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VisualDL
未验证 提交 9583bf7c 编写于 作者: C chenjian 提交者： GitHub
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add English version for fastdeploy client (#1197) 

* add english page for fastdeploy client

* fix a bug
上级 a418dd44
隐藏空白更改
内联 并排
Showing with 598 addition and 80 deletion
visualdl/component/inference/fastdeploy_client/client_app.py
浏览文件 @ 9583bf7c
......@@ -18,6 +18,7 @@ import numpy as np
from .http_client_manager import get_metric_data
from .http_client_manager import HttpClientManager
from .http_client_manager import metrics_table_head
from .http_client_manager import metrics_table_head_en
from .visualizer import visualize_detection
from .visualizer import visualize_face_alignment
from .visualizer import visualize_face_detection
......@@ -257,11 +258,400 @@ def create_gradio_client_app(): # noqa:C901
max_lines=1,
interactive=False)
lang_text = gr.Textbox(
label="lang",
show_label=False,
value='zh',
max_lines=1,
visible=False
) # This text box is only used for divide zh and en page
all_input_output_components = input_accordions + input_name_texts + input_images + \
input_texts + output_accordions + output_name_texts + output_images + output_texts
def get_input_output_name(server_ip, server_port, model_name,
model_version, lang_text):
try:
server_addr = server_ip + ':' + server_port
input_metas, output_metas = _http_manager.get_model_meta(
server_addr, model_name, model_version)
except Exception as e:
return {status_text: str(e)}
results = {
component: None
for component in all_input_output_components
}
results[component_format_column] = gr.update(visible=True)
for input_accordio in input_accordions:
results[input_accordio] = gr.update(visible=False)
for output_accordio in output_accordions:
results[output_accordio] = gr.update(visible=False)
results[status_text] = 'Get model inputs and outputs successfully.'
for i, input_meta in enumerate(input_metas):
results[input_accordions[i]] = gr.update(visible=True)
results[input_name_texts[i]] = input_meta['name']
for i, output_meta in enumerate(output_metas):
results[output_accordions[i]] = gr.update(visible=True)
results[output_name_texts[i]] = output_meta['name']
return results
def component_inference(*args):
server_ip = args[0]
http_port = args[1]
metric_port = args[2]
model_name = args[3]
model_version = args[4]
names = args[5:5 + len(input_name_texts)]
images = args[5 + len(input_name_texts):5 + len(input_name_texts) +
len(input_images)]
texts = args[5 + len(input_name_texts) + len(input_images):5 +
len(input_name_texts) + len(input_images) +
len(input_texts)]
task_type = args[-1]
server_addr = server_ip + ':' + http_port
if server_ip and http_port and model_name and model_version:
inputs = {}
for i, input_name in enumerate(names):
if input_name:
if images[i] is not None:
inputs[input_name] = np.array([images[i]])
if texts[i]:
inputs[input_name] = np.array(
[[texts[i].encode('utf-8')]], dtype=np.object_)
try:
infer_results = _http_manager.infer(
server_addr, model_name, model_version, inputs)
results = {status_text: 'Inference successfully.'}
for i, (output_name,
data) in enumerate(infer_results.items()):
results[output_name_texts[i]] = output_name
results[output_texts[i]] = str(data)
if task_type != 'unspecified':
try:
results[output_images[i]] = supported_tasks[
task_type](images[0], data)
except Exception:
results[output_images[i]] = None
if metric_port:
html_table = get_metric_data(server_ip, metric_port,
'zh')
results[output_html_table] = html_table
return results
except Exception as e:
return {status_text: 'Error: {}'.format(e)}
else:
return {
status_text:
'Please input server addr, model name and model version.'
}
def raw_inference(*args):
server_ip = args[0]
http_port = args[1]
metric_port = args[2]
model_name = args[3]
model_version = args[4]
payload_text = args[5]
server_addr = server_ip + ':' + http_port
try:
result = _http_manager.raw_infer(server_addr, model_name,
model_version, payload_text)
results = {
status_text: 'Get response from server',
output_raw_text: result
}
if server_ip and metric_port:
html_table = get_metric_data(server_ip, metric_port, 'zh')
results[output_html_table] = html_table
return results
except Exception as e:
return {status_text: 'Error: {}'.format(e)}
def update_metric(server_ip, metrics_port, lang_text):
if server_ip and metrics_port:
try:
html_table = get_metric_data(server_ip, metrics_port, 'zh')
return {
output_html_table: html_table,
status_text: "Update metrics successfully."
