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// Copyright 2017 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.
// =============================================================================
#include "tensorflow/contrib/boosted_trees/lib/utils/examples_iterable.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"
namespace tensorflow {
namespace boosted_trees {
namespace utils {
namespace {
class ExamplesIterableTest : public ::testing::Test {};
TEST_F(ExamplesIterableTest, Iterate) {
// Create a batch of 8 examples having one dense float, two sparse float and
// two sparse int features. Second sparse float feature is multivalent.
// The data looks like the following:
// Instance | DenseF1 | SparseF1 | SparseF2 | SparseI1 | SparseI2 |
// 0 | 7 | -3 | | 1 | 1, 8 | |
// 1 | -2 | | 4 | | 0 | 7 |
// 2 | 8 | 0 | | 3 | | 13 |
// 3 | 1 | 5 | 7 | | 2, 0 | 4 |
// 4 | 0 | 0 | | 4.3 | | 0 |
// 5 | -4 | | 9 | 0.8 | | |
// 6 | 7 | | | | | |
// 7 | -2 | | -4 | | 5 | |
auto dense_float_tensor = test::AsTensor<float>(
{7.0f, -2.0f, 8.0f, 1.0f, 0.0f, -4.0f, 7.0f, -2.0f}, {8, 1});
auto sparse_float_indices1 =
test::AsTensor<int64>({0, 0, 2, 0, 3, 0, 4, 0}, {4, 2});
auto sparse_float_values1 = test::AsTensor<float>({-3.0f, 0.0f, 5.0f, 0.0f});
auto sparse_float_shape1 = TensorShape({8, 1});
sparse::SparseTensor sparse_float_tensor1;
TF_ASSERT_OK(
sparse::SparseTensor::Create(sparse_float_indices1, sparse_float_values1,
sparse_float_shape1, &sparse_float_tensor1));
auto sparse_float_indices2 = test::AsTensor<int64>(
{0, 1, 1, 0, 2, 1, 3, 0, 4, 1, 5, 0, 5, 1, 7, 0}, {8, 2});
auto sparse_float_values2 =
test::AsTensor<float>({1.f, 4.0f, 3.f, 7.0f, 4.3f, 9.0f, 0.8f, -4.0f});
auto sparse_float_shape2 = TensorShape({8, 2});
sparse::SparseTensor sparse_float_tensor2;
TF_ASSERT_OK(
sparse::SparseTensor::Create(sparse_float_indices2, sparse_float_values2,
sparse_float_shape2, &sparse_float_tensor2));
auto sparse_int_indices1 =
test::AsTensor<int64>({0, 0, 0, 1, 1, 0, 3, 0, 3, 1, 7, 0}, {6, 2});
auto sparse_int_values1 = test::AsTensor<int64>({1, 8, 0, 2, 0, 5});
auto sparse_int_shape1 = TensorShape({8, 2});
sparse::SparseTensor sparse_int_tensor1;
TF_ASSERT_OK(
sparse::SparseTensor::Create(sparse_int_indices1, sparse_int_values1,
sparse_int_shape1, &sparse_int_tensor1));
auto sparse_int_indices2 =
test::AsTensor<int64>({1, 0, 2, 0, 3, 0, 4, 0}, {4, 2});
auto sparse_int_values2 = test::AsTensor<int64>({7, 13, 4, 0});
auto sparse_int_shape2 = TensorShape({8, 1});
sparse::SparseTensor sparse_int_tensor2;
TF_ASSERT_OK(
sparse::SparseTensor::Create(sparse_int_indices2, sparse_int_values2,
sparse_int_shape2, &sparse_int_tensor2));
auto validate_example_features = [](int64 example_idx,
const Example& example) {
EXPECT_EQ(1, example.dense_float_features.size());
switch (example_idx) {
case 0: {
EXPECT_EQ(0, example.example_idx);
EXPECT_EQ(7.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_TRUE(example.sparse_float_features[0][0].has_value());
EXPECT_EQ(-3.0f, example.sparse_float_features[0][0].get_value());
// SparseF2 - multivalent.
EXPECT_FALSE(example.sparse_float_features[1][0].has_value());
EXPECT_TRUE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(1.0f, example.sparse_float_features[1][1].get_value());
EXPECT_EQ(2, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[0].count(1));
EXPECT_EQ(1, example.sparse_int_features[0].count(8));
EXPECT_EQ(0, example.sparse_int_features[1].size());
} break;
case 1: {
EXPECT_EQ(1, example.example_idx);
EXPECT_EQ(-2.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_FALSE(example.sparse_float_features[0][0].has_value());
// SparseF2.
