from clipper_admin import ClipperConnection, DockerContainerManager clipper_conn = ClipperConnection(DockerContainerManager()) clipper_conn.connect() clipper_conn.get_clipper_logs()
from clipper_admin import ClipperConnection, DockerContainerManager from clipper_admin.deployers.pytorch import deploy_pytorch_model from torch import nn clipper_conn = ClipperConnection(DockerContainerManager()) clipper_conn.connect() log_files = clipper_conn.get_clipper_logs() logs = [open(filename).read() for filename in log_files] # for log in logs: # print(log) print(log_files)
import sys
sys.path.insert(0,
'/Users/xunzhang/Desktop/2018/github/clipper/clipper_admin/')
import tensorflow as tf
from clipper_admin import ClipperConnection, DockerContainerManager
from clipper_admin.deployers.tensorflow import deploy_tensorflow_model
cur_dir = os.path.dirname(os.path.abspath(__file__))
app_name = "tf-lr-app"
model_name = "tf-lr-model"
if __name__ == "__main__":
clipper_conn = ClipperConnection(DockerContainerManager())
clipper_conn.stop_all()
clipper_conn.start_clipper()
clipper_conn.register_application(name=app_name,
input_type="integers",
default_output="rabbit",
slo_micros=100000)
print(os.path.abspath("data"))
clipper_conn.build_and_deploy_model(
name=model_name,
version=1,
input_type="integers",
model_data_path=os.path.abspath("data"),
base_image="xunzhang/tf_lr_container:latest",
num_replicas=1)
clipper_conn.link_model_to_app(app_name, model_name)
print(clipper_conn.get_clipper_logs())
