def __deploy_model(self):
service_name = self.__args.service_name
model = Model(self.__ws, self.__args.model_name)
explainer_model = Model(self.__ws, self.__args.explainer_model_name)
myenv = Environment.from_conda_specification(
name=self.__config.get('DEPLOY', 'ENV_NAME'),
file_path=self.__config.get('DEPLOY', 'ENV_FILE_PATH'))
inference_config = InferenceConfig(
entry_script=self.__config.get('DEPLOY', 'SCORE_PATH'),
environment=myenv,
source_directory=self.__config.get('DEPLOY',
'DEPENDENCIES_DIRECTORY'))
if not self.__args.update_deployment:
deployment_config = AciWebservice.deploy_configuration(
cpu_cores=self.__config.getint('DEPLOY', 'ACI_CPU'),
memory_gb=self.__config.getint('DEPLOY', 'ACI_MEM'),
collect_model_data=True,
enable_app_insights=True)
service = Model.deploy(self.__ws, service_name,
[model, explainer_model], inference_config,
deployment_config)
else:
service = AciWebservice(self.__ws, service_name)
service.update(models=[model, explainer_model],
inference_config=inference_config)
service.wait_for_deployment(show_output=True)
print(service.state)
print(service.get_logs())
def main():
ws = Workspace.from_config()
conda = CondaDependencies()
conda.add_conda_package("python==3.5")
conda.add_pip_package("h5py==2.8.0")
conda.add_pip_package("html5lib==1.0.1")
conda.add_pip_package("keras==2.2.0")
conda.add_pip_package("Keras-Applications==1.0.2")
conda.add_pip_package("Keras-Preprocessing==1.0.1")
conda.add_pip_package("matplotlib==2.2.2")
conda.add_pip_package("numpy==1.14.5")
conda.add_pip_package("opencv-python==3.3.0.9")
conda.add_pip_package("pandas==0.23.3")
conda.add_pip_package("Pillow==5.2.0")
conda.add_pip_package("requests==2.19.1")
conda.add_pip_package("scikit-image==0.14.0")
conda.add_pip_package("scikit-learn==0.19.2")
conda.add_pip_package("scipy==1.1.0")
conda.add_pip_package("sklearn==0.0")
conda.add_pip_package("tensorflow==1.9.0")
conda.add_pip_package("urllib3==1.23")
conda.add_pip_package("azureml-sdk")
with open("environment.yml", "w") as f:
f.write(conda.serialize_to_string())
with open("environment.yml", "r") as f:
print(f.read())
image_config = ContainerImage.image_configuration(
execution_script="score.py",
runtime="python",
conda_file="environment.yml",
docker_file="Dockerfile",
dependencies=DEPENDENCIES)
webservices = ws.webservices(compute_type='ACI')
image = ContainerImage.create(name="ai-bootcamp",
models=[],
image_config=image_config,
workspace=ws)
image.wait_for_creation(show_output=True)
webservices_list = []
for key in webservices:
webservices_list.append(key)
service_name = webservices_list[0]
aciwebservice = AciWebservice(ws, service_name)
aciwebservice.update(image=image)
def deploy():
parser = argparse.ArgumentParser()
parser.add_argument("--model_name", required=True)
parser.add_argument("--model_path", required=True)
args = parser.parse_args()
print(f"model_name : {args.model_name}")
print(f"model_path: {args.model_path}")
run = Run.get_context()
ws = run.experiment.workspace
model = Model.register(workspace=ws,
model_path=args.model_path,
model_name=args.model_name)
print("Registered version {0} of model {1}".format(model.version,
model.name))
inference_config = InferenceConfig(
entry_script='score.py',
runtime='python',
conda_file='conda.yml',
extra_docker_file_steps='extra_docker_steps',
source_directory='server_files/')
deployment_config = AciWebservice.deploy_configuration(cpu_cores=0.1,
memory_gb=0.5,
auth_enabled=True)
try:
service = AciWebservice(ws, "testscorescriptauto")
service.update(models=[model])
print("EXISTING ENDPOINT FOUND: MODEL UPDATED")
except Exception:
Model.deploy(ws, "testscorescriptauto", [model], inference_config,
deployment_config)
print("NO EXISTING ENDPOINT FOUND: DEPLOYED MODEL TO NEW ENDPOINT")
print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep='\n')
# Loading Image
image_details = profiling_result["image_id"].split(":")
image = Image(workspace=ws, name=image_details[0], version=image_details[1])
# Deploying model on ACI
print("Deploying model on ACI")
try:
print("Trying to update existing ACI service")
dev_service = AciWebservice(workspace=ws, name=aci_settings["name"])
dev_service.update(image=image,
tags=deployment_settings["image"]["tags"],
properties=deployment_settings["image"]["properties"],
description=deployment_settings["image"]["description"],
auth_enabled=aci_settings["auth_enabled"],
ssl_enabled=aci_settings["ssl_enabled"],
ssl_cert_pem_file=aci_settings["ssl_cert_pem_file"],
ssl_key_pem_file=aci_settings["ssl_key_pem_file"],
ssl_cname=aci_settings["ssl_cname"],
enable_app_insights=aci_settings["enable_app_insights"])
print("Successfully updated existing ACI service")
except WebserviceException:
print("Failed to update ACI service... Creating new ACI instance")
aci_config = AciWebservice.deploy_configuration(
cpu_cores=profiling_result["cpu"],
memory_gb=profiling_result["memory"],
tags=deployment_settings["image"]["tags"],
properties=deployment_settings["image"]["properties"],
description=deployment_settings["image"]["description"],
location=aci_settings["location"],
auth_enabled=aci_settings["auth_enabled"],
