def main():
# create remote ebonite client from saved configuration
ebnt = Ebonite.from_config_file('client_config.json')
model = ebnt.get_model('add_one_model', 'my_task', 'my_project')
# run flask service with this model
run_test_model_server(model)
def main():
# create remote ebonite client. This client stores metadata in postgres and artifacts in s3
ebnt = Ebonite.custom_client(
'sqlalchemy',
's3',
meta_kwargs={
'db_uri': 'postgresql://*****:*****@localhost:5435/ebonite'
},
artifact_kwargs={
'endpoint': 'http://localhost:8008',
'bucket_name': 'ebonite'
})
# save client configuration for later use
ebnt.save_client_config('client_config.json')
# obtain Task
task = ebnt.get_or_create_task('my_project', 'my_task')
# remove model if it exists (for demo purposes)
if task.models.contains('add_one_model'):
model = task.models('add_one_model')
task.delete_model(model)
# create model from function add_one and numpy array as data sample
model = ebonite.create_model(add_one, np.array([0]), 'add_one_model')
# persist model
task.push_model(model)
def image_to_delete(ebnt: Ebonite, model, mock_env):
task = ebnt.get_or_create_task('Project', 'Task')
ebnt.meta_repo.create_environment(mock_env)
image = Image('image', BuildableMock(), id=None, task_id=task.id, params=Image.Params())
image.environment = mock_env
image.params.name = 'image'
image.bind_builder(mock_env.params.get_builder())
image = ebnt.meta_repo.create_image(image)
yield image
def main():
# create remote ebonite client from saved configuration
os.environ['S3_ACCESS_KEY'] = 'eboniteAccessKey'
os.environ['S3_SECRET_KEY'] = 'eboniteSecretKey'
ebnt = Ebonite.from_config_file('client_config.json')
model = ebnt.get_model('add_one_model', 'my_task', 'my_project')
# run flask service with this model
run_model_server(model)
def main():
# obtain trained model and data sample
reg, data = train_model()
ebnt = Ebonite.inmemory()
# this changes docker image builder behaviour to get ebonite from local installation instead of pip
with use_local_installation():
ebnt.create_instance_from_model('my_model', reg, data, task_name='my_task',
instance_name='magic-one-line-ebnt-service', run_instance=True, detach=False)
def main():
# create local ebonite client. This client stores metadata and artifacts on local fs.
ebnt = Ebonite.local()
model = ebnt.get_model(project='my_project',
task='regression_is_my_profession',
model_name='mymodel')
# run flask service with this model
run_model_server(model)
def main():
# create local ebonite client. This client stores metadata and artifacts on local fs.
# clear=True means it will erase previous data (this is for demo purposes)
ebnt = Ebonite.local(clear=True)
# create sample data
data = pd.DataFrame([{'value': 1}])
# create model with name 'custom_code_model' from function 'run_my_model' and pandas data sample
# and push this model to repository
ebnt.create_model('custom_code_model', run_my_model, data,
project_name='custom_code_project', task_name='custom_code_task')
def main():
# create local ebonite client. This client stores metadata and artifacts on local fs.
ebnt = Ebonite.local()
task = ebnt.get_or_create_task('my_project', 'regression_is_my_profession')
model = task.models('mymodel')
# this changes docker image builder behaviour to get ebonite from local installation instead of pip
# 1. for developing reasons 2. we dont have ebonite on pip yet
with use_local_installation():
# build docker image from model and run it
ebnt.build_and_run_service("sklearn_model_service", model, detach=False, force_overwrite=True)
def main():
# create local ebonite client. This client stores metadata and artifacts on local fs.
ebnt = Ebonite.local()
task = ebnt.get_or_create_task('my_project', 'regression_is_my_profession')
model = task.models('mymodel')
# build docker image from model and run it
ebnt.build_and_run_instance("sklearn_model_service",
model,
runner_kwargs={'detach': False},
builder_kwargs={'force_overwrite': True})
def main():
# create local ebonite client. This client stores metadata and artifacts on local fs.
# clear=True means it will erase previous data (this is for demo purposes)
ebnt = Ebonite.local(clear=True)
# create a Task, container for models
task = ebnt.get_or_create_task('custom_code_project', 'custom_code_task')
# create sample data
data = pd.DataFrame([{'value': 1}])
# create model with name 'custom_code_model' from function 'run_my_model' and pandas data sample
# and push this model to repository
task.create_and_push_model(run_my_model, data, 'custom_code_model')
def main():
ebnt = Ebonite.local(clear=True)
task = ebnt.get_or_create_task('local_deployment', 'local_deployment')
model = create_model(model_function, 0, model_name='dummy_function')
task.add_model(model)
image = ebnt.build_image('dummy_image', model, force_overwrite=True)
instance = ebnt.create_instance('dummy_service', image)
instance.run()
for log in instance.logs(stream=True):
try:
print(log, end='')
except KeyboardInterrupt: # FIXME does not work since we stuck in generator
break
ebnt.stop_instance(instance)