# Copyright 2022 The TensorFlow 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.

# Lint as: python3
"""Tests for segmentation_heads.py."""

from absl.testing import parameterized
import numpy as np
import tensorflow as tf

from official.projects.volumetric_models.modeling.heads import segmentation_heads_3d


class SegmentationHead3DTest(parameterized.TestCase, tf.test.TestCase):

  @parameterized.parameters(
      (1, 0, True),
      (2, 1, False),
  )
  def test_forward(self, level, num_convs, use_bn):
    head = segmentation_heads_3d.SegmentationHead3D(
        num_classes=10,
        level=level,
        num_convs=num_convs,
        use_batch_normalization=use_bn)
    backbone_features = {
        '1': np.random.rand(2, 128, 128, 128, 16),
        '2': np.random.rand(2, 64, 64, 64, 16),
    }
    decoder_features = {
        '1': np.random.rand(2, 128, 128, 128, 16),
        '2': np.random.rand(2, 64, 64, 64, 16),
    }
    logits = head((backbone_features, decoder_features))

    if str(level) in decoder_features:
      self.assertAllEqual(logits.numpy().shape, [
          2, decoder_features[str(level)].shape[1],
          decoder_features[str(level)].shape[2],
          decoder_features[str(level)].shape[3], 10
      ])

  def test_serialize_deserialize(self):
    head = segmentation_heads_3d.SegmentationHead3D(num_classes=10, level=3)
    config = head.get_config()
    new_head = segmentation_heads_3d.SegmentationHead3D.from_config(config)
    self.assertAllEqual(head.get_config(), new_head.get_config())


if __name__ == '__main__':
  tf.test.main()
