| /* 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/lite/c/builtin_op_data.h" |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/micro/kernels/all_ops_resolver.h" |
| #include "tensorflow/lite/micro/testing/micro_test.h" |
| #include "tensorflow/lite/micro/testing/test_utils.h" |
| |
| namespace tflite { |
| namespace testing { |
| namespace { |
| |
| void TestSoftmaxFloat(std::initializer_list<int> input_dims_data, |
| std::initializer_list<float> input_data, |
| std::initializer_list<float> expected_output_data, |
| std::initializer_list<int> output_dims_data, |
| float* output_data) { |
| TfLiteIntArray* input_dims = IntArrayFromInitializer(input_dims_data); |
| TfLiteIntArray* output_dims = IntArrayFromInitializer(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] = { |
| CreateFloatTensor(input_data, input_dims, "input_tensor"), |
| CreateFloatTensor(output_data, output_dims, "output_tensor"), |
| }; |
| |
| TfLiteContext context; |
| PopulateContext(tensors, tensors_size, micro_test::reporter, &context); |
| |
| ::tflite::ops::micro::AllOpsResolver resolver; |
| const TfLiteRegistration* registration = |
| resolver.FindOp(tflite::BuiltinOperator_SOFTMAX, 1); |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration); |
| |
| TfLiteSoftmaxParams builtin_data = {1.0f}; |
| const char* init_data = reinterpret_cast<const char*>(&builtin_data); |
| size_t init_data_size = 0; |
| void* user_data = nullptr; |
| if (registration->init) { |
| user_data = registration->init(&context, init_data, init_data_size); |
| } |
| int inputs_array_data[] = {1, 0}; |
| TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data); |
| int outputs_array_data[] = {1, 1}; |
| TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data); |
| int temporaries_array_data[] = {0}; |
| TfLiteIntArray* temporaries_array = IntArrayFromInts(temporaries_array_data); |
| |
| TfLiteNode node; |
| node.inputs = inputs_array; |
| node.outputs = outputs_array; |
| node.temporaries = temporaries_array; |
| node.user_data = user_data; |
| node.builtin_data = reinterpret_cast<void*>(&builtin_data); |
| node.custom_initial_data = nullptr; |
| node.custom_initial_data_size = 0; |
| node.delegate = nullptr; |
| if (registration->prepare) { |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->prepare(&context, &node)); |
| } |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration->invoke); |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->invoke(&context, &node)); |
| if (registration->free) { |
| registration->free(&context, user_data); |
| } |
| for (int i = 0; i < output_dims_count; ++i) { |
| TF_LITE_MICRO_EXPECT_NEAR(expected_output_data.begin()[i], output_data[i], |
| 1e-5f); |
| } |
| } |
| |
| void TestSoftmaxQuantized(std::initializer_list<int> input_dims_data, |
| std::initializer_list<uint8_t> input_data, |
| float input_min, float input_max, |
| std::initializer_list<uint8_t> expected_output_data, |
| std::initializer_list<int> output_dims_data, |
| float output_min, float output_max, |
| uint8_t* output_data) { |
| TfLiteIntArray* input_dims = IntArrayFromInitializer(input_dims_data); |
| TfLiteIntArray* output_dims = IntArrayFromInitializer(output_dims_data); |
| const int output_dims_count = ElementCount(*output_dims); |
| |
| constexpr int inputs_size = 1; |
| constexpr int outputs_size = 1; |
| constexpr int tensors_size = inputs_size + outputs_size; |
| TfLiteTensor tensors[tensors_size] = { |
| CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, |
| input_max), |
| CreateQuantizedTensor(output_data, output_dims, "output_tensor", |
| output_min, output_max), |
