/* * 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 #include #include #include using namespace tflite; using namespace nnfw::tflite; TEST(NNAPI_Quickcheck_logistic_quan_1, simple_test) { int verbose = 0; 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 "logistic_quan_1.lst" #undef INT_VALUE const int32_t IFM_N = IFM_N_Value(); const int32_t IFM_C = IFM_C_Value(); const int32_t IFM_H = IFM_H_Value(); const int32_t IFM_W = IFM_W_Value(); const int32_t OFM_N = IFM_N; const int32_t OFM_C = IFM_C; const int32_t OFM_H = IFM_H; const int32_t OFM_W = IFM_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(IFM_N); PRINT_VALUE(IFM_C); PRINT_VALUE(IFM_H); PRINT_VALUE(IFM_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 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); TfLiteQuantizationParams in_quantization; in_quantization.scale = 0.5f; in_quantization.zero_point = 0; TfLiteQuantizationParams out_quantization; out_quantization.scale = 1.f / 256; out_quantization.zero_point = 0; // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N) interp.AddTensors(2); // Configure output interp.SetTensorParametersReadWrite(0, kTfLiteUInt8 /* type */, "output" /* name */, {OFM_N, OFM_H, OFM_W, OFM_C} /* dims */, out_quantization); // Configure input interp.SetTensorParametersReadWrite(1, kTfLiteUInt8 /* type */, "input" /* name */, {IFM_N, IFM_H, IFM_W, IFM_C} /* dims */, in_quantization); // Add Logistic Node // Run Logistic and store the result into Tensor #0 // - Read input from Tensor #1 interp.AddNodeWithParameters({1}, {0}, nullptr, 0, nullptr, BuiltinOpResolver().FindOp(BuiltinOperator_LOGISTIC, 1)); interp.SetInputs({1}); 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); }