed
,
fetch
=
fetch
)
fetch_map
=
self
.
postprocess
(
feed
=
request
.
json
,
fetch
=
fetch
,
fetch_map
=
fetch_map
)
return
fetch_map
if
isinstance
(
feed
,
list
):
fetch_map_batch
=
client_service
.
batch_predict
(
feed_batch
=
feed
,
fetch
=
fetch
)
fetch_map_batch
=
self
.
postprocess
(
feed
=
request
.
json
,
fetch
=
fetch
,
fetch_map
=
fetch_map_batch
)
result
=
{
"result"
:
fetch_map_batch
}
elif
isinstance
(
feed
,
dict
):
if
"fetch"
in
feed
:
del
feed
[
"fetch"
]
fetch_map
=
client_service
.
predict
(
feed
=
feed
,
fetch
=
fetch
)
result
=
self
.
postprocess
(
feed
=
request
.
json
,
fetch
=
fetch
,
fetch_map
=
fetch_map
)
return
result
app_instance
.
run
(
host
=
"0.0.0.0"
,
port
=
self
.
port
,
...
...
@@ -92,5 +99,5 @@ class WebService(object):
def
preprocess
(
self
,
feed
=
{},
fetch
=
[]):
return
feed
,
fetch
def
postprocess
(
self
,
feed
=
{},
fetch
=
[],
fetch_map
=
{}
):
def
postprocess
(
self
,
feed
=
{},
fetch
=
[],
fetch_map
=
None
):
return
fetch_map
python/paddle_serving_server_gpu/serve.py
浏览文件 @
52a42433
...
...
@@ -23,14 +23,14 @@ from multiprocessing import Pool, Process
from
paddle_serving_server_gpu
import
serve_args
def
start_gpu_card_model
(
gpuid
,
args
):
# pylint: disable=doc-string-missing
def
start_gpu_card_model
(
index
,
gpuid
,
args
):
# pylint: disable=doc-string-missing
gpuid
=
int
(
gpuid
)
device
=
"gpu"
port
=
args
.
port
if
gpuid
==
-
1
:
device
=
"cpu"
elif
gpuid
>=
0
:
port
=
args
.
port
+
gpuid
port
=
args
.
port
+
index
thread_num
=
args
.
thread
model
=
args
.
model
workdir
=
"{}_{}"
.
format
(
args
.
workdir
,
gpuid
)
...
...
@@ -78,6 +78,7 @@ def start_multi_card(args): # pylint: disable=doc-string-missing
p
=
Process
(
target
=
start_gpu_card_model
,
args
=
(
i
,
gpu_id
,
args
,
))
gpu_processes
.
append
(
p
)
for
p
in
gpu_processes
:
...
...
python/paddle_serving_server_gpu/web_service.py
浏览文件 @
52a42433
...
...
@@ -95,12 +95,20 @@ class WebService(object):
while
True
:
request_json
=
inputqueue
.
get
()
feed
,
fetch
=
self
.
preprocess
(
request_json
,
request_json
[
"fetch"
])
if
"fetch"
in
feed
:
del
feed
[
"fetch"
]
fetch_map
=
client
.
predict
(
feed
=
feed
,
fetch
=
fetch
)
fetch_map
=
self
.
postprocess
(
feed
=
request_json
,
fetch
=
fetch
,
fetch_map
=
fetch_map
)
self
.
output_queue
.
put
(
fetch_map
)
if
isinstance
(
feed
,
list
):
fetch_map_batch
=
client
.
batch_predict
(
feed_batch
=
feed
,
fetch
=
fetch
)
fetch_map_batch
=
self
.
postprocess
(
feed
=
request_json
,
fetch
=
fetch
,
fetch_map
=
fetch_map_batch
)
result
=
{
"result"
:
fetch_map_batch
}
elif
isinstance
(
feed
,
dict
):
if
"fetch"
in
feed
:
del
feed
[
"fetch"
]
fetch_map
=
client
.
predict
(
feed
=
feed
,
fetch
=
fetch
)
result
=
self
.
postprocess
(
feed
=
request_json
,
fetch
=
fetch
,
fetch_map
=
fetch_map
)
self
.
output_queue
.
put
(
result
)
def
_launch_web_service
(
self
,
gpu_num
):
app_instance
=
Flask
(
__name__
)
...
...
@@ -186,5 +194,5 @@ class WebService(object):
def
preprocess
(
self
,
feed
=
{},
fetch
=
[]):
return
feed
,
fetch
def
postprocess
(
self
,
feed
=
{},
fetch
=
[],
fetch_map
=
{}
):
def
postprocess
(
self
,
feed
=
{},
fetch
=
[],
fetch_map
=
None
):
return
fetch_map
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