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# The structure of this project is inspired by
import os, json, sys, random
# os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf
import time
if sys.version_info < (3, 0):
print('This script requires Python 3.')
# See the __init__ script in the models folder
# `make_models` is a helper function to load any models you have.
from models import make_model
import os, sys
import time
from hpsearch import hyperband, randomsearch
# Make paths absolute and independent from where the python script is called.
script_dir = os.path.dirname(os.path.realpath(__file__))
results_dir = os.path.join(script_dir, 'results')
sys.path.append(os.path.join(script_dir, 'sealionengine'))
flags =
# Agent configuration
flags.DEFINE_string('model_name', 'InceptionModel', \
'Unique name of the model')
flags.DEFINE_string('config', '{}', \
'JSON inputs to fix model parameters, ' \
+ 'ex: \'{"lr": 0.001}\'')
flags.DEFINE_boolean('load_best_config', False, \
'Force to use the best known configuration')
# Run configuration
flags.DEFINE_string('results_dir', '', \
'Directory to store/log the model ' \
'(if it exist, the model will be loaded from it)')
flags.DEFINE_string('task', 'train', 'The task to run: train, test or search')
flags.DEFINE_boolean('debug', False, 'Debug mode')
def main(_):
config = flags.FLAGS.__flags.copy()
del config['config']
if config['results_dir'] == '':
del config['results_dir']
if config['task'] == 'search':
# Hyperparameter search cannot be continued, so a new results dir is created.
config['results_dir'] = os.path.join(results_dir, 'hs', config['model_name'] \
+ time.strftime('_%Y-%m-%d_%H-%M-%S', time.gmtime()))
hb = Hyperband(config)
results =
model = make_model(config)
if config['task'] == 'train':
elif config['task'] == 'test':
print('Invalid argument: --task=%s. ' \
+ 'It should be either of {train, test, search}.' % config['task'])
if __name__ == '__main__':
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