}
except Exception as e:
return {status_text: 'Error: {}'.format(e)}
else:
return {
status_text: 'Please input server ip and metrics_port.'
}
check_button.click(
fn=get_input_output_name,
inputs=[
server_addr_text, server_http_port_text, model_name_text,
model_version_text, lang_text
],
outputs=[
*all_input_output_components, check_button,
component_format_column, status_text
])
component_submit_button.click(
fn=component_inference,
inputs=[
server_addr_text, server_http_port_text,
server_metric_port_text, model_name_text, model_version_text,
*input_name_texts, *input_images, *input_texts, task_radio
],
outputs=[
*output_name_texts, *output_images, *output_texts, status_text,
output_html_table
])
raw_submit_button.click(
fn=raw_inference,
inputs=[
server_addr_text, server_http_port_text,
server_metric_port_text, model_name_text, model_version_text,
raw_payload_text
],
outputs=[output_raw_text, status_text, output_html_table])
update_metric_button.click(
fn=update_metric,
inputs=[server_addr_text, server_metric_port_text, lang_text],
outputs=[output_html_table, status_text])
return block
def create_gradio_client_app_en(): # noqa:C901
css = """
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: white;
border-color: black;
background: black;
}
input[type='range'] {
accent-color: black;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
#gallery {
min-height: 22rem;
margin-bottom: 15px;
margin-left: auto;
margin-right: auto;
border-bottom-right-radius: .5rem !important;
border-bottom-left-radius: .5rem !important;
}
#gallery>div>.h-full {
min-height: 20rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) \
var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.prompt h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
"""
block = gr.Blocks(css=css)
with block:
gr.HTML("""
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
<div
style="
display: inline-flex;
gap: 0.8rem;
font-size: 1.75rem;
justify-content: center;
"
>
<h1>
FastDeploy Client
</h1>
</div>
<p font-size: 94%">
The client is used for creating requests to fastdeploy server.
</p>
</div>
""")
with gr.Group():
with gr.Box():
with gr.Column():
with gr.Row():
server_addr_text = gr.Textbox(
label="server ip",
show_label=True,
max_lines=1,
placeholder="localhost",
)
server_http_port_text = gr.Textbox(
label="server port",
show_label=True,
max_lines=1,
placeholder="8000",
)
server_metric_port_text = gr.Textbox(
label="metrics port",
show_label=True,
max_lines=1,
placeholder="8002",
)
with gr.Row():
model_name_text = gr.Textbox(
label="model name",
show_label=True,
max_lines=1,
placeholder="yolov5",
)
model_version_text = gr.Textbox(
label="model version",
show_label=True,
max_lines=1,
placeholder="1",
)
with gr.Box():
with gr.Tab("Component form"):
check_button = gr.Button("get model input and output")
component_format_column = gr.Column(visible=False)
with component_format_column:
task_radio = gr.Radio(
choices=list(supported_tasks.keys()),
value='unspecified',
label='task type',
visible=True)
gr.Markdown(
"Choose text or image component to input according to data type"
)
with gr.Row():
with gr.Column():
gr.Markdown("Inputs")
input_accordions = []
input_name_texts = []
input_images = []
input_texts = []
for i in range(6):
accordion = gr.Accordion(
"variable {}".format(i),
open=True,
visible=False)
with accordion:
input_name_text = gr.Textbox(
label="variable name",
interactive=False)
input_image = gr.Image(type='numpy')
input_text = gr.Textbox(
label="text", max_lines=1000)
input_accordions.append(accordion)
input_name_texts.append(input_name_text)
input_images.append(input_image)
input_texts.append(input_text)
with gr.Column():
gr.Markdown("Outputs")
output_accordions = []
output_name_texts = []
output_images = []
output_texts = []
for i in range(6):
accordion = gr.Accordion(
"variable {}".format(i),
open=True,
visible=False)
with accordion:
output_name_text = gr.Textbox(
label="variable name",
interactive=False)
output_text = gr.Textbox(
label="text",
interactive=False,
show_label=True)
output_image = gr.Image(
interactive=False)
output_accordions.append(accordion)
output_name_texts.append(output_name_text)
output_images.append(output_image)
output_texts.append(output_text)
component_submit_button = gr.Button("submit request")
with gr.Tab("Original form"):
gr.Markdown("Request")
raw_payload_text = gr.Textbox(
label="request payload", max_lines=10000)
with gr.Column():
gr.Markdown("Response")
output_raw_text = gr.Textbox(
label="raw response data", interactive=False)
raw_submit_button = gr.Button("submit request")
with gr.Box():
with gr.Column():
gr.Markdown(
"Metrics（update automatically when submit request，or click update metrics button manually）"
)
output_html_table = gr.HTML(
label="metrics",
interactive=False,
show_label=False,
value=metrics_table_head_en.format('', ''))
update_metric_button = gr.Button("update metrics")
status_text = gr.Textbox(