| }; |
| |
| TfLiteContext context; |
| PopulateContext(tensors, tensors_size, micro_test::reporter, &context); |
| |
| ::tflite::ops::micro::AllOpsResolver resolver; |
| const TfLiteRegistration* registration = |
| resolver.FindOp(tflite::BuiltinOperator_SOFTMAX, 1); |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration); |
| |
| TfLiteSoftmaxParams builtin_data = {1.0f}; |
| const char* init_data = reinterpret_cast<const char*>(&builtin_data); |
| size_t init_data_size = 0; |
| void* user_data = nullptr; |
| if (registration->init) { |
| user_data = registration->init(&context, init_data, init_data_size); |
| } |
| |
| int inputs_array_data[] = {1, 0}; |
| TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data); |
| int outputs_array_data[] = {1, 1}; |
| TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data); |
| int temporaries_array_data[] = {0}; |
| TfLiteIntArray* temporaries_array = IntArrayFromInts(temporaries_array_data); |
| |
| TfLiteNode node; |
| node.inputs = inputs_array; |
| node.outputs = outputs_array; |
| node.temporaries = temporaries_array; |
| node.user_data = user_data; |
| node.builtin_data = reinterpret_cast<void*>(&builtin_data); |
| node.custom_initial_data = nullptr; |
| node.custom_initial_data_size = 0; |
| node.delegate = nullptr; |
| |
| if (registration->prepare) { |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->prepare(&context, &node)); |
| } |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration->invoke); |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->invoke(&context, &node)); |
| if (registration->free) { |
| registration->free(&context, user_data); |
| } |
| for (int i = 0; i < output_dims_count; ++i) { |
| TF_LITE_MICRO_EXPECT_EQ(expected_output_data.begin()[i], output_data[i]); |
| } |
| } |
| |
| void TestSoftmaxQuantizedSigned( |
| std::initializer_list<int> input_dims_data, |
| std::initializer_list<int8_t> input_data, float input_min, float input_max, |
| std::initializer_list<int8_t> expected_output_data, |
| std::initializer_list<int> output_dims_data, float output_min, |
| float output_max, int8_t* output_data) { |
| TfLiteIntArray* input_dims = IntArrayFromInitializer(input_dims_data); |
| TfLiteIntArray* output_dims = IntArrayFromInitializer(output_dims_data); |
| const int output_dims_count = ElementCount(*output_dims); |
| |
| constexpr int inputs_size = 1; |
| constexpr int outputs_size = 1; |
| constexpr int tensors_size = inputs_size + outputs_size; |
| TfLiteTensor tensors[tensors_size] = { |
| CreateQuantizedTensor(input_data, input_dims, "input_tensor", input_min, |
| input_max), |
| CreateQuantizedTensor(output_data, output_dims, "output_tensor", |
| output_min, output_max), |
| }; |
| |
| TfLiteContext context; |
| PopulateContext(tensors, tensors_size, micro_test::reporter, &context); |
| |
| ::tflite::ops::micro::AllOpsResolver resolver; |
| const TfLiteRegistration* registration = |
| resolver.FindOp(tflite::BuiltinOperator_SOFTMAX, 1); |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration); |
| |
| TfLiteSoftmaxParams builtin_data = {1.0f}; |
| const char* init_data = reinterpret_cast<const char*>(&builtin_data); |
| size_t init_data_size = 0; |
| void* user_data = nullptr; |
| if (registration->init) { |
| user_data = registration->init(&context, init_data, init_data_size); |
| } |
| |
| int inputs_array_data[] = {1, 0}; |
| TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data); |
| int outputs_array_data[] = {1, 1}; |
| TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data); |
| int temporaries_array_data[] = {0}; |
