# Lint as: python3
# Copyright 2020 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.
# ==============================================================================
"""Tests for cls_head."""

import tensorflow as tf

from official.nlp.modeling.layers import cls_head


class ClassificationHead(tf.test.TestCase):

  def test_layer_invocation(self):
    test_layer = cls_head.ClassificationHead(inner_dim=5, num_classes=2)
    features = tf.zeros(shape=(2, 10, 10), dtype=tf.float32)
    output = test_layer(features)
    self.assertAllClose(output, [[0., 0.], [0., 0.]])
    self.assertSameElements(test_layer.checkpoint_items.keys(),
                            ["pooler_dense"])

  def test_layer_serialization(self):
    layer = cls_head.ClassificationHead(10, 2)
    new_layer = cls_head.ClassificationHead.from_config(layer.get_config())

    # If the serialization was successful, the new config should match the old.
    self.assertAllEqual(layer.get_config(), new_layer.get_config())


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