import tensorflow as tf

tf.app.flags.DEFINE_string(
    'dataset_name', '{}_????', 'The pattern of the dataset name to load.')
tf.app.flags.DEFINE_string(
    'model_dir', './logs_sext_cpn/',
    'The parent directory where the model will be stored.')
tf.app.flags.DEFINE_integer(
    'log_every_n_steps', 10,
    'The frequency with which logs are print.')
tf.app.flags.DEFINE_integer(
    'save_summary_steps', 100,
    'The frequency with which summaries are saved, in seconds.')
tf.app.flags.DEFINE_integer(
    'save_checkpoints_secs', 3600,
    'The frequency with which the model is saved, in seconds.')
# model related configuration
tf.app.flags.DEFINE_integer(
    'train_image_size', 384,
    'The size of the input image for the model to use.')
tf.app.flags.DEFINE_integer(
    'heatmap_size', 96,
    'The size of the output heatmap of the model.')
tf.app.flags.DEFINE_string(
