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Diffstat (limited to 'tools/nnapi_quickcheck/tests/add_8.cpp')
| -rw-r--r-- | tools/nnapi_quickcheck/tests/add_8.cpp | 190 |
1 files changed, 0 insertions, 190 deletions
diff --git a/tools/nnapi_quickcheck/tests/add_8.cpp b/tools/nnapi_quickcheck/tests/add_8.cpp deleted file mode 100644 index d89e977d5..000000000 --- a/tools/nnapi_quickcheck/tests/add_8.cpp +++ /dev/null @@ -1,190 +0,0 @@ -/* - * Copyright (c) 2018 Samsung Electronics Co., Ltd. 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 "gtest/gtest.h" - -#include "tflite/ext/kernels/register.h" -#include "tensorflow/lite/model.h" -#include "tensorflow/lite/builtin_op_data.h" - -#include "env.h" -#include "memory.h" -#include "misc/environment.h" - -#include "tflite/Diff.h" -#include "tflite/Quantization.h" -#include "tflite/interp/FunctionBuilder.h" - -#include <iostream> -#include <cassert> - -#include <chrono> -#include <random> - -using namespace tflite; -using namespace nnfw::tflite; - -TEST(NNAPI_Quickcheck_add_8, simple_test) -{ - int verbose = 1; - int tolerance = 1; - - nnfw::misc::env::IntAccessor("VERBOSE").access(verbose); - nnfw::misc::env::IntAccessor("TOLERANCE").access(tolerance); - - // Set random seed - int SEED = std::chrono::system_clock::now().time_since_epoch().count(); - - nnfw::misc::env::IntAccessor("SEED").access(SEED); - -#define INT_VALUE(NAME, VALUE) IntVar NAME##_Value(#NAME, VALUE); -#include "add_8.lst" -#undef INT_VALUE - - const int32_t LEFT_N = LEFT_N_Value(); - const int32_t LEFT_C = LEFT_C_Value(); - const int32_t LEFT_H = LEFT_H_Value(); - const int32_t LEFT_W = LEFT_W_Value(); - - const int32_t RIGHT_N = RIGHT_N_Value(); - const int32_t RIGHT_C = RIGHT_C_Value(); - const int32_t RIGHT_H = RIGHT_H_Value(); - const int32_t RIGHT_W = RIGHT_W_Value(); - - const int32_t OFM_N = std::max(LEFT_N, RIGHT_N); - const int32_t OFM_C = std::max(LEFT_C, RIGHT_C); - const int32_t OFM_H = std::max(LEFT_H, RIGHT_H); - const int32_t OFM_W = std::max(LEFT_W, RIGHT_W); - - // Initialize random number generator - std::minstd_rand random(SEED); - - std::cout << "Configurations:" << std::endl; -#define PRINT_NEWLINE() \ - { \ - std::cout << std::endl; \ - } -#define PRINT_VALUE(value) \ - { \ - std::cout << " " << #value << ": " << (value) << std::endl; \ - } - PRINT_VALUE(SEED); - PRINT_NEWLINE(); - - PRINT_VALUE(LEFT_N); - PRINT_VALUE(LEFT_C); - PRINT_VALUE(LEFT_H); - PRINT_VALUE(LEFT_W); - PRINT_NEWLINE(); - - PRINT_VALUE(RIGHT_N); - PRINT_VALUE(RIGHT_C); - PRINT_VALUE(RIGHT_H); - PRINT_VALUE(RIGHT_W); - PRINT_NEWLINE(); - - PRINT_VALUE(OFM_N); - PRINT_VALUE(OFM_C); - PRINT_VALUE(OFM_H); - PRINT_VALUE(OFM_W); -#undef PRINT_VALUE -#undef PRINT_NEWLINE - - // Configure left data - const uint32_t left_size = LEFT_N * LEFT_C * LEFT_H * LEFT_W; - const uint32_t right_size = RIGHT_N * RIGHT_C * RIGHT_H * RIGHT_W; - float left_data[left_size] = { - 0.0f, - }; - float right_data[right_size] = { - 0.0f, - }; - - // Fill left data with random data - { - std::normal_distribution<float> left_dist(-1.0f, +1.0f); - int value = 10; - for (uint32_t off = 0; off < left_size; ++off) - { - left_data[off] = value; - std::cout << left_data[off] << std::endl; - } - value = 1; - for (uint32_t off = 0; off < right_size; ++off) - { - right_data[off] = value++; - std::cout << right_data[off] << std::endl; - } - } - - auto setup = [&](Interpreter &interp) { - // Comment from 'context.h' - // - // Parameters for asymmetric quantization. Quantized values can be converted - // back to float using: - // real_value = scale * (quantized_value - zero_point); - // - // Q: Is this necessary? - TfLiteQuantizationParams quantization = make_default_quantization(); - - // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N) - interp.AddTensors(3); - - // Configure output - interp.SetTensorParametersReadWrite(0, kTfLiteFloat32 /* type */, "output" /* name */, - {OFM_N, OFM_H, OFM_W, OFM_C} /* dims */, quantization); - - // Configure input(s) - interp.SetTensorParametersReadOnly(1, kTfLiteFloat32 /* type */, "left" /* name */, - {LEFT_N, LEFT_H, LEFT_W, LEFT_C} /* dims */, quantization, - reinterpret_cast<const char *>(left_data), - left_size * sizeof(float)); - - // Configure input(s) - interp.SetTensorParametersReadOnly( - 2, kTfLiteFloat32 /* type */, "right" /* name */, {RIGHT_C} /* dims */, quantization, - //{RIGHT_W, RIGHT_C} /* dims */, quantization, - reinterpret_cast<const char *>(right_data), right_size * sizeof(float)); - - // Add Convolution Node - // - // NOTE AddNodeWithParameters take the ownership of param, and deallocate it with free - // So, param should be allocated with malloc - auto param = make_alloc<TfLiteAddParams>(); - - param->activation = kTfLiteActNone; - - // Run Add and store the result into Tensor #0 - // - Read LHS from Tensor #1 - // - Read RHS from Tensor #2, - interp.AddNodeWithParameters({1, 2}, {0}, nullptr, 0, reinterpret_cast<void *>(param), - BuiltinOpResolver().FindOp(BuiltinOperator_ADD, 1)); - - interp.SetInputs({}); - interp.SetOutputs({0}); - }; - - const nnfw::tflite::FunctionBuilder builder(setup); - - RandomTestParam param; - - param.verbose = verbose; - param.tolerance = tolerance; - - int res = RandomTestRunner{SEED, param}.run(builder); - - EXPECT_EQ(res, 0); -} |