label="status",
show_label=True,
max_lines=1,
interactive=False)
lang_text = gr.Textbox(
label="lang",
show_label=False,
value='en',
max_lines=1,
visible=False
) # This text box is only used for divide zh and en page
all_input_output_components = input_accordions + input_name_texts + input_images + \
input_texts + output_accordions + output_name_texts + output_images + output_texts
def get_input_output_name(server_ip, server_port, model_name,
model_version):
model_version, lang_text):
try:
server_addr = server_ip + ':' + server_port
input_metas, output_metas = _http_manager.get_model_meta(
......@@ -273,12 +663,11 @@ def create_gradio_client_app(): # noqa:C901
for component in all_input_output_components
}
results[component_format_column] = gr.update(visible=True)
# results[check_button] = gr.update(visible=False)
for input_accordio in input_accordions:
results[input_accordio] = gr.update(visible=False)
for output_accordio in output_accordions:
results[output_accordio] = gr.update(visible=False)
results[status_text] = 'GetInputOutputName Successful'
results[status_text] = 'Get model inputs and outputs successfully.'
for i, input_meta in enumerate(input_metas):
results[input_accordions[i]] = gr.update(visible=True)
results[input_name_texts[i]] = input_meta['name']
......@@ -313,7 +702,7 @@ def create_gradio_client_app(): # noqa:C901
try:
infer_results = _http_manager.infer(
server_addr, model_name, model_version, inputs)
results = {status_text: 'Inference Successful'}
results = {status_text: 'Inference successfully.'}
for i, (output_name,
data) in enumerate(infer_results.items()):
results[output_name_texts[i]] = output_name
......@@ -325,7 +714,8 @@ def create_gradio_client_app(): # noqa:C901
except Exception:
results[output_images[i]] = None
if metric_port:
html_table = get_metric_data(server_ip, metric_port)
html_table = get_metric_data(server_ip, metric_port,
'en')
results[output_html_table] = html_table
return results
except Exception as e:
......@@ -352,19 +742,19 @@ def create_gradio_client_app(): # noqa:C901
output_raw_text: result
}
if server_ip and metric_port:
html_table = get_metric_data(server_ip, metric_port)
html_table = get_metric_data(server_ip, metric_port, 'en')
results[output_html_table] = html_table
return results
except Exception as e:
return {status_text: 'Error: {}'.format(e)}
def update_metric(server_ip, metrics_port):
def update_metric(server_ip, metrics_port, lang_text):
if server_ip and metrics_port:
try:
html_table = get_metric_data(server_ip, metrics_port)
html_table = get_metric_data(server_ip, metrics_port, 'en')
return {
output_html_table: html_table,
status_text: "Successfully update metrics."
status_text: "Update metrics successfully."
}
except Exception as e:
return {status_text: 'Error: {}'.format(e)}
......@@ -377,7 +767,7 @@ def create_gradio_client_app(): # noqa:C901
fn=get_input_output_name,
inputs=[
server_addr_text, server_http_port_text, model_name_text,
model_version_text
model_version_text, lang_text
],
outputs=[
*all_input_output_components, check_button,
......@@ -404,6 +794,6 @@ def create_gradio_client_app(): # noqa:C901
outputs=[output_raw_text, status_text, output_html_table])
update_metric_button.click(
fn=update_metric,
inputs=[server_addr_text, server_metric_port_text],
inputs=[server_addr_text, server_metric_port_text, lang_text],
outputs=[output_html_table, status_text])
return block
visualdl/component/inference/fastdeploy_client/http_client_manager.py
浏览文件 @ 9583bf7c
......@@ -19,7 +19,6 @@ import numpy as np
import requests
import tritonclient.http as httpclient
from attrdict import AttrDict
from tritonclient.utils import InferenceServerException
def convert_http_metadata_config(metadata):
......@@ -118,8 +117,63 @@ table, th {{
</div>
"""
metrics_table_head_en = """
<style>
table, th {{
border:0.1px solid black;
}}
</style>
<div>
<table style="width:100%">
<tr>
<th rowspan="2">Model name</th>
<th colspan="4">Execution metric</th>
<th colspan="5">Delay metric</th>
</tr>
<tr>
<th>inference request success</th>
<th>inference request failure</th>
<th>inference count</th>
<th>inference exec count</th>
<th>inference request duration(ms)</th>
<th>inference queue duration(ms)</th>
<th>inference comput input duration(ms)</th>
<th>inference compute infer duration
(ms)</th>
<th>inference compute output duration(ms)</th>
</tr>
{}
</table>
</div>
<br>
<br>
<br>
<br>
<br>
<div>
<table style="width:100%">
<tr>
<th rowspan="2">GPU</th>
<th colspan="4">Performance metric</th>
<th colspan="2">Memory</th>
</tr>
<tr>
<th>utilization(%)</th>
<th>power usage(W)</th>
<th>power limit(W)</th>
<th>energy consumption(W)</th>
<th>total(GB)</th>
<th>used(GB)</th>
</tr>
{}
</table>
</div>
"""
def get_metric_data(server_addr, metric_port): # noqa:C901
def get_metric_data(server_addr, metric_port, lang='zh'): # noqa:C901
'''
Get metrics data from fastdeploy server, and transform it into html table.