| TfLiteIntArray* temporaries_array = IntArrayFromInts(temporaries_array_data); |
| |
| TfLiteNode node; |
| node.inputs = inputs_array; |
| node.outputs = outputs_array; |
| node.temporaries = temporaries_array; |
| node.user_data = user_data; |
| node.builtin_data = reinterpret_cast<void*>(&builtin_data); |
| node.custom_initial_data = nullptr; |
| node.custom_initial_data_size = 0; |
| node.delegate = nullptr; |
| |
| if (registration->prepare) { |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->prepare(&context, &node)); |
| } |
| TF_LITE_MICRO_EXPECT_NE(nullptr, registration->invoke); |
| TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, registration->invoke(&context, &node)); |
| if (registration->free) { |
| registration->free(&context, user_data); |
| } |
| for (int i = 0; i < output_dims_count; ++i) { |
| TF_LITE_MICRO_EXPECT_EQ(expected_output_data.begin()[i], output_data[i]); |
| } |
| } |
| |
| } // namespace |
| } // namespace testing |
| } // namespace tflite |
| |
| TF_LITE_MICRO_TESTS_BEGIN |
| |
| TF_LITE_MICRO_TEST(SimpleTest) { |
| const int output_dims_count = 10; |
| float output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxFloat( // |
| {2, 2, 5}, // Input shape. |
| { |
| 1.0, 2.0, 3.0, 4.0, 5.0, // b = 0 |
| -1.0, -2.0, -3.0, -4.0, -5.0, // b = 0 |
| }, |
| { |
| // Expected results. |
| 0.011656231, |
| 0.031684921, |
| 0.086128544, |
| 0.234121657, |
| 0.636408647, |
| 0.636408647, |
| 0.234121657, |
| 0.086128544, |
| 0.031684921, |
| 0.011656231, |
| }, |
| {2, 2, 5}, // Output shape. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(SimpleTestQuantizedUnsigned) { |
| using tflite::testing::F2Q; |
| |
| const float input_min = -63.5f; |
| const float input_max = 64.0f; |
| const float output_min = 0.0f; |
| const float output_max = (255.0f / 256.0f); |
| const int output_dims_count = 5; |
| uint8_t output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxQuantized( // |
| {2, 1, 5}, // Input shape. |
| { |
| F2Q(1.0, input_min, input_max), |
| F2Q(2.0, input_min, input_max), |
| F2Q(3.0, input_min, input_max), |
| F2Q(4.0, input_min, input_max), |
| F2Q(5.0, input_min, input_max), |
| }, |
| input_min, input_max, // Input quantized range. |
| { |
| // Expected results. |
| F2Q(0.011656231, output_min, output_max), |
| F2Q(0.031684921, output_min, output_max), |
| F2Q(0.086128544, output_min, output_max), |
| F2Q(0.234121657, output_min, output_max), |
| F2Q(0.636408647, output_min, output_max), |
| }, |
| {2, 1, 5}, // Output shape. |
| output_min, output_max, // Output quantized range. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(SimpleTestQuantizedSigned) { |
| using tflite::testing::F2QS; |
| |
| const float input_min = -63.5f; |
| const float input_max = 64.0f; |
| const float output_min = 0.0f; |
| const float output_max = (255.0f / 256.0f); |
| const int output_dims_count = 10; |
| int8_t output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxQuantizedSigned( // |
| {2, 2, 5}, // Input shape. |
| { // b = 0 |
| F2QS(-3.0, input_min, input_max), F2QS(5.0, input_min, input_max), |
| F2QS(-7.0, input_min, input_max), F2QS(9.0, input_min, input_max), |
| F2QS(-11.0, input_min, input_max), |
| // b = 1 |
| F2QS(1.0, input_min, input_max), F2QS(2.0, input_min, input_max), |
| F2QS(3.0, input_min, input_max), F2QS(4.0, input_min, input_max), |
| F2QS(5.0, input_min, input_max)}, |
| input_min, input_max, // Input quantized range. |
| { |
| // Expected results. |
| // b = 0 |
| F2QS(0.000006933, output_min, output_max), |
| F2QS(0.017986099, output_min, output_max), |
| F2QS(0.000000110, output_min, output_max), |
| F2QS(0.982007754, output_min, output_max), |
