# Path: studio/fs_tracker.py
# STUDIOML_EXPERIMENT = 'STUDIOML_EXPERIMENT'
# STUDIOML_HOME = 'STUDIOML_HOME'
# STUDIOML_ARTIFACT_MAPPING = 'STUDIOML_ARTIFACT_MAPPING'
# def get_experiment_key():
# def get_studio_home():
# def setup_experiment(env, experiment, clean=True):
# def get_artifact(tag):
# def get_artifacts():
# def get_model_directory(experiment_name=None):
# def get_artifact_cache(tag, experiment_name=None):
# def get_blob_cache(blobkey):
# def get_model_directory(experiment_name=None):
# def _get_artifact_mapping_path(experiment_name=None):
# def _get_experiment_key(experiment):
# def _setup_model_directory(experiment_name, clean=False):
# def get_queue_directory():
# def get_tensorboard_dir(experiment_name=None):


from studio import fs_tracker
import numpy as np

try:
    lr = np.load(fs_tracker.get_artifact('lr'))
except BaseException:
    lr = np.random.random(10)


# Path: studio/fs_tracker.py
# STUDIOML_EXPERIMENT = 'STUDIOML_EXPERIMENT'
# STUDIOML_HOME = 'STUDIOML_HOME'
# STUDIOML_ARTIFACT_MAPPING = 'STUDIOML_ARTIFACT_MAPPING'
# def get_experiment_key():
# def get_studio_home():
# def setup_experiment(env, experiment, clean=True):
# def get_artifact(tag):
# def get_artifacts():
# def get_model_directory(experiment_name=None):
# def get_artifact_cache(tag, experiment_name=None):
# def get_blob_cache(blobkey):
# def get_model_directory(experiment_name=None):
# def _get_artifact_mapping_path(experiment_name=None):
# def _get_experiment_key(experiment):
# def _setup_model_directory(experiment_name, clean=False):
# def get_queue_directory():
# def get_tensorboard_dir(experiment_name=None):


# Path: tests/test_array.py
from studio import fs_tracker
import numpy as np


try:
    lr = np.load(fs_tracker.get_artifact('lr'))
except BaseException:
    lr = np.random.random(10)


print("fitness: %s" % np.abs(np.sum(lr)))