wehub-resource-sync
134 lines
5.0 KiB
C++
134 lines
5.0 KiB
C++
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <initializer_list>
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#include <vector>
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#include "Eigen/Core"
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#include <gtest/gtest.h>
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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#include "tensorflow/lite/types/half.h"
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namespace tflite {
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namespace {
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using ::testing::ElementsAreArray;
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template <typename T>
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class RoundOpModel : public SingleOpModel {
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public:
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RoundOpModel(std::initializer_list<int> input_shape) {
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input_ = AddInput(GetTensorType<T>());
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output_ = AddOutput(GetTensorType<T>());
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SetBuiltinOp(BuiltinOperator_ROUND, BuiltinOptions_NONE, 0);
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BuildInterpreter({
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input_shape,
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});
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}
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int input() { return input_; }
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std::vector<T> GetOutput() { return ExtractVector<T>(output_); }
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std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
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private:
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int input_;
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int output_;
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};
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TEST(RoundOpTest, SingleDim) {
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RoundOpModel<float> model({6});
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model.PopulateTensor<float>(model.input(), {8.5, 0.0, 3.5, 4.2, -3.5, -4.5});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput(), ElementsAreArray({8, 0, 4, 4, -4, -4}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({6}));
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}
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TEST(RoundOpTest, MultiDims) {
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RoundOpModel<float> model({2, 1, 1, 6});
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model.PopulateTensor<float>(
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model.input(), {0.0001, 8.0001, 0.9999, 9.9999, 0.5, -0.0001, -8.0001,
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-0.9999, -9.9999, -0.5, -2.5, 1.5});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput(),
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ElementsAreArray({0, 8, 1, 10, 0, 0, -8, -1, -10, -0, -2, 2}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 1, 1, 6}));
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}
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TEST(RoundOpTest, Float16SingleDim) {
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RoundOpModel<half> model({6});
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model.PopulateTensor<half>(model.input(),
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{half(8.5f), half(0.0f), half(3.5f), half(4.2f),
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half(-3.5f), half(-4.5f)});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput(),
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ElementsAreArray(
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{half(8), half(0), half(4), half(4), half(-4), half(-4)}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({6}));
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}
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TEST(RoundOpTest, Float16MultiDims) {
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RoundOpModel<half> model({2, 1, 1, 6});
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model.PopulateTensor<half>(
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model.input(),
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{half(0.0001f), half(8.0001f), half(0.9999f), half(9.9999f), half(0.5f),
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half(-0.0001f), half(-8.0001f), half(-0.9999f), half(-9.9999f),
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half(-0.5f), half(-2.5f), half(1.5f)});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput(),
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ElementsAreArray({half(0), half(8), half(1), half(10), half(0),
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half(0), half(-8), half(-1), half(-10),
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half(-0), half(-2), half(2)}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 1, 1, 6}));
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}
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TEST(RoundOpTest, BFloat16SingleDim) {
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RoundOpModel<Eigen::bfloat16> model({6});
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model.PopulateTensor<Eigen::bfloat16>(
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model.input(),
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{Eigen::bfloat16(8.5), Eigen::bfloat16(0.0), Eigen::bfloat16(3.5),
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Eigen::bfloat16(4.2), Eigen::bfloat16(-3.5), Eigen::bfloat16(-4.5)});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(model.GetOutput(),
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ElementsAreArray({Eigen::bfloat16(8), Eigen::bfloat16(0),
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Eigen::bfloat16(4), Eigen::bfloat16(4),
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Eigen::bfloat16(-4), Eigen::bfloat16(-4)}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({6}));
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}
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TEST(RoundOpTest, BFloat16MultiDims) {
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RoundOpModel<Eigen::bfloat16> model({2, 1, 1, 6});
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model.PopulateTensor<Eigen::bfloat16>(
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model.input(),
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{Eigen::bfloat16(0.0001), Eigen::bfloat16(8.0001),
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Eigen::bfloat16(0.9999), Eigen::bfloat16(9.9999), Eigen::bfloat16(0.5),
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Eigen::bfloat16(-0.0001), Eigen::bfloat16(-8.0001),
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Eigen::bfloat16(-0.9999), Eigen::bfloat16(-9.9999),
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Eigen::bfloat16(-0.5), Eigen::bfloat16(-2.5), Eigen::bfloat16(1.5)});
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ASSERT_EQ(model.Invoke(), kTfLiteOk);
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EXPECT_THAT(
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model.GetOutput(),
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ElementsAreArray(
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{Eigen::bfloat16(0), Eigen::bfloat16(8), Eigen::bfloat16(1),
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Eigen::bfloat16(10), Eigen::bfloat16(0), Eigen::bfloat16(0),
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Eigen::bfloat16(-8), Eigen::bfloat16(-1), Eigen::bfloat16(-10),
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Eigen::bfloat16(-0), Eigen::bfloat16(-2), Eigen::bfloat16(2)}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 1, 1, 6}));
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}
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} // namespace
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} // namespace tflite
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