| F2QS(0.000000002, output_min, output_max), |
| // b = 1 |
| F2QS(0.011656231, output_min, output_max), |
| F2QS(0.031684921, output_min, output_max), |
| F2QS(0.086128544, output_min, output_max), |
| F2QS(0.234121657, output_min, output_max), |
| F2QS(0.636408647, output_min, output_max), |
| }, |
| {2, 2, 5}, // Output shape. |
| output_min, output_max, // Output quantized range. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(SimpleTestQuantizedSigned1D) { |
| using tflite::testing::F2QS; |
| |
| const float input_min = -63.5f; |
| const float input_max = 64.0f; |
| const float output_min = 0.0f; |
| const float output_max = (255.0f / 256.0f); |
| const int output_dims_count = 5; |
| int8_t output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxQuantizedSigned( // |
| {1, 5}, // Input shape. |
| { |
| F2QS(1.0, input_min, input_max), |
| F2QS(2.0, input_min, input_max), |
| F2QS(3.0, input_min, input_max), |
| F2QS(4.0, input_min, input_max), |
| F2QS(5.0, input_min, input_max), |
| }, |
| input_min, input_max, // Input quantized range. |
| { |
| // Expected results. |
| F2QS(0.011656231, output_min, output_max), |
| F2QS(0.031684921, output_min, output_max), |
| F2QS(0.086128544, output_min, output_max), |
| F2QS(0.234121657, output_min, output_max), |
| F2QS(0.636408647, output_min, output_max), |
| }, |
| {1, 5}, // Output shape. |
| output_min, output_max, // Output quantized range. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(SimpleTestQuantizedSigned2D) { |
| using tflite::testing::F2QS; |
| |
| const float input_min = -63.5f; |
| const float input_max = 64.0f; |
| const float output_min = 0.0f; |
| const float output_max = (255.0f / 256.0f); |
| const int output_dims_count = 10; |
| int8_t output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxQuantizedSigned( // |
| {2, 2, 5}, // Input shape. |
| { // h = 0 |
| F2QS(-3.0, input_min, input_max), F2QS(5.0, input_min, input_max), |
| F2QS(-7.0, input_min, input_max), F2QS(9.0, input_min, input_max), |
| F2QS(-11.0, input_min, input_max), |
| // h = 1 |
| F2QS(1.0, input_min, input_max), F2QS(2.0, input_min, input_max), |
| F2QS(3.0, input_min, input_max), F2QS(4.0, input_min, input_max), |
| F2QS(5.0, input_min, input_max)}, |
| input_min, input_max, // Input quantized range. |
| { |
| // Expected results. |
| // h = 0 |
| F2QS(0.000006034, output_min, output_max), |
| F2QS(0.017986099, output_min, output_max), |
| F2QS(0.000000111, output_min, output_max), |
| F2QS(0.982007754, output_min, output_max), |
| F2QS(0.000000002, output_min, output_max), |
| // h = 1 |
| F2QS(0.011656231, output_min, output_max), |
| F2QS(0.031684921, output_min, output_max), |
| F2QS(0.086128544, output_min, output_max), |
| F2QS(0.234121657, output_min, output_max), |
| F2QS(0.636408647, output_min, output_max), |
| }, |
| {2, 2, 5}, // Output shape. |
| output_min, output_max, // Output quantized range. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TEST(SimpleTestQuantizedSigned4D) { |
| using tflite::testing::F2QS; |
| |
| const float input_min = -63.5f; |
| const float input_max = 64.0f; |
| const float output_min = 0.0f; |
| const float output_max = (255.0f / 256.0f); |
| const int output_dims_count = 120; |
| int8_t output_data[output_dims_count]; |
| tflite::testing::TestSoftmaxQuantizedSigned( // |
| {4, 2, 3, 4, 5}, // Input shape. |
| { // n = 0 |
| // c = 0 |
| // h = 0 |
| F2QS(3.00, input_min, input_max), F2QS(6.00, input_min, input_max), |
| F2QS(-5.00, input_min, input_max), F2QS(4.00, input_min, input_max), |
| F2QS(-9.00, input_min, input_max), |
| // h = 1 |
