def get_model(module, serve_model=False):
import_name = prepare_import(module)
try:
module = importlib.import_module(import_name)
except Exception as ex:
logger.error(traceback.format_exc())
return None
serve_models = [
v for v in module.__dict__.values() if isinstance(v, ServeModel)
]
if len(serve_models) > 0 and serve_model:
serve_model = serve_models[0]
return serve_model
apps = [v for v in module.__dict__.values() if isinstance(v, MLServer)]
if len(apps) > 0:
return apps[0]
if len(serve_models) > 0:
return serve_models[0]
# Could not find model
logger.debug("Could not find ServeModel")
serve_models = [
v for v in module.__dict__.values() if not isinstance(v, type)
]
if len(serve_models) > 0 and serve_model:
serve_model = ServeModel(serve_models[-1])
return serve_model
logger.error(
"Could not find any instance to serve. So please check again the mlconfig.yaml or server file!"
)
return None
def upload_file(self,
filename,
key,
bucket_name=None,
overwrite=False,
encrypt=False,
acl=None,
use_basename=False):
"""
Uploads a local file to S3.
Args:
filename: `str`. name of the file to upload.
key: `str`. S3 key that will point to the file.
bucket_name: `str`. Name of the bucket in which to store the file.
overwrite: `bool`. A flag to decide whether or not to overwrite the key
if it already exists. If replace is False and the key exists, an
error will be raised.
encrypt: `bool`. If True, the file will be encrypted on the server-side
by S3 and will be stored in an encrypted form while at rest in S3.
acl: `str`. ACL to use for uploading, e.g. "public-read".
use_basename: `bool`. whether or not to use the basename of the filename.
"""
if not bucket_name:
bucket_name = self.bucket
if bucket_name is None:
raise MlChainError("bucket can't be None",
code="S000",
status_code=500)
if use_basename:
key = os.path.join(key, os.path.basename(filename))
try:
self.client.upload_file(filename, bucket_name, key)
except Exception as ex:
logger.error(str(ex))
raise MlChainError(str(ex), code="S005", status_code=500)
def download_cv2(self, key, bucket_name=None):
"""
Download a file from S3.
Args:
key: `str`. S3 key that will point to the file.
local_path: `str`. the path to download to.
bucket_name: `str`. Name of the bucket in which to store the file.
use_basename: `bool`. whether or not to use the basename of the key.
"""
if not bucket_name:
bucket_name = self.bucket
if bucket_name is None:
raise MlChainError("bucket can't be None",
code="S000",
status_code=500)
try:
buffer = BytesIO()
self.client.download_fileobj(bucket_name, key, buffer)
cv2 = import_cv2()
return cv2.imdecode(
np.asarray(bytearray(buffer.getvalue()), dtype="uint8"),
cv2.IMREAD_COLOR)
except Exception as ex:
logger.error(str(ex))
raise MlChainError(str(ex), code="S003", status_code=500)
def get_model(module, serve_model=False, queue=None, trace=False, name=None):
import_name = prepare_import(module)
module = importlib.import_module(import_name)
serve_models = [
v for v in module.__dict__.values() if isinstance(v, ServeModel)
]
if len(serve_models) > 0 and serve_model:
serve_model = serve_models[0]
if queue == 'rabbit':
logger.debug('load rabbit {0}'.format(serve_model))
from mlchain.queue.rabbit_queue import RabbitQueue
if not isinstance(serve_model, RabbitQueue):
serve_model = RabbitQueue(serve_model,
module_name=name,
trace=trace)
serve_model.run(threading=True)
elif queue == 'redis':
logger.debug('load redis {0}'.format(serve_model))
from mlchain.queue.redis_queue import RedisQueue
if not isinstance(serve_model, RedisQueue):
serve_model = RedisQueue(serve_model,
module_name=name,
trace=trace)
serve_model.run(threading=True)
return serve_model
apps = [v for v in module.__dict__.values() if isinstance(v, MLServer)]
if len(apps) > 0:
return apps[0]
if len(serve_models) > 0:
return serve_models[0]
# Could not find model
logger.debug("Could not find ServeModel")
serve_models = [
v for v in module.__dict__.values() if not isinstance(v, type)
]
if len(serve_models) > 0 and serve_model:
serve_model = ServeModel(serve_models[-1])
if queue == 'rabbit':
logger.debug('Load rabbit {0}'.format(serve_model))
from mlchain.queue.rabbit_queue import RabbitQueue
