117 lines
4.6 KiB
C++
117 lines
4.6 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 "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/micro/all_ops_resolver.h"
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#include "tensorflow/lite/micro/kernels/kernel_runner.h"
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#include "tensorflow/lite/micro/test_helpers.h"
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#include "tensorflow/lite/micro/testing/micro_test.h"
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namespace tflite {
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namespace testing {
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namespace {
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void TestLogicalOp(const TfLiteRegistration& registration,
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const int* input1_dims_data, const bool* input1_data,
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const int* input2_dims_data, const bool* input2_data,
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const int* output_dims_data,
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const bool* expected_output_data, bool* output_data) {
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TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data);
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TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data);
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TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);
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const int output_dims_count = ElementCount(*output_dims);
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constexpr int inputs_size = 2;
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constexpr int outputs_size = 1;
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constexpr int tensors_size = inputs_size + outputs_size;
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TfLiteTensor tensors[tensors_size] = {
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CreateTensor(input1_data, input1_dims),
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CreateTensor(input2_data, input2_dims),
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CreateTensor(output_data, output_dims),
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};
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int inputs_array_data[] = {2, 0, 1};
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TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
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int outputs_array_data[] = {1, 2};
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TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);
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micro::KernelRunner runner(registration, tensors, tensors_size, inputs_array,
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outputs_array,
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/*builtin_data=*/nullptr, micro_test::reporter);
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare());
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TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.Invoke());
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TF_LITE_MICRO_EXPECT_EQ(output_dims_count, 4);
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for (int i = 0; i < output_dims_count; ++i) {
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TF_LITE_MICRO_EXPECT_EQ(expected_output_data[i], output_data[i]);
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}
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}
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} // namespace
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} // namespace testing
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} // namespace tflite
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TF_LITE_MICRO_TESTS_BEGIN
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TF_LITE_MICRO_TEST(LogicalOr) {
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const int shape[] = {4, 1, 1, 1, 4};
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const bool input1[] = {true, false, false, true};
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const bool input2[] = {true, false, true, false};
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const bool golden[] = {true, false, true, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_OR(),
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shape, input1, shape, input2, shape, golden,
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output_data);
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}
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TF_LITE_MICRO_TEST(BroadcastLogicalOr) {
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const int input1_shape[] = {4, 1, 1, 1, 4};
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const bool input1[] = {true, false, false, true};
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const int input2_shape[] = {4, 1, 1, 1, 1};
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const bool input2[] = {false};
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const bool golden[] = {true, false, false, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_OR(),
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input1_shape, input1, input2_shape, input2,
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input1_shape, golden, output_data);
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}
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TF_LITE_MICRO_TEST(LogicalAnd) {
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const int shape[] = {4, 1, 1, 1, 4};
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const bool input1[] = {true, false, false, true};
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const bool input2[] = {true, false, true, false};
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const bool golden[] = {true, false, false, false};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_AND(),
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shape, input1, shape, input2, shape, golden,
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output_data);
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}
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TF_LITE_MICRO_TEST(BroadcastLogicalAnd) {
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const int input1_shape[] = {4, 1, 1, 1, 4};
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const bool input1[] = {true, false, false, true};
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const int input2_shape[] = {4, 1, 1, 1, 1};
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const bool input2[] = {true};
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const bool golden[] = {true, false, false, true};
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bool output_data[4];
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tflite::testing::TestLogicalOp(tflite::ops::micro::Register_LOGICAL_AND(),
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input1_shape, input1, input2_shape, input2,
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input1_shape, golden, output_data);
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}
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TF_LITE_MICRO_TESTS_END
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