| F2QS(-10.00, input_min, input_max), F2QS(-10.00, input_min, input_max), |
| F2QS(-8.00, input_min, input_max), F2QS(2.00, input_min, input_max), |
| F2QS(2.00, input_min, input_max), |
| // h = 2 |
| F2QS(8.00, input_min, input_max), F2QS(-5.00, input_min, input_max), |
| F2QS(-8.00, input_min, input_max), F2QS(5.00, input_min, input_max), |
| F2QS(-6.00, input_min, input_max), |
| // h = 3 |
| F2QS(-8.00, input_min, input_max), F2QS(6.00, input_min, input_max), |
| F2QS(1.00, input_min, input_max), F2QS(-10.00, input_min, input_max), |
| F2QS(-8.00, input_min, input_max), |
| |
| // c = 1 |
| // h = 0 |
| F2QS(7.00, input_min, input_max), F2QS(6.00, input_min, input_max), |
| F2QS(-10.00, input_min, input_max), F2QS(-4.00, input_min, input_max), |
| F2QS(-5.00, input_min, input_max), |
| // h = 1 |
| F2QS(2.00, input_min, input_max), F2QS(7.00, input_min, input_max), |
| F2QS(9.00, input_min, input_max), F2QS(-9.00, input_min, input_max), |
| F2QS(7.00, input_min, input_max), |
| // h = 2 |
| F2QS(-4.00, input_min, input_max), F2QS(-2.00, input_min, input_max), |
| F2QS(8.00, input_min, input_max), F2QS(2.00, input_min, input_max), |
| F2QS(2.00, input_min, input_max), |
| // h = 3 |
| F2QS(3.00, input_min, input_max), F2QS(6.00, input_min, input_max), |
| F2QS(6.00, input_min, input_max), F2QS(2.00, input_min, input_max), |
| F2QS(4.00, input_min, input_max), |
| |
| // c = 2 |
| // h = 0 |
| F2QS(9.00, input_min, input_max), F2QS(7.00, input_min, input_max), |
| F2QS(-7.00, input_min, input_max), F2QS(0.00, input_min, input_max), |
| F2QS(4.00, input_min, input_max), |
| // h = 1 |
| F2QS(-3.00, input_min, input_max), F2QS(8.00, input_min, input_max), |
| F2QS(8.00, input_min, input_max), F2QS(-3.00, input_min, input_max), |
| F2QS(-4.00, input_min, input_max), |
| // h = 2 |
| F2QS(-9.00, input_min, input_max), F2QS(-9.00, input_min, input_max), |
| F2QS(4.00, input_min, input_max), F2QS(-8.00, input_min, input_max), |
| F2QS(-1.00, input_min, input_max), |
| // h = 3 |
| F2QS(-10.00, input_min, input_max), F2QS(-2.00, input_min, input_max), |
| F2QS(6.00, input_min, input_max), F2QS(-7.00, input_min, input_max), |
| F2QS(0.00, input_min, input_max), |
| |
| // n = 1 |
| // c = 0 |
| // h = 0 |
| F2QS(-9.00, input_min, input_max), F2QS(-8.00, input_min, input_max), |
| F2QS(6.00, input_min, input_max), F2QS(-1.00, input_min, input_max), |
| F2QS(-5.00, input_min, input_max), |
| // h = 1 |
| F2QS(-10.00, input_min, input_max), F2QS(-5.00, input_min, input_max), |
| F2QS(-10.00, input_min, input_max), F2QS(7.00, input_min, input_max), |
| F2QS(-2.00, input_min, input_max), |
| // h = 2 |
| F2QS(-5.00, input_min, input_max), F2QS(-4.00, input_min, input_max), |
| F2QS(1.00, input_min, input_max), F2QS(2.00, input_min, input_max), |
| F2QS(2.00, input_min, input_max), |
| // h = 3 |
| F2QS(-2.00, input_min, input_max), F2QS(-2.00, input_min, input_max), |
| F2QS(1.00, input_min, input_max), F2QS(1.00, input_min, input_max), |
| F2QS(-4.00, input_min, input_max), |
| |
| // c = 1 |
| // h = 0 |
| F2QS(-8.00, input_min, input_max), F2QS(-3.00, input_min, input_max), |
| F2QS(1.00, input_min, input_max), F2QS(1.00, input_min, input_max), |
| F2QS(-1.00, input_min, input_max), |
| // h = 1 |
| F2QS(-2.00, input_min, input_max), F2QS(6.00, input_min, input_max), |
| F2QS(-1.00, input_min, input_max), F2QS(-5.00, input_min, input_max), |
| F2QS(6.00, input_min, input_max), |
| // h = 2 |
| F2QS(-7.00, input_min, input_max), F2QS(8.00, input_min, input_max), |
| F2QS(9.00, input_min, input_max), F2QS(0.00, input_min, input_max), |
| F2QS(9.00, input_min, input_max), |
| // h = 3 |
