def publish_model(self, args):
"""发布模型到稳定版"""
message = args.message
project = get_active_project()
config_path = self.get_model_config_path()
config = get_config_parser(config_path)
section_name = DEFAULT_MODEL_SECTION
model_id = config_get(config.get, section_name, 'model_id')
oauth2_section = DEFAULT_OAUTH2_SECTION
token_section = DEFAULT_TOKEN_SECTION
config = read_config(project)
access_token = config_get(config.get, token_section, 'access_token')
endpoint = config_get(config.get, oauth2_section, 'endpoint')
api = API(access_token,
endpoint=endpoint,
timeout=DEFAULT_MODEL_TIMEOUT)
try:
result = api.publish_model(model_id, message)
except APIError as e:
output('[red]模型发布失败：[/red]')
output_json(e.result)
sys.exit(1)
output('[green]模型 {} 稳定版已成功发布。\n版本号：{}。[/green]'.format(
model_id, result['version']))
def run_model(self, args):
params = {}
if args.file:
filepath = args.file
if not exists(filepath):
output('文件不存在：{}'.format(filepath))
sys.exit(1)
if isdir(filepath):
output('存在文件夹：{}'.format(filepath))
sys.exit(1)
with open(filepath, 'r') as fp:
params = json.load(fp)
elif args.args:
params = dict(args.args)
draft = args.draft
test = args.test
project = get_active_project()
config_path = self.get_model_config_path()
config = get_config_parser(config_path)
section_name = DEFAULT_MODEL_SECTION
model_id = config_get(config.get, section_name, 'model_id')
oauth2_section = DEFAULT_OAUTH2_SECTION
token_section = DEFAULT_TOKEN_SECTION
config = read_config(project)
access_token = config_get(config.get, token_section, 'access_token')
endpoint = config_get(config.get, oauth2_section, 'endpoint')
api = API(access_token,
endpoint=endpoint,
timeout=DEFAULT_MODEL_TIMEOUT)
try:
if draft is True:
result = api.invoke_draft_model(model_id, **params)
elif test is True:
port = args.port
api = API(access_token,
endpoint='{}:{}'.format(TEST_SERVER_ENDPOINT, port),
timeout=DEFAULT_MODEL_TIMEOUT)
result = api.invoke_model(model_id, **params)
else:
result = api.invoke_model(model_id, **params)
except APIError as e:
output('[red]模型运行失败：[/red]')
output_json(e.result)
sys.exit(1)
output('[green]模型返回值：[/green]')
output_json(result.json())
def deploy_model(self, args):
"""部署模型"""
ignore_source = args.ignore_source
home = get_home()
project = get_active_project()
config_path = self.get_model_config_path()
config = get_config_parser(config_path)
section_name = DEFAULT_MODEL_SECTION
model_id = config_get(config.get, section_name, 'model_id')
timestr = datetime.now().strftime('%Y%m%d%H%M%S%f')
randstr = uuid4().hex
zip_filename = '{}.{}.{}.zip'.format(model_id, timestr, randstr)
params = {}
params['runtime'] = config_get(config.get, section_name, 'runtime')
params['memory_size'] = config_get(config.getint, section_name,
'memory_size')
params['timeout'] = config_get(config.getint, section_name, 'timeout')
oauth2_section = DEFAULT_OAUTH2_SECTION
token_section = DEFAULT_TOKEN_SECTION
config = read_config(project)
access_token = config_get(config.get, token_section, 'access_token')
endpoint = config_get(config.get, oauth2_section, 'endpoint')
api = API(access_token,
endpoint=endpoint,
timeout=DEFAULT_MODEL_TIMEOUT)
object_name = None
if not ignore_source:
ignore_path = join(home, BGE_IGNORE_FILE)
if not exists(ignore_path):
output('未发现 .bgeignore 文件，初始化 {} ...'.format(ignore_path))
open(ignore_path, 'w').write(BGEIGNORE_TEMPLATE)
minify_path = join(home, BGE_MINIFY_FILE)
if not exists(minify_path):
output('未发现 .bgeminify 文件，初始化 {} ...'.format(minify_path))
open(minify_path, 'w').write(BGEMINIFY_TEMPLATE)
output('开始打包模型源码...')
zip_tmpdir = join(home, '.bge', 'tmp')
if not exists(zip_tmpdir):
os.makedirs(zip_tmpdir)
with tempfile.NamedTemporaryFile(suffix='.zip',
prefix='model-',
dir=zip_tmpdir,
delete=False) as tmp:
with zipfile.ZipFile(tmp.name, 'w', ZIP_COMPRESSION) as zf:
self._zip_codedir(home, zf)
tmp.flush()
tmp.seek(0, 2)
size = tmp.tell()
tmp.seek(0)
human_size = human_byte(size)
if size > 100 * 1024 * 1024:
output('打包后 zip 文件大小为 {}，最大限制 100MB'.format(human_size))
exit(1)
output('打包成功：{}'.format(tmp.name))
output('文件大小：{}'.format(human_size))
output('开始上传模型源码...')
try:
object_name = api.upload(zip_filename, tmp)
except APIError as e:
output('[red]上传模型源码失败：[/red]')
output_json(e.result)
sys.exit(1)
output('[green]上传成功[green]')
with console.status('模型部署中...', spinner='earth'):
try:
result = api.deploy_model(model_id,
object_name=object_name,
**params)
except APIError as e:
output('[red]部署模型失败：[/red]')
output_json(e.result)
sys.exit(1)
task_id = result.task_id
output('模型部署任务：{}'.format(task_id))
task_path = join(home, '.bge', 'task_id')
with open(task_path, 'w') as f:
f.write(task_id)
output('模型部署任务返回结果：')
progress = self._wait_model_task(api, task_id, task_path)
if 'SUCCESS' == progress:
output('[green]模型 {} 灰度部署成功。'.format(model_id))
elif 'FAILURE' == progress:
output('[red]模型 {} 灰度部署失败。任务结果：{}'.format(model_id, result))
elif 'REVOKED' == progress:
output('[white]模型 {} 灰度部署任务已被撤销。'.format(model_id))