| /* Copyright 2018 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/lite/c/builtin_op_data.h" |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/micro/kernels/kernel_runner.h" |
| #include "tensorflow/lite/micro/test_helpers.h" |
| #include "tensorflow/lite/micro/testing/micro_test.h" |
| |
| namespace tflite { |
| namespace testing { |
| namespace { |
| |
| void TestLogicalOp(const TFLMRegistration& registration, int* input1_dims_data, |
| const bool* input1_data, int* input2_dims_data, |
| const bool* input2_data, int* output_dims_data, |
| const bool* expected_output_data, bool* output_data) { |
| TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data); |
| TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data); |
| TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data); |
| const int output_dims_count = ElementCount(*output_dims); |
| |
| constexpr int inputs_size = 2; |
| constexpr int outputs_size = 1; |
| constexpr int tensors_size = inputs_size + outputs_size; |
| TfLiteTensor tensors[tensors_size] = { |
| CreateTensor(input1_data, input1_dims), |
| CreateTensor(input2_data, input2_dims), |
| CreateTensor(output_data, output_dims), |
| }; |
| |
| int inputs_array_data[] = {2, 0, 1}; |
| TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data); |
| int outputs_array_data[] = {1, 2}; |
| TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data); |
| |
| micro::KernelRunner runner(registration, tensors, tensors_size, inputs_array, |
| outputs_array, |
| /*builtin_data=*/nullptr); |
| |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.InitAndPrepare()); |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, runner.Invoke()); |
| |
| TF_LITE_MICRO_EXPECT_EQ(output_dims_count, 4); |
| for (int i = 0; i < output_dims_count; ++i) { |
| TF_LITE_MICRO_EXPECT_EQ(expected_output_data[i], output_data[i]); |
| } |
| } |
| |
| } // namespace |
| } // namespace testing |
| } // namespace tflite |
| |
| TF_LITE_MICRO_TESTS_BEGIN |
| |
| TF_LITE_MICRO_TEST(LogicalOr) { |
| int shape[] = {4, 1, 1, 1, 4}; |
| const bool input1[] = {true, false, false, true}; |
| const bool input2[] = {true, false, true, false}; |
| const bool golden[] = {true, false, true, true}; |
| bool output_data[4]; |
| tflite::testing::TestLogicalOp(tflite::Register_LOGICAL_OR(), shape, input1, |
| shape, input2, shape, golden, output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(BroadcastLogicalOr) { |
| int input1_shape[] = {4, 1, 1, 1, 4}; |
| const bool input1[] = {true, false, false, true}; |
| int input2_shape[] = {4, 1, 1, 1, 1}; |
| const bool input2[] = {false}; |
| const bool golden[] = {true, false, false, true}; |
| bool output_data[4]; |
| tflite::testing::TestLogicalOp(tflite::Register_LOGICAL_OR(), input1_shape, |
| input1, input2_shape, input2, input1_shape, |
| golden, output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(LogicalAnd) { |
| int shape[] = {4, 1, 1, 1, 4}; |
| const bool input1[] = {true, false, false, true}; |
| const bool input2[] = {true, false, true, false}; |
| const bool golden[] = {true, false, false, false}; |
| bool output_data[4]; |
| tflite::testing::TestLogicalOp(tflite::Register_LOGICAL_AND(), shape, input1, |
| shape, input2, shape, golden, output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(BroadcastLogicalAnd) { |
| int input1_shape[] = {4, 1, 1, 1, 4}; |
| const bool input1[] = {true, false, false, true}; |
| int input2_shape[] = {4, 1, 1, 1, 1}; |
| const bool input2[] = {true}; |
| const bool golden[] = {true, false, false, true}; |
| bool output_data[4]; |
| tflite::testing::TestLogicalOp(tflite::Register_LOGICAL_AND(), input1_shape, |
| input1, input2_shape, input2, input1_shape, |
| golden, output_data); |
| } |
| |
| TF_LITE_MICRO_TESTS_END |