EXPECT_TRUE(example.sparse_float_features[1][0].has_value());
EXPECT_EQ(4.0f, example.sparse_float_features[1][0].get_value());
EXPECT_FALSE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(1, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[0].count(0));
EXPECT_EQ(1, example.sparse_int_features[1].size());
EXPECT_EQ(1, example.sparse_int_features[1].count(7));
} break;
case 2: {
EXPECT_EQ(2, example.example_idx);
EXPECT_EQ(8.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_TRUE(example.sparse_float_features[0][0].has_value());
EXPECT_EQ(0.0f, example.sparse_float_features[0][0].get_value());
// SparseF2.
EXPECT_FALSE(example.sparse_float_features[1][0].has_value());
EXPECT_TRUE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(3.f, example.sparse_float_features[1][1].get_value());
EXPECT_EQ(0, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[1].size());
EXPECT_EQ(1, example.sparse_int_features[1].count(13));
} break;
case 3: {
EXPECT_EQ(3, example.example_idx);
EXPECT_EQ(1.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_TRUE(example.sparse_float_features[0][0].has_value());
EXPECT_EQ(5.0f, example.sparse_float_features[0][0].get_value());
// SparseF2.
EXPECT_TRUE(example.sparse_float_features[1][0].has_value());
EXPECT_EQ(7.0f, example.sparse_float_features[1][0].get_value());
EXPECT_FALSE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(2, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[0].count(2));
EXPECT_EQ(1, example.sparse_int_features[0].count(0));
EXPECT_EQ(1, example.sparse_int_features[1].size());
EXPECT_EQ(1, example.sparse_int_features[1].count(4));
} break;
case 4: {
EXPECT_EQ(4, example.example_idx);
EXPECT_EQ(0.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_TRUE(example.sparse_float_features[0][0].has_value());
EXPECT_EQ(0.0f, example.sparse_float_features[0][0].get_value());
// SparseF2.
EXPECT_FALSE(example.sparse_float_features[1][0].has_value());
EXPECT_TRUE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(4.3f, example.sparse_float_features[1][1].get_value());
EXPECT_EQ(0, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[1].size());
EXPECT_EQ(1, example.sparse_int_features[1].count(0));
} break;
case 5: {
EXPECT_EQ(5, example.example_idx);
EXPECT_EQ(-4.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_FALSE(example.sparse_float_features[0][0].has_value());
// SparseF2.
EXPECT_TRUE(example.sparse_float_features[1][0].has_value());
EXPECT_EQ(9.0f, example.sparse_float_features[1][0].get_value());
EXPECT_TRUE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(0.8f, example.sparse_float_features[1][1].get_value());
EXPECT_EQ(0, example.sparse_int_features[0].size());
} break;
case 6: {
EXPECT_EQ(6, example.example_idx);
EXPECT_EQ(7.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_FALSE(example.sparse_float_features[0][0].has_value());
// SparseF2.
EXPECT_FALSE(example.sparse_float_features[1][0].has_value());
EXPECT_FALSE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(0, example.sparse_int_features[0].size());
} break;
case 7: {
EXPECT_EQ(7, example.example_idx);
EXPECT_EQ(-2.0f, example.dense_float_features[0]);
// SparseF1.
EXPECT_FALSE(example.sparse_float_features[0][0].has_value());
// SparseF2.
EXPECT_TRUE(example.sparse_float_features[1][0].has_value());
EXPECT_EQ(-4.0f, example.sparse_float_features[1][0].get_value());
EXPECT_FALSE(example.sparse_float_features[1][1].has_value());
EXPECT_EQ(1, example.sparse_int_features[0].size());
EXPECT_EQ(1, example.sparse_int_features[0].count(5));
} break;
default: { LOG(QFATAL) << "Invalid example index."; } break;
}
};
// Iterate through all examples sequentially.
ExamplesIterable full_iterable(
{dense_float_tensor}, {sparse_float_tensor1, sparse_float_tensor2},
{sparse_int_tensor1, sparse_int_tensor2}, 0, 8);
int64 example_idx = 0;
for (const auto& example : full_iterable) {
validate_example_features(example_idx, example);
++example_idx;
}
EXPECT_EQ(8, example_idx);
// Iterate through slice (2, 6) of examples.
ExamplesIterable slice_iterable(
{dense_float_tensor}, {sparse_float_tensor1, sparse_float_tensor2},
{sparse_int_tensor1, sparse_int_tensor2}, 2, 6);
example_idx = 2;
for (const auto& example : slice_iterable) {
validate_example_features(example_idx, example);
++example_idx;
}
EXPECT_EQ(6, example_idx);
}
} // namespace
} // namespace utils
} // namespace boosted_trees
} // namespace tensorflow
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