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98cc7fee
编写于
4月 18, 2021
作者:
Z
zhangjun
浏览文件
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电子邮件补丁
差异文件
add vgg19, bert, ernie example for xpu deployment
上级
1cab575a
变更
13
展开全部
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13 changed file
with
42772 addition
and
0 deletion
+42772
-0
python/examples/xpu/bert/README.md
python/examples/xpu/bert/README.md
+20
-0
python/examples/xpu/bert/bert_client.py
python/examples/xpu/bert/bert_client.py
+37
-0
python/examples/xpu/bert/bert_web_service.py
python/examples/xpu/bert/bert_web_service.py
+48
-0
python/examples/xpu/bert/chinese_bert_reader.py
python/examples/xpu/bert/chinese_bert_reader.py
+123
-0
python/examples/xpu/bert/vocab.txt
python/examples/xpu/bert/vocab.txt
+21128
-0
python/examples/xpu/ernie/README.md
python/examples/xpu/ernie/README.md
+20
-0
python/examples/xpu/ernie/chinese_ernie_reader.py
python/examples/xpu/ernie/chinese_ernie_reader.py
+130
-0
python/examples/xpu/ernie/erine_web_service.py
python/examples/xpu/ernie/erine_web_service.py
+48
-0
python/examples/xpu/ernie/ernie_client.py
python/examples/xpu/ernie/ernie_client.py
+37
-0
python/examples/xpu/ernie/vocab.txt
python/examples/xpu/ernie/vocab.txt
+21128
-0
python/examples/xpu/vgg19/README.md
python/examples/xpu/vgg19/README.md
+20
-0
python/examples/xpu/vgg19/daisy.jpg
python/examples/xpu/vgg19/daisy.jpg
+0
-0
python/examples/xpu/vgg19/vgg19_client.py
python/examples/xpu/vgg19/vgg19_client.py
+33
-0
未找到文件。
python/examples/xpu/bert/README.md
0 → 100644
浏览文件 @
98cc7fee
## Prepare
### convert model
```
python -m paddle_serving_client.convert --dirname infer_bert-base-chinese_ft_model_4000.pdparams
```
## RPC Service
### Start Service
```
pytyon bert_web_service.py serving_server 7703
```
### Client Prediction
```
python bert_client.py
```
python/examples/xpu/bert/bert_client.py
0 → 100644
浏览文件 @
98cc7fee
# coding:utf-8
# pylint: disable=doc-string-missing
# Copyright (c) 2020 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
sys
from
paddle_serving_client
import
Client
from
paddle_serving_client.utils
import
benchmark_args
from
chinese_bert_reader
import
ChineseBertReader
import
numpy
as
np
args
=
benchmark_args
()
reader
=
ChineseBertReader
({
"max_seq_len"
:
128
})
fetch
=
[
"save_infer_model/scale_0.tmp_1"
]
endpoint_list
=
[
'127.0.0.1:7703'
]
client
=
Client
()
client
.
load_client_config
(
args
.
model
)
client
.
connect
(
endpoint_list
)
for
line
in
sys
.
stdin
:
feed_dict
=
reader
.
process
(
line
)
for
key
in
feed_dict
.
keys
():
feed_dict
[
key
]
=
np
.
array
(
feed_dict
[
key
]).
reshape
((
128
,
1
))
#print(feed_dict)
result
=
client
.
predict
(
feed
=
feed_dict
,
fetch
=
fetch
,
batch
=
False
)
print
(
result
)
python/examples/xpu/bert/bert_web_service.py
0 → 100644
浏览文件 @
98cc7fee
# coding=utf-8
# Copyright (c) 2020 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.
# pylint: disable=doc-string-missing
from
paddle_serving_server.web_service
import
WebService
from
paddle_serving_app.reader
import
ChineseBertReader
import
sys
import
os
import
numpy
as
np
class
BertService
(
WebService
):
def
load
(
self
):
self
.
reader
=
ChineseBertReader
({
"vocab_file"
:
"vocab.txt"
,
"max_seq_len"
:
128
})
def
preprocess
(
self
,
feed
=
[],
fetch
=
[]):
feed_res
=
[]
is_batch
=
False
for
ins
in
feed
:
feed_dict
=
self
.
