import tensorflow as tf

# checkpoint related configuration
tf.app.flags.DEFINE_string(
    'checkpoint_path', './model',
    'The path to a checkpoint from which to fine-tune.')
tf.app.flags.DEFINE_string(
    'checkpoint_model_scope', '',
    'Model scope in the checkpoint. None if the same as the trained model.')
tf.app.flags.DEFINE_string(
    #'blouse', 'dress', 'outwear', 'skirt', 'trousers', 'all'
    'model_scope', None,
    'Model scope name used to replace the name_scope in checkpoint.')
tf.app.flags.DEFINE_string(
    'checkpoint_exclude_scopes', None,
    'Comma-separated list of scopes of variables to exclude when restoring from a checkpoint.')
tf.app.flags.DEFINE_boolean(
    'ignore_missing_vars', True,
    'When restoring a checkpoint would ignore missing variables.')
tf.app.flags.DEFINE_boolean(
    'run_on_cloud', False,
    'Wether we will train on cloud.')
tf.app.flags.DEFINE_boolean(
    'seq_train', False,
