if summary_writer: summary_writer.close() eval_result = None train_result = None if not flags_obj.skip_eval: eval_result = [ test_loss.result().numpy(), test_accuracy.result().numpy() ] train_result = [ train_loss.result().numpy(), training_accuracy.result().numpy() ] stats = build_stats(train_result, eval_result, time_callback) return stats def main(_): model_helpers.apply_clean(flags.FLAGS) with logger.benchmark_context(flags.FLAGS): stats = run(flags.FLAGS) logging.info('Run stats:\n%s', stats) if __name__ == '__main__': logging.set_verbosity(logging.INFO) common.define_keras_flags() app.run(main)
def define_imagenet_keras_flags(): common.define_keras_flags() flags_core.set_defaults() flags.adopt_module_key_flags(common)
def setUpClass(cls): super(CtlImagenetTest, cls).setUpClass() common.define_keras_flags()
def setUpClass(cls): # pylint: disable=invalid-name super(CtlImagenetTest, cls).setUpClass() common.define_keras_flags()