def test_e2e(Skil): model_path = './dummy.pb' skil_server = Skil() skil_server.upload_model(model_path) ws = WorkSpace(skil_server, 'jupyter_ws') experiment = Experiment(ws, 'test_exp') model = Model(model_path, experiment) model.add_evaluation(accuracy=0.93) deployment = Deployment(skil_server, 'test_deployment') model.deploy(deployment, start_server=False)
def test_experiment(Skil): skil_server = Skil() ws = WorkSpace(skil_server) experiment = Experiment(ws)
from skil import Skil, WorkSpace, Experiment, Model, Deployment from keras.datasets import mnist skil_server = Skil() work_space = WorkSpace(skil_server) experiment = Experiment(work_space) model = Model('model.pb', model_id='tf_model', experiment=experiment) deployment = Deployment(skil_server) service = model.deploy(deployment, input_names=['input'], output_names=['output']) (x_train, y_train), (x_test, y_test) = mnist.load_data() x_test = x_test.reshape(10000, 784) x_test = x_test.astype('float32') x_test /= 255 print(service.predict_single(x_test[0])) print(service.predict(x_test[:10]))
from skil import Skil, WorkSpace, Experiment, Model, Deployment import json # Initialize a new experiment in a workspace skil_server = Skil() ws = WorkSpace(skil_server) experiment = Experiment(ws) deployment = Deployment(skil_server, "keras_models") skil_models = [] for epoch in range(2): model_name = 'model_{epoch:02d}.hdf5'.format(epoch=epoch + 1) model = Model(model_name, id=epoch, experiment=experiment) model.deploy(start_server=False, deployment=deployment) skil_models.append(model) with open('history.json', 'r') as f: history = json.loads(f.read()) acc = history.get('val_acc') best_model = skil_models[acc.index(max(acc))] best_model.serve()
def test_work_space(Skil): skil_server = Skil() ws = WorkSpace(skil_server)
from skil import Skil, WorkSpace, Experiment, Model, Deployment import json # Initialize a new experiment in a workspace skil_server = Skil() work_space = WorkSpace(skil_server, name='mnist-workspace') experiment = Experiment(work_space, name='mnist-experiment') deployment = Deployment(skil_server, name='mnist-deployment') # Deploy all models with SKIL skil_services = [] for epoch in range(2): model_name = 'model_{epoch:02d}.hdf5'.format(epoch=epoch + 1) model = Model(model_name, model_id=epoch, experiment=experiment) service = model.deploy(start_server=False, deployment=deployment) skil_services.append(service) # Serve the best one with open('history.json', 'r') as f: history = json.loads(f.read()) acc = history.get('val_acc') best_service = skil_services[acc.index(max(acc))] best_service.start()
#import skil_client # #configuration = skil_client.Configuration() #configuration.host = 'http://52.15.103.124:9008' #configuration.api_key['authorization'] = 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJhdWQiOiJTa2lsVXNlciIsInN1YiI6IntcInVzZXJJZFwiOlwiYWRtaW5cIixcInVzZXJOYW1lXCI6XCJhZG1pblwiLFwicm9sZVwiOlwiYWRtaW5cIixcInNjb3BlXCI6XCJhZG1pblwifSIsImlzcyI6IlNraWxBdXRoTWFuYWdlciIsImV4cCI6MTU4NjgyODcxMCwiaWF0IjoxNTU1MjkyNzEwfQ.vXXpr0kk9H8nMbkcM8sPWPJwuws1GGvI8SWc76qKvUo' #api_instance = skil_client.DefaultApi(skil_client.ApiClient(configuration)) #api_response = api_instance.predictimage("yolo", "default", "yolomodel", image='input.jpg') # from skil import Skil skil_server = Skil(host='52.15.103.124', password='******') from skil import WorkSpace, Experiment, Model work_space = WorkSpace(skil_server, name="Object detection project") experiment = Experiment(work_space, name="YOLO") model = Model('yolo_v2.pb', name='yolo_model', experiment=experiment) # from skil import Deployment deployment = Deployment(skil_server) service = model.deploy(deployment, scale=1, input_names=['input'], output_names=['output']) # #from skil.utils.yolo import annotate_image #import cv2 # #image = cv2.imread('input.jpg') #detection = service.detect_objects(image)
'deployment_id': '' }, f) with open('.skil', 'r') as f: skil_conf = json.load(f) # Connect to SKIL and create an experiment for storing our model experiments. skil_server = Skil(host=skil_conf['host'], port=skil_conf['port'], user_id=skil_conf['username'], password=skil_conf['password']) work_space = None if skil_conf['workspace_id'] == '': work_space = WorkSpace(skil_server, name="Mnist Sample") skil_conf['workspace_id'] = work_space.id else: work_space = skil.get_workspace_by_id(None, skil_server, skil_conf['workspace_id']) experiment = None if skil_conf['experiment_id'] == '': experiment = Experiment(work_space, name='Simple MLP') skil_conf['experiment_id'] = experiment.id else: experiment = skil.get_experiment_by_id(work_space, skil_conf['experiment_id']) with open('.skil', 'w') as f: json.dump(skil_conf, f)