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#
# Licensed under the Apache License, Version 2.0 (the "License");
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"""Tests for segmentation_heads.py."""

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

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()