reader
.
process
(
ins
[
"words"
].
encode
(
"utf-8"
))
for
key
in
feed_dict
.
keys
():
feed_dict
[
key
]
=
np
.
array
(
feed_dict
[
key
]).
reshape
(
(
len
(
feed_dict
[
key
]),
1
))
feed_res
.
append
(
feed_dict
)
return
feed_res
,
fetch
,
is_batch
bert_service
=
BertService
(
name
=
"bert"
)
bert_service
.
load
()
bert_service
.
load_model_config
(
sys
.
argv
[
1
])
bert_service
.
prepare_server
(
workdir
=
"workdir"
,
port
=
int
(
sys
.
argv
[
2
]),
use_lite
=
True
,
use_xpu
=
True
,
ir_optim
=
True
)
bert_service
.
run_rpc_service
()
bert_service
.
run_web_service
()
python/examples/xpu/bert/chinese_bert_reader.py
0 → 100644
浏览文件 @
98cc7fee
# Copyright (c) 2020 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.
# coding=utf-8
from
paddle_serving_app.reader.bert_base_reader
import
BertBaseReader
from
paddle_serving_app.reader.batching
import
pad_batch_data
from
paddle_serving_app.reader.tokenization
import
FullTokenizer
,
convert_to_unicode
class
ChineseBertReader
(
BertBaseReader
):
"""
ChineseBertReader handles the most traditional Chinese Bert
preprocessing, a user can define the vocab file through initialization
Examples:
from paddle_serving_app import ChineseBertReader
line = ["this is China"]
reader = ChineseBertReader()
reader.process(line[0])
"""
def
__init__
(
self
,
args
=
{}):
super
(
ChineseBertReader
,
self
).
__init__
()
vocab_file
=
""
if
"vocab_file"
in
args
:
vocab_file
=
args
[
"vocab_file"
]
else
:
vocab_file
=
self
.
_download_or_not
()
self
.
tokenizer
=
FullTokenizer
(
vocab_file
=
vocab_file
)
if
"max_seq_len"
in
args
:
self
.
max_seq_len
=
args
[
"max_seq_len"
]
else
:
self
.
max_seq_len
=
20
self
.
vocab
=
self
.
tokenizer
.
vocab
self
.
pad_id
=
self
.
vocab
[
"[PAD]"
]
self
.
cls_id
=
self
.
vocab
[
"[CLS]"
]
self
.
sep_id
=
self
.
vocab
[
"[SEP]"
]
self
.
mask_id
=
self
.
vocab
[
"[MASK]"
]
self
.
feed_keys
=
[
"input_ids"
,
"token_type_ids"
]
"""
inner function
"""
def
_download_or_not
(
self
):
import
os
import
paddle_serving_app
module_path
=
os
.
path
.
dirname
(
paddle_serving_app
.
__file__
)
full_path
=
"{}/tmp/chinese_bert"
.
format
(
module_path
)
os
.
system
(
"mkdir -p {}"
.
format
(
full_path
))
if
os
.
path
.
exists
(
"{}/vocab.txt"
.
format
(
full_path
)):
pass
else
:
url
=
"https://paddle-serving.bj.bcebos.com/reader/chinese_bert/vocab.txt"
r
=
os
.
system
(
"wget --no-check-certificate "
+
url
)
os
.
system
(
"mv vocab.txt {}"
.
format
(
full_path
))
if
r
!=
0
:
raise
SystemExit
(
'Download failed, please check your network'
)
return
"{}/vocab.txt"
.
format
(
full_path
)
"""
inner function
"""
def
_pad_batch
(
self
,
token_ids
,
text_type_ids
):
batch_token_ids
=
[
token_ids
]
batch_text_type_ids
=
[
text_type_ids
]
padded_token_ids
,
input_mask
=
pad_batch_data
(
batch_token_ids
,
max_seq_len
=
self
.
max_seq_len
,
pad_idx
=
self
.
pad_id
,
return_input_mask
=
True
)
padded_text_type_ids
=
pad_batch_data
(
batch_text_type_ids
,
max_seq_len
=
self
.