| F2QS(-9.00, input_min, input_max), F2QS(-5.00, input_min, input_max), |
| F2QS(-2.00, input_min, input_max), F2QS(0.00, input_min, input_max), |
| F2QS(8.00, input_min, input_max), |
| |
| // c = 2 |
| // h = 0 |
| F2QS(4.00, input_min, input_max), F2QS(2.00, input_min, input_max), |
| F2QS(-3.00, input_min, input_max), F2QS(5.00, input_min, input_max), |
| F2QS(8.00, input_min, input_max), |
| // h = 1 |
| F2QS(-1.00, input_min, input_max), F2QS(1.00, input_min, input_max), |
| F2QS(-4.00, input_min, input_max), F2QS(-9.00, input_min, input_max), |
| F2QS(7.00, input_min, input_max), |
| // h = 2 |
| F2QS(3.00, input_min, input_max), F2QS(-8.00, input_min, input_max), |
| F2QS(0.00, input_min, input_max), F2QS(9.00, input_min, input_max), |
| F2QS(-4.00, input_min, input_max), |
| // h = 3 |
| F2QS(8.00, input_min, input_max), F2QS(-1.00, input_min, input_max), |
| F2QS(9.00, input_min, input_max), F2QS(-9.00, input_min, input_max), |
| F2QS(1.00, input_min, input_max)}, |
| input_min, input_max, // Input quantized range. |
| { // Expected results. |
| // n = 0 |
| // c = 0 |
| // h = 0 |
| F2QS(0.042009463, output_min, output_max), |
| F2QS(0.843782625, output_min, output_max), |
| F2QS(0.000014093, output_min, output_max), |
| F2QS(0.114193561, output_min, output_max), |
| F2QS(0.000000258, output_min, output_max), |
| // h = 1 |
| F2QS(0.000003072, output_min, output_max), |
| F2QS(0.000003072, output_min, output_max), |
| F2QS(0.000022699, output_min, output_max), |
| F2QS(0.499985578, output_min, output_max), |
| F2QS(0.499985578, output_min, output_max), |
| // h = 2 |
| F2QS(0.952571219, output_min, output_max), |
| F2QS(0.000002153, output_min, output_max), |
| F2QS(0.000000107, output_min, output_max), |
| F2QS(0.047425728, output_min, output_max), |
| F2QS(0.000000792, output_min, output_max), |
| // h = 3 |
| F2QS(0.000000826, output_min, output_max), |
| F2QS(0.993305397, output_min, output_max), |
| F2QS(0.006692839, output_min, output_max), |
| F2QS(0.000000112, output_min, output_max), |
| F2QS(0.000000826, output_min, output_max), |
| |
| // c = 1 |
| // h = 0 |
| F2QS(0.731046347, output_min, output_max), |
| F2QS(0.268936922, output_min, output_max), |
| F2QS(0.000000030, output_min, output_max), |
| F2QS(0.000012210, output_min, output_max), |
| F2QS(0.000004492, output_min, output_max), |
| // h = 1 |
| F2QS(0.000717124, output_min, output_max), |
| F2QS(0.106430599, output_min, output_max), |
| F2QS(0.786421666, output_min, output_max), |
| F2QS(0.000000012, output_min, output_max), |
| F2QS(0.106430599, output_min, output_max), |
| // h = 2 |
| F2QS(0.000006114, output_min, output_max), |
| F2QS(0.000045174, output_min, output_max), |
| F2QS(0.995015917, output_min, output_max), |
| F2QS(0.002466398, output_min, output_max), |
| F2QS(0.002466398, output_min, output_max), |
| // h = 3 |
| F2QS(0.022595176, output_min, output_max), |
| F2QS(0.453836234, output_min, output_max), |
| F2QS(0.453836234, output_min, output_max), |
| F2QS(0.008312301, output_min, output_max), |
| F2QS(0.061420055, output_min, output_max), |
| |
| // c = 2 |
| // h = 0 |
| F2QS(0.875505904, output_min, output_max), |
| F2QS(0.118486839, output_min, output_max), |
| F2QS(0.000000099, output_min, output_max), |
| F2QS(0.000108046, output_min, output_max), |
| F2QS(0.005899112, output_min, output_max), |
| // h = 1 |
| F2QS(0.000008351, output_min, output_max), |
| F2QS(0.499990113, output_min, output_max), |
| F2QS(0.499990113, output_min, output_max), |
| F2QS(0.000008351, output_min, output_max), |
| F2QS(0.000003072, output_min, output_max), |
| // h = 2 |
| F2QS(0.000002245, output_min, output_max), |
