tensorflow/lite/testing/op_tests/segment_sum.py

# 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.
# ==============================================================================
"""Test configs for segment_sum."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow.compat.v1 as tf
from tensorflow.lite.testing.zip_test_utils import create_tensor_data
from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
from tensorflow.lite.testing.zip_test_utils import register_make_test_function


@register_make_test_function()
def make_segment_sum_tests(options):
  """Make a set of tests to do segment_sum."""

  test_parameters = [
      {
          "data_shape": [[4, 4], [4], [4, 3, 2]],
          "data_dtype": [tf.float32, tf.int32],
          "segment_ids": [[0, 0, 1, 1], [0, 1, 2, 2], [0, 1, 2, 3],
                          [0, 0, 0, 0]],
      },
  ]

  def build_graph(parameters):
    """Build the segment_sum op testing graph."""
    data = tf.compat.v1.placeholder(
        dtype=parameters["data_dtype"],
        name="data",
        shape=parameters["data_shape"])
    segment_ids = tf.constant(parameters["segment_ids"], dtype=tf.int32)
    out = tf.segment_sum(data, segment_ids)
    return [data], [out]

  def build_inputs(parameters, sess, inputs, outputs):
    data = create_tensor_data(parameters["data_dtype"],
                              parameters["data_shape"])
    return [data], sess.run(outputs, feed_dict=dict(zip(inputs, [data])))

  options.use_experimental_converter = True
  make_zip_of_tests(
      options,
      test_parameters,
      build_graph,
      build_inputs,
      expected_tf_failures=0)