max_seq_len
,
pad_idx
=
self
.
pad_id
)
return
padded_token_ids
,
padded_text_type_ids
"""
process function deals with a raw Chinese string as a sentence
this funtion returns a feed_dict
default key of the returned feed_dict: input_ids, position_ids, segment_ids, input_mask
"""
def
process
(
self
,
line
):
text_a
=
convert_to_unicode
(
line
)
tokens_a
=
self
.
tokenizer
.
tokenize
(
text_a
)
if
len
(
tokens_a
)
>
self
.
max_seq_len
-
2
:
tokens_a
=
tokens_a
[
0
:(
self
.
max_seq_len
-
2
)]
tokens
=
[]
text_type_ids
=
[]
tokens
.
append
(
"[CLS]"
)
text_type_ids
.
append
(
0
)
for
token
in
tokens_a
:
tokens
.
append
(
token
)
text_type_ids
.
append
(
0
)
token_ids
=
self
.
tokenizer
.
convert_tokens_to_ids
(
tokens
)
#position_ids = list(range(len(token_ids)))
p_token_ids
,
p_text_type_ids
=
\
self
.
_pad_batch
(
token_ids
,
text_type_ids
)
feed_result
=
{
self
.
feed_keys
[
0
]:
p_token_ids
.
reshape
(
-
1
).
tolist
(),
#self.feed_keys[1]: p_pos_ids.reshape(-1).tolist(),
self
.
feed_keys
[
1
]:
p_text_type_ids
.
reshape
(
-
1
).
tolist
(),
#self.feed_keys[3]: input_mask.reshape(-1).tolist()
}
return
feed_result
python/examples/xpu/bert/vocab.txt
0 → 100644
浏览文件 @
98cc7fee
此差异已折叠。
点击以展开。
python/examples/xpu/ernie/README.md
0 → 100644
浏览文件 @
98cc7fee
## Prepare
### convert model
```
python3 -m paddle_serving_client.convert --dirname erine
```
## RPC Service
### Start Service
```
python3 -m paddle_serving_server.serve --model serving_server --port 7704 --use_lite --use_xpu --ir_optim
```
### Client Prediction
```
head data-c.txt | python3 ernie_client.py --model serving_client/serving_client_conf.prototxt
```
python/examples/xpu/ernie/chinese_ernie_reader.py
0 → 100644
浏览文件 @
98cc7fee
# Copyright (c) 2020 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.
# coding=utf-8
from
paddle_serving_app.reader.bert_base_reader
import
BertBaseReader
from
paddle_serving_app.reader.batching
import
pad_batch_data
from
paddle_serving_app.reader.tokenization
import
FullTokenizer
,
convert_to_unicode
class
ChineseErnieReader
(
BertBaseReader
):
"""
ChineseErnieReader handles the most traditional Chinese Bert
preprocessing, a user can define the vocab file through initialization
Examples:
from paddle_serving_app import ChineseErnieReader
line = ["this is China"]
reader = ChineseErnieReader()
reader.process(line[0])
"""
def
__init__
(
self
,
args
=
{}):
super
(
ChineseErnieReader
,
self
).
__init__
()
vocab_file
=
""
if
"vocab_file"
in
args
:
vocab_file
=
args
[
"vocab_file"
]
print
(
"vocab"
)
else
:
vocab_file
=
self
.
_download_or_not
()
self
.
tokenizer
=
FullTokenizer
(
vocab_file
=
vocab_file
)
print
(
self
.
tokenizer
)
if
"max_seq_len"
in
args
:
self
.
max_seq_len
=
args
[
"max_seq_len"
]
else
:
self
.
max_seq_len
=
20
self
.
vocab
=
self
.
tokenizer
.
vocab
self
.
pad_id
=
self
.
vocab
[
"[PAD]"
]
self
.
cls_id
=
self
.
vocab
[
"[CLS]"
]
self
.
sep_id
=
self
.
vocab
[
"[SEP]"
]
self
.
mask_id
=
self
.
vocab
[
"[MASK]"
]
self
.
feed_keys
=
[
"placeholder_0"
,
"placeholder_1"
,
"placeholder_2"
,
"placeholder_3"
]
"""
inner function
"""
def
_download_or_not
(
self
):
import
os
import
paddle_serving_app
module_path
=
os
.
path
.
dirname
(
paddle_serving_app
.