| F2QS(0.000002245, output_min, output_max), |
| F2QS(0.993296627, output_min, output_max), |
| F2QS(0.000006103, output_min, output_max), |
| F2QS(0.006692780, output_min, output_max), |
| // h = 3 |
| F2QS(0.000000112, output_min, output_max), |
| F2QS(0.000334520, output_min, output_max), |
| F2QS(0.997191323, output_min, output_max), |
| F2QS(0.000002254, output_min, output_max), |
| F2QS(0.002471790, output_min, output_max), |
| |
| // n = 1 |
| // c = 0 |
| // h = 0 |
| F2QS(0.000000306, output_min, output_max), |
| F2QS(0.000000831, output_min, output_max), |
| F2QS(0.999071142, output_min, output_max), |
| F2QS(0.000911035, output_min, output_max), |
| F2QS(0.000016686, output_min, output_max), |
| // h = 1 |
| F2QS(0.000000041, output_min, output_max), |
| F2QS(0.000006143, output_min, output_max), |
| F2QS(0.000000041, output_min, output_max), |
| F2QS(0.999870380, output_min, output_max), |
| F2QS(0.000123394, output_min, output_max), |
| // h = 2 |
| F2QS(0.000384554, output_min, output_max), |
| F2QS(0.001045327, output_min, output_max), |
| F2QS(0.155140254, output_min, output_max), |
| F2QS(0.421714933, output_min, output_max), |
| F2QS(0.421714933, output_min, output_max), |
| // h = 3 |
| F2QS(0.023637081, output_min, output_max), |
| F2QS(0.023637081, output_min, output_max), |
| F2QS(0.474763454, output_min, output_max), |
| F2QS(0.474763454, output_min, output_max), |
| F2QS(0.003198931, output_min, output_max), |
| |
| // c = 1 |
| // h = 0 |
| F2QS(0.000057299, output_min, output_max), |
| F2QS(0.008503973, output_min, output_max), |
| F2QS(0.464301197, output_min, output_max), |
| F2QS(0.464301197, output_min, output_max), |
| F2QS(0.062836334, output_min, output_max), |
| // h = 1 |
| F2QS(0.000167625, output_min, output_max), |
| F2QS(0.499684188, output_min, output_max), |
| F2QS(0.000455653, output_min, output_max), |
| F2QS(0.000008346, output_min, output_max), |
| F2QS(0.499684188, output_min, output_max), |
| // h = 2 |
| F2QS(0.000000048, output_min, output_max), |
| F2QS(0.155354299, output_min, output_max), |
| F2QS(0.422296769, output_min, output_max), |
| F2QS(0.000052116, output_min, output_max), |
| F2QS(0.422296769, output_min, output_max), |
| // h = 3 |
| F2QS(0.000000041, output_min, output_max), |
| F2QS(0.000002259, output_min, output_max), |
| F2QS(0.000045383, output_min, output_max), |
| F2QS(0.000335334, output_min, output_max), |
| F2QS(0.999616982, output_min, output_max), |
| |
| // c = 2 |
| // h = 0 |
| F2QS(0.017107856, output_min, output_max), |
| F2QS(0.002315297, output_min, output_max), |
| F2QS(0.000015600, output_min, output_max), |
| F2QS(0.046503973, output_min, output_max), |
| F2QS(0.934057274, output_min, output_max), |
| // h = 1 |
| F2QS(0.000334516, output_min, output_max), |
| F2QS(0.002471755, output_min, output_max), |
| F2QS(0.000016655, output_min, output_max), |
| F2QS(0.000000112, output_min, output_max), |
| F2QS(0.997176963, output_min, output_max), |
| // h = 2 |
| F2QS(0.002472313, output_min, output_max), |
| F2QS(0.000000041, output_min, output_max), |
| F2QS(0.000123089, output_min, output_max), |
| F2QS(0.997402302, output_min, output_max), |
| F2QS(0.000002254, output_min, output_max), |
| // h = 3 |
| F2QS(0.268866557, output_min, output_max), |
| F2QS(0.000033181, output_min, output_max), |
| F2QS(0.730855076, output_min, output_max), |
| F2QS(0.000000011, output_min, output_max), |
| F2QS(0.000245175, output_min, output_max)}, |
| {4, 2, 3, 4, 5}, // Output shape. |
| output_min, output_max, // Output quantized range. |
| output_data); |
| } |
| |
| TF_LITE_MICRO_TESTS_END |