Args:
......@@ -235,6 +289,8 @@ def get_metric_data(server_addr, metric_port): # noqa:C901
for item in data]) + "</tr>"
for data in gpu_data_list
])
if lang == 'en':
return metrics_table_head_en.format(model_data, gpu_data)
return metrics_table_head.format(model_data, gpu_data)
......@@ -294,7 +350,7 @@ class HttpClientManager:
try:
model_metadata = fastdeploy_client.get_model_metadata(
model_name=model_name, model_version=model_version)
except InferenceServerException as e:
except Exception as e:
raise RuntimeError("Failed to retrieve the metadata: " + str(e))
model_metadata = convert_http_metadata_config(model_metadata)
......
visualdl/component/inference/fastdeploy_server.py
浏览文件 @ 9583bf7c
......@@ -25,6 +25,7 @@ from pathlib import Path
import requests
from .fastdeploy_client.client_app import create_gradio_client_app
from .fastdeploy_client.client_app import create_gradio_client_app_en
from .fastdeploy_lib import analyse_config
from .fastdeploy_lib import check_process_zombie
from .fastdeploy_lib import copy_config_file_to_default_config
......@@ -53,7 +54,8 @@ class FastDeployServerApi(object):
self.root_dir = Path(os.getcwd())
self.opened_servers = {
} # Use to store the opened server process pid and process itself
self.client_port = None
self.client_port = None # Chinese version
self.client_en_port = None # English version
@result()
def get_directory(self, cur_dir):
......@@ -351,34 +353,43 @@ class FastDeployServerApi(object):
version_filenames_dict_for_frontend)
return version_info_for_frontend
def create_fastdeploy_client(self):
if self.client_port is None:
def get_free_tcp_port():
tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# tcp.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1)
tcp.bind(('localhost', 0))
addr, port = tcp.getsockname()
tcp.close()
return port
self.client_port = get_free_tcp_port()
app = create_gradio_client_app()
thread = Process(
target=app.launch, kwargs={'server_port': self.client_port})
thread.start()
def check_alive():
while True:
try:
requests.get('http://localhost:{}/'.format(
self.client_port))
break
except Exception:
time.sleep(1)
check_alive()
return self.client_port
def create_fastdeploy_client(self, lang='zh'):
def get_free_tcp_port():
tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# tcp.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1)
tcp.bind(('localhost', 0))
addr, port = tcp.getsockname()
tcp.close()
return port
def check_alive(client_port):
while True:
try:
requests.get('http://localhost:{}/'.format(client_port))
break
except Exception:
time.sleep(1)
if lang == 'en':
if self.client_en_port is None:
self.client_en_port = get_free_tcp_port()
app = create_gradio_client_app_en()
thread = Process(
target=app.launch,
kwargs={'server_port': self.client_en_port})
thread.start()
check_alive(self.client_en_port)
return self.client_en_port
else:
if self.client_port is None:
self.client_port = get_free_tcp_port()
app = create_gradio_client_app()
thread = Process(
target=app.launch,
kwargs={'server_port': self.client_port})
thread.start()
check_alive(self.client_port)
return self.client_port
def _poll_zombie_process(self):
# check if there are servers killed by other vdl app instance and become zoombie
......@@ -410,7 +421,7 @@ def create_fastdeploy_api_call():
'start_server': (api.start_server, ['config']),
'stop_server': (api.stop_server, ['server_id']),
'get_server_output': (api.get_server_output, ['server_id', 'length']),
'create_fastdeploy_client': (api.create_fastdeploy_client, []),
'create_fastdeploy_client': (api.create_fastdeploy_client, ['lang']),
'get_server_list': (api.get_server_list, []),
'get_server_metric': (api.get_server_metric, ['server_id']),
'get_server_config': (api.get_server_config, ['server_id']),
......
