# coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# 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 models."""

from absl.testing import absltest
from absl.testing import parameterized

import numpy as np

import models
import utils


class ModelsTest(parameterized.TestCase):

  @parameterized.named_parameters(
      dict(
          testcase_name='one_sequence',
          sequences=[[1, 0, 0]],
      ),
      dict(
          testcase_name='two_sequences',
          sequences=[[0, 0, 0], [1, 0, 0]],
      ),
      dict(
          testcase_name='three_sequences',
          sequences=[[0, 0, 0], [1, 0, 0], [2, 2, 2]],
      ),
  )
  def test_fit_predict(self, sequences):
    sequence_length = 3
    vocab_size = 3
    model = models.KerasModelWrapper(
        models.build_cnn_model, sequence_length, vocab_size, fit_kwargs={})
    x = utils.onehot(np.array(sequences), num_classes=vocab_size)
    y = np.ones(len(sequences))
    model.fit(x, y)
    output_shape = (len(sequences),)
    self.assertEqual(model.predict(x).shape, output_shape)


if __name__ == '__main__':
  absltest.main()

# coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# 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 models."""

from absl.testing import absltest
from absl.testing import parameterized

import numpy as np

import models
import utils


class ModelsTest(parameterized.TestCase):

  @parameterized.named_parameters(
      dict(
          testcase_name='one_sequence',
          sequences=[[1, 0, 0]],
      ),
      dict(
          testcase_name='two_sequences',
          sequences=[[0, 0, 0], [1, 0, 0]],
      ),
      dict(
          testcase_name='three_sequences',
          sequences=[[0, 0, 0], [1, 0, 0], [2, 2, 2]],
      ),
  )
  def test_fit_predict(self, sequences):
    sequence_length = 3
    vocab_size = 3
    model = models.KerasModelWrapper(
        models.build_cnn_model, sequence_length, vocab_size, fit_kwargs={})
    x = utils.onehot(np.array(sequences), num_classes=vocab_size)
    y = np.ones(len(sequences))
    model.fit(x, y)
    output_shape = (len(sequences),)
    self.assertEqual(model.predict(x).shape, output_shape)


if __name__ == '__main__':
  absltest.main()

# coding=utf-8 # Copyright 2021 The Google Research Authors. # # 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 models.