# Copyright 2021 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
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# ==============================================================================
"""Test configs for pool operators."""
import tensorflow as tf
from tensorflow.lite.testing.zip_test_utils import create_tensor_data
from tensorflow.lite.testing.zip_test_utils import ExtraConvertOptions
from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
from tensorflow.lite.testing.zip_test_utils import register_make_test_function


def make_pool3d_tests(pool_op):
  """Make a set of tests to do pooling.

  Args:
    pool_op: TensorFlow pooling operation to test  i.e. `tf.nn.max_pool3d`.

  Returns:
    A function representing the true generator (after curried pool_op).
  """

  def f(options, expected_tf_failures=0):
    """Actual function that generates examples.

    Args:
      options: An Options instance.
      expected_tf_failures: number of expected tensorflow failures.
    """

    # Chose a set of parameters
    test_parameters = [
        {
            "ksize": [[1, 1, 1, 1, 1], [1, 2, 2, 2, 1], [1, 2, 3, 4, 1]],
            "strides": [[1, 1, 1, 1, 1], [1, 2, 1, 2, 1], [1, 2, 2, 4, 1]],
            "input_shape": [[1, 1, 1, 1, 1], [1, 16, 15, 14, 1],
                            [3, 16, 15, 14, 3]],
            "padding": ["SAME", "VALID"],
            "data_format": ["NDHWC"],
        },
    ]

    def build_graph(parameters):
      input_tensor = tf.compat.v1.placeholder(
          dtype=tf.float32, name="input", shape=parameters["input_shape"])
      out = pool_op(
          input_tensor,
          ksize=parameters["ksize"],
          strides=parameters["strides"],
          data_format=parameters["data_format"],
          padding=parameters["padding"])
      return [input_tensor], [out]

    def build_inputs(parameters, sess, inputs, outputs):
      input_values = create_tensor_data(tf.float32, parameters["input_shape"])
      return [input_values], sess.run(
          outputs, feed_dict=dict(zip(inputs, [input_values])))

    extra_convert_options = ExtraConvertOptions()
    extra_convert_options.allow_custom_ops = True
    make_zip_of_tests(
        options,
        test_parameters,
        build_graph,
        build_inputs,
        extra_convert_options,
        expected_tf_failures=expected_tf_failures)

  return f


@register_make_test_function()
def make_avg_pool3d_tests(options):
  make_pool3d_tests(tf.nn.avg_pool3d)(options, expected_tf_failures=6)


@register_make_test_function()
def make_max_pool3d_tests(options):
  make_pool3d_tests(tf.nn.max_pool3d)(options, expected_tf_failures=6)