visualdl/server/app.py
浏览文件 @ 9583bf7c
......@@ -181,6 +181,7 @@ def create_app(args): # noqa: C901
error_msg = '{}'.format(e)
return make_response(error_msg)
args = urllib.parse.urlencode(request_args)
if args:
return redirect(
api_path + "/fastdeploy/fastdeploy_client/app?{}".format(args),
......@@ -201,14 +202,30 @@ def create_app(args): # noqa: C901
Returns:
Any thing from gradio server.
'''
lang = 'zh'
if request.method == 'POST':
if request.mimetype == 'application/json':
request_args = request.json
else:
request_args = request.form.to_dict()
if 'data' in request_args:
lang = request_args['data'][-1]
request_args['lang'] = lang
elif 'lang' in request_args:
lang = request_args['lang']
port = fastdeploy_api_call('create_fastdeploy_client',
request.form)
request_args = request.form
request_args)
else:
request_args = request.args.to_dict()
if 'data' in request_args:
lang = request_args['data'][-1]
request_args['lang'] = lang
elif 'lang' in request_args:
lang = request_args['lang']
port = fastdeploy_api_call('create_fastdeploy_client',
request.args)
request_args = request.args
request_args)
if path == 'app':
proxy_url = request.url.replace(
request.host_url.rstrip('/') + api_path +
......@@ -239,38 +256,82 @@ def create_app(args): # noqa: C901
model_name = start_args.get('default_model_name', '')
content = content.decode()
try:
default_server_addr = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("服务ip", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_server_addr = default_server_addr.replace(
'"value": ""', '"value": "localhost"')
default_http_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("推理服务端口", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_http_port = default_http_port.replace(
'"value": ""', '"value": "{}"'.format(http_port))
default_metrics_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("性能服务端口", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_metrics_port = default_metrics_port.replace(
'"value": ""', '"value": "{}"'.format(metrics_port))
default_model_name = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("模型名称", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_model_name = default_model_name.replace(
'"value": ""', '"value": "{}"'.format(model_name))
default_model_version = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("模型版本", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_model_version = default_model_version.replace(
'"value": ""', '"value": "{}"'.format('1'))
content = content.replace(default_server_addr,
cur_server_addr)
if request_args.get('lang', 'zh') == 'en':
default_server_addr = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"server ip", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_server_addr = default_server_addr.replace(
'"value": ""', '"value": "localhost"')
default_http_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"server port", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_http_port = default_http_port.replace(
'"value": ""', '"value": "{}"'.format(http_port))
default_metrics_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"metrics port", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_metrics_port = default_metrics_port.replace(
'"value": ""',
'"value": "{}"'.format(metrics_port))
default_model_name = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"model name", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_model_name = default_model_name.replace(
'"value": ""', '"value": "{}"'.format(model_name))
default_model_version = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("model version",
ensure_ascii=True).replace(
'\\', '\\\\')),
content).group(0)
cur_model_version = default_model_version.replace(
'"value": ""', '"value": "{}"'.format('1'))
content = content.replace(default_server_addr,
cur_server_addr)
else:
default_server_addr = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("服务ip", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_server_addr = default_server_addr.replace(
'"value": ""', '"value": "localhost"')
default_http_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"推理服务端口", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_http_port = default_http_port.replace(
'"value": ""', '"value": "{}"'.format(http_port))
default_metrics_port = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps(
"性能服务端口", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_metrics_port = default_metrics_port.replace(
'"value": ""',
'"value": "{}"'.format(metrics_port))
default_model_name = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("模型名称", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_model_name = default_model_name.replace(
'"value": ""', '"value": "{}"'.format(model_name))
default_model_version = re.search(
'"label": {}.*?"value": "".*?}}'.format(
json.dumps("模型版本", ensure_ascii=True).replace(
'\\', '\\\\')), content).group(0)
cur_model_version = default_model_version.replace(
'"value": ""', '"value": "{}"'.format('1'))
content = content.replace(default_server_addr,
cur_server_addr)
if http_port:
content = content.replace(default_http_port,
cur_http_port)
......
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