__file__
)
full_path
=
"{}/tmp/chinese_bert"
.
format
(
module_path
)
os
.
system
(
"mkdir -p {}"
.
format
(
full_path
))
if
os
.
path
.
exists
(
"{}/vocab.txt"
.
format
(
full_path
)):
pass
else
:
url
=
"https://paddle-serving.bj.bcebos.com/reader/chinese_bert/vocab.txt"
r
=
os
.
system
(
"wget --no-check-certificate "
+
url
)
os
.
system
(
"mv vocab.txt {}"
.
format
(
full_path
))
if
r
!=
0
:
raise
SystemExit
(
'Download failed, please check your network'
)
return
"{}/vocab.txt"
.
format
(
full_path
)
"""
inner function
"""
def
_pad_batch
(
self
,
token_ids
,
text_type_ids
,
position_ids
):
batch_token_ids
=
[
token_ids
]
batch_text_type_ids
=
[
text_type_ids
]
batch_position_ids
=
[
position_ids
]
padded_token_ids
,
input_mask
=
pad_batch_data
(
batch_token_ids
,
max_seq_len
=
self
.
max_seq_len
,
pad_idx
=
self
.
pad_id
,
return_input_mask
=
True
)
padded_text_type_ids
=
pad_batch_data
(
batch_text_type_ids
,
max_seq_len
=
self
.
max_seq_len
,
pad_idx
=
self
.
pad_id
)
padded_position_ids
=
pad_batch_data
(
batch_position_ids
,
max_seq_len
=
self
.
max_seq_len
,
pad_idx
=
self
.
pad_id
)
return
padded_token_ids
,
padded_position_ids
,
padded_text_type_ids
,
input_mask
"""
process function deals with a raw Chinese string as a sentence
this funtion returns a feed_dict
default key of the returned feed_dict: input_ids, position_ids, segment_ids, input_mask
"""
def
process
(
self
,
line
):
text_a
=
convert_to_unicode
(
line
)
tokens_a
=
self
.
tokenizer
.
tokenize
(
text_a
)
if
len
(
tokens_a
)
>
self
.
max_seq_len
-
2
:
tokens_a
=
tokens_a
[
0
:(
self
.
max_seq_len
-
2
)]
tokens
=
[]
text_type_ids
=
[]
tokens
.
append
(
"[CLS]"
)
text_type_ids
.
append
(
0
)
for
token
in
tokens_a
:
tokens
.
append
(
token
)
text_type_ids
.
append
(
0
)
token_ids
=
self
.
tokenizer
.
convert_tokens_to_ids
(
tokens
)
position_ids
=
list
(
range
(
len
(
token_ids
)))
p_token_ids
,
p_pos_ids
,
p_text_type_ids
,
input_mask
=
\
self
.
_pad_batch
(
token_ids
,
text_type_ids
,
position_ids
)
feed_result
=
{
self
.
feed_keys
[
0
]:
p_token_ids
.
reshape
(
-
1
).
tolist
(),
self
.
feed_keys
[
1
]:
p_pos_ids
.
reshape
(
-
1
).
tolist
(),
self
.
feed_keys
[
2
]:
p_text_type_ids
.
reshape
(
-
1
).
tolist
(),
self
.
feed_keys
[
3
]:
input_mask
.
reshape
(
-
1
).
tolist
()
}
return
feed_result
python/examples/xpu/ernie/erine_web_service.py
0 → 100644
浏览文件 @
98cc7fee
# coding=utf-8
# Copyright (c) 2020 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.
# pylint: disable=doc-string-missing
from
paddle_serving_server.web_service
import
WebService
from
paddle_serving_app.reader
import
ChineseBertReader
import
sys
import
os
import
numpy
as
np
class
BertService
(
WebService
):
def
load
(
self
):
self
.