if not isinstance(serve_model, RabbitQueue):
serve_model = RabbitQueue(serve_model,
module_name=name,
trace=trace)
serve_model.run(threading=True)
elif queue == 'redis':
logger.debug('load redis {0}'.format(serve_model))
from mlchain.queue.redis_queue import RedisQueue
if not isinstance(serve_model, RedisQueue):
serve_model = RedisQueue(serve_model,
module_name=name,
trace=trace)
serve_model.run(threading=True)
return serve_model
logger.error("Could not find any instance to serve")
return None
def register_autofrontend(model_id,
serve_model,
version='latest',
endpoint=None):
mlchain_management = os.getenv('MLCHAIN_URL', None)
if endpoint is None:
endpoint = ''
autofrontend_template = AutofrontendConfig()
if serve_model.config is not None:
out_configs = serve_model.config
else:
out_configs = {}
for name, func in serve_model.get_all_func().items():
if name in out_configs:
out_config = out_configs[name]
if 'config' in out_config:
config = out_config['config']
else:
config = None
else:
config = None
autofrontend_template.add_endpoint(func,
f'{endpoint}/call/{name}',
output_config=config)
if os.path.exists("Readme.md"):
description = open("Readme.md", encoding='utf-8').read()
else:
description = ""
if os.path.exists("changelog.md"):
changelog = open("changelog.md", encoding='utf-8').read()
else:
changelog = ""
if mlchain_management and model_id is not None:
config_version = {
"model_id": model_id,
"version": version,
"input_config": autofrontend_template.input_config,
"output_config": autofrontend_template.output_config,
'endpoint': endpoint,
'readme': description,
'changelog': changelog
}
try:
import requests
res = requests.post(f'{mlchain_management}/version/create',
json=config_version)
logger.info(str(res.json()))
except Exception as ex:
logger.error(ex)
def download_bytes(self, key, bucket_name=None, use_basename=True):
"""
Download a file from S3.
Args:
key: `str`. S3 key that will point to the file.
local_path: `str`. the path to download to.
bucket_name: `str`. Name of the bucket in which to store the file.
use_basename: `bool`. whether or not to use the basename of the key.
"""
if not bucket_name:
bucket_name = self.bucket
if bucket_name is None:
raise MlChainError("bucket can't be None",
code="S000",
status_code=500)
try:
buffer = BytesIO()
self.client.download_fileobj(bucket_name, key, buffer)
return buffer.getvalue()
except Exception as ex:
logger.error(str(ex))
raise MlChainError(str(ex), code="S002", status_code=500)
def download_dir(self, prefix, dir_path, bucket_name=None):
bucket_name = bucket_name or self.bucket
if bucket_name is None:
raise MlChainError("bucket can't be None",
code="S000",
status_code=500)
if prefix.endswith('/'):
prefix = prefix[:-1]
if len(prefix) > 0:
prefix = '{0}/'.format(prefix)
try:
results = self.list(bucket_name=bucket_name, prefix=prefix)
for file in results['keys']:
self.download_file(prefix + file,
os.path.join(dir_path, file),
bucket_name=bucket_name)
for dir in results['prefixes']:
self.download_dir(prefix + dir,
os.path.join(dir_path, dir),
bucket_name=bucket_name)
except Exception as ex:
logger.error(str(ex))
raise MlChainError(str(ex), code="S004", status_code=500)
def download_file(self,
key,
local_path,
bucket_name=None,
use_basename=False):
"""
Download a file from S3.
Args:
key: `str`. S3 key that will point to the file.
local_path: `str`. the path to download to.
bucket_name: `str`. Name of the bucket in which to store the file.
use_basename: `bool`. whether or not to use the basename of the key.
"""
if not bucket_name:
bucket_name = self.bucket
if bucket_name is None:
raise MlChainError("bucket can't be None",
code="S000",
status_code=500)
local_path = os.path.abspath(local_path)
if use_basename:
local_path = os.path.join(local_path, os.path.basename(key))
dir_name = os.path.dirname(local_path)
if not os.path.exists(dir_name):
os.makedirs(dir_name)
try:
content_length = self.client.head_object(Bucket=bucket_name,
Key=key)["ContentLength"]
progress = ProgressPercentage(key, content_length)
self.client.download_file(bucket_name,
key,
local_path,
Callback=progress)
return True
except Exception as ex:
logger.error(str(ex))
raise MlChainError(str(ex), code="S001", status_code=500)