#!/usr/bin/env python
# coding=utf-8
# Copyright 2018 The DisentanglementLib Authors.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Evaluation module for disentangled representations."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from absl import app
from absl import flags
from disentanglement_lib.evaluation import evaluate
from tensorflow.compat.v1 import gfile

FLAGS = flags.FLAGS

flags.DEFINE_string("input_dir", None, "Directory to take trained "
                    "representation from.")
flags.DEFINE_string("output_dir", None, "Directory to save scores to.")
flags.DEFINE_multi_string("gin_config", [],
                          "List of paths to the config files.")
flags.DEFINE_multi_string("gin_bindings", [],
                          "Newline separated list of Gin parameter bindings.")
flags.DEFINE_string("gin_evaluation_config_glob", None,
                    "Path to glob pattern to evaluation configs.")
flags.DEFINE_boolean("overwrite", False,
                     "Whether to overwrite output directory.")


def main(unused_argv):
  # We either allow multiple scores to be computed via the
  # gin_evaluation_config_glob flag or a single score via the gin_config and
  # gin_bindings flags.
  if FLAGS.gin_evaluation_config_glob is not None:
    for gin_eval_config in sorted(gfile.Glob(FLAGS.gin_evaluation_config_glob)):
      metric_name = os.path.basename(gin_eval_config).replace(".gin", "")
      metric_dir = os.path.join(FLAGS.output_dir, metric_name)
      gin_config_files = [gin_eval_config]
      gin_bindings = [
          "evaluation.name = '{}'".format(metric_name)
      ]
      evaluate.evaluate_with_gin(FLAGS.input_dir, metric_dir, FLAGS.overwrite,
                                 gin_config_files, gin_bindings)
  else:
    evaluate.evaluate_with_gin(FLAGS.input_dir, FLAGS.output_dir,
                               FLAGS.overwrite, FLAGS.gin_config,
                               FLAGS.gin_bindings)


if __name__ == "__main__":
  app.run(main)