reader
=
ChineseBertReader
({
"vocab_file"
:
"vocab.txt"
,
"max_seq_len"
:
128
})
def
preprocess
(
self
,
feed
=
[],
fetch
=
[]):
feed_res
=
[]
is_batch
=
False
for
ins
in
feed
:
feed_dict
=
self
.
reader
.
process
(
ins
[
"words"
].
encode
(
"utf-8"
))
for
key
in
feed_dict
.
keys
():
feed_dict
[
key
]
=
np
.
array
(
feed_dict
[
key
]).
reshape
(
(
len
(
feed_dict
[
key
]),
1
))
feed_res
.
append
(
feed_dict
)
return
feed_res
,
fetch
,
is_batch
bert_service
=
BertService
(
name
=
"bert"
)
bert_service
.
load
()
bert_service
.
load_model_config
(
sys
.
argv
[
1
])
bert_service
.
prepare_server
(
workdir
=
"workdir"
,
port
=
int
(
sys
.
argv
[
2
]),
use_lite
=
True
,
use_xpu
=
True
,
ir_optim
=
True
)
bert_service
.
run_rpc_service
()
bert_service
.
run_web_service
()
python/examples/xpu/ernie/ernie_client.py
0 → 100644
浏览文件 @
98cc7fee
# coding:utf-8
# pylint: disable=doc-string-missing
# Copyright (c) 2020 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
sys
from
paddle_serving_client
import
Client
from
paddle_serving_client.utils
import
benchmark_args
from
chinese_ernie_reader
import
ChineseErnieReader
import
numpy
as
np
args
=
benchmark_args
()
reader
=
ChineseErnieReader
({
"max_seq_len"
:
128
})
fetch
=
[
"save_infer_model/scale_0"
]
endpoint_list
=
[
'127.0.0.1:7704'
]
client
=
Client
()
client
.
load_client_config
(
args
.
model
)
client
.
connect
(
endpoint_list
)
for
line
in
sys
.
stdin
:
feed_dict
=
reader
.
process
(
line
)
for
key
in
feed_dict
.
keys
():
feed_dict
[
key
]
=
np
.
array
(
feed_dict
[
key
]).
reshape
((
128
,
1
))
# print(feed_dict)
result
=
client
.
predict
(
feed
=
feed_dict
,
fetch
=
fetch
,
batch
=
False
)
print
(
result
)
python/examples/xpu/ernie/vocab.txt
0 → 100644
浏览文件 @
98cc7fee
此差异已折叠。
点击以展开。
python/examples/xpu/vgg19/README.md
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浏览文件 @
98cc7fee
## Prepare
### convert model
```
python -m paddle_serving_client.convert --dirname VGG19
```
## RPC Service
### Start Service
```
python -m paddle_serving_server.serve --model serving_server --port 7702 --use_lite --use_xpu --ir_optim
```
### Client Prediction
```
python vgg19_client.py
```
python/examples/xpu/vgg19/daisy.jpg
0 → 100644
浏览文件 @
98cc7fee
38.8 KB
python/examples/xpu/vgg19/vgg19_client.py
0 → 100644
浏览文件 @
98cc7fee
# Copyright (c) 2020 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
paddle_serving_client
import
Client
from
paddle_serving_app.reader
import
Sequential
,
File2Image
,
Resize
,
CenterCrop
from
paddle_serving_app.reader
import
RGB2BGR
,
Transpose
,
Div
,
Normalize
client
=
Client
()
client
.
load_client_config
(
"serving_client/serving_client_conf.prototxt"
)
client
.
connect
([
"127.0.0.1:7702"
])
seq
=
Sequential
([
File2Image
(),
Resize
(
256
),
CenterCrop
(
224
),
RGB2BGR
(),
Transpose
((
2
,
0
,
1
)),
Div
(
255
),
Normalize
([
0.485
,
0.456
,
0.406
],
[
0.229
,
0.224
,
0.225
],
True
)
])
image_file
=
"daisy.jpg"
img
=
seq
(
image_file
)
fetch_map
=
client
.
predict
(
feed
=
{
"image"
:
img
},
fetch
=
[
"save_infer_model/scale_0"
])
#print(fetch_map)
print
(
fetch_map
[
"save_infer_model/scale_0"
].
reshape
(
-
1
))
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