def override_with_flags(hparams):
    'Overrides parameters with flag values.'
    override_flag_names = ['aux_scaling', 'train_batch_size', 'batch_norm_decay', 'batch_norm_epsilon', 'dense_dropout_keep_prob', 'drop_connect_keep_prob', 'drop_connect_version', 'eval_batch_size', 'gradient_clipping_by_global_norm', 'lr', 'lr_decay_method', 'lr_decay_value', 'lr_num_epochs_per_decay', 'moving_average_decay', 'image_size', 'num_cells', 'reduction_size', 'stem_reduction_size', 'num_epochs', 'num_epochs_per_eval', 'optimizer', 'enable_hostcall', 'use_aux_head', 'use_bp16', 'use_tpu', 'lr_warmup_epochs', 'weight_decay', 'num_shards', 'distributed_group_size', 'num_train_images', 'num_eval_images', 'num_label_classes']
    for flag_name in override_flag_names:
        flag_value = getattr(FLAGS, flag_name, 'INVALID')
        if (flag_value == 'INVALID'):
            tf.logging.fatal(('Unknown flag %s.' % str(flag_name)))
        if (flag_value is not None):
            _set_or_add_hparam(hparams, flag_name, flag_value)
Overrides parameters with flag values.
def override_with_flags(hparams):
    
    override_flag_names = ['aux_scaling', 'train_batch_size', 'batch_norm_decay', 'batch_norm_epsilon', 'dense_dropout_keep_prob', 'drop_connect_keep_prob', 'drop_connect_version', 'eval_batch_size', 'gradient_clipping_by_global_norm', 'lr', 'lr_decay_method', 'lr_decay_value', 'lr_num_epochs_per_decay', 'moving_average_decay', 'image_size', 'num_cells', 'reduction_size', 'stem_reduction_size', 'num_epochs', 'num_epochs_per_eval', 'optimizer', 'enable_hostcall', 'use_aux_head', 'use_bp16', 'use_tpu', 'lr_warmup_epochs', 'weight_decay', 'num_shards', 'distributed_group_size', 'num_train_images', 'num_eval_images', 'num_label_classes']
    for flag_name in override_flag_names:
        flag_value = getattr(FLAGS, flag_name, 'INVALID')
        if (flag_value == 'INVALID'):
            tf.logging.fatal(('Unknown flag %s.' % str(flag_name)))
        if (flag_value is not None):
            _set_or_add_hparam(hparams, flag_name, flag_value)