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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, 190 insertions, 0 deletions
diff --git a/tools/nnapi_quickcheck/tests/add_8.cpp b/tools/nnapi_quickcheck/tests/add_8.cpp new file mode 100644 index 000000000..ec11c3969 --- /dev/null +++ b/tools/nnapi_quickcheck/tests/add_8.cpp @@ -0,0 +1,190 @@ +/* + * 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 "support/tflite/kernels/register.h" +#include "tensorflow/contrib/lite/model.h" +#include "tensorflow/contrib/lite/builtin_op_data.h" + +#include "env.h" +#include "memory.h" +#include "util/environment.h" + +#include "support/tflite/Diff.h" +#include "support/tflite/Quantization.h" +#include "support/tflite/interp/FunctionBuilder.h" + +#include <iostream> +#include <cassert> + +#include <chrono> +#include <random> + +using namespace tflite; +using namespace tflite::ops::builtin; + +TEST(NNAPI_Quickcheck_add_8, simple_test) +{ + int verbose = 1; + int tolerance = 1; + + nnfw::util::env::IntAccessor("VERBOSE").access(verbose); + nnfw::util::env::IntAccessor("TOLERANCE").access(tolerance); + + // Set random seed + int SEED = std::chrono::system_clock::now().time_since_epoch().count(); + + nnfw::util::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::support::tflite::interp::FunctionBuilder builder(setup); + + RandomTestParam param; + + param.verbose = verbose; + param.tolerance = tolerance; + + int res = RandomTestRunner{SEED, param}.run(builder); + + EXPECT_EQ(res, 0); +} |