diff options
Diffstat (limited to 'tools/nnapi_quickcheck/tests/split_1.cpp')
| -rw-r--r-- | tools/nnapi_quickcheck/tests/split_1.cpp | 153 |
1 files changed, 153 insertions, 0 deletions
diff --git a/tools/nnapi_quickcheck/tests/split_1.cpp b/tools/nnapi_quickcheck/tests/split_1.cpp new file mode 100644 index 000000000..742c5dbed --- /dev/null +++ b/tools/nnapi_quickcheck/tests/split_1.cpp @@ -0,0 +1,153 @@ +/* + * 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 "util/feature/Shape.h" + +#include "support/tflite/Diff.h" +#include "support/tflite/Quantization.h" +#include "support/tflite/interp/FunctionBuilder.h" + +#include <chrono> +#include <random> +#include <iostream> +#include <cassert> + +using namespace tflite; +using namespace tflite::ops::builtin; + +TEST(NNAPI_Quickcheck_split_1, simple_test) +{ + int verbose = 0; + int tolerance = 1; + + nnfw::util::env::IntAccessor("VERBOSE").access(verbose); + nnfw::util::env::IntAccessor("TOLERANCE").access(tolerance); + +#define INT_VALUE(NAME, VALUE) IntVar NAME##_Value(#NAME, VALUE); +#include "split_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 NUM_SPLIT = NUM_SPLIT_Value(); + const int32_t AXIS = AXIS_Value(); + + // Set random seed + int SEED = std::chrono::system_clock::now().time_since_epoch().count(); + + nnfw::util::env::IntAccessor("SEED").access(SEED); + + // 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_VALUE(NUM_SPLIT); + PRINT_VALUE(AXIS); +#undef PRINT_VALUE +#undef PRINT_NEWLINE + + 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; + const int32_t axis[1] = {AXIS}; + + 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(NUM_SPLIT + 2); + + // Configure Input Tensor(s) + interp.SetTensorParametersReadOnly(0, kTfLiteInt32 /* type */, "axis" /* name */, + {1} /* dims */, quantization, + reinterpret_cast<const char *>(axis), 1 * sizeof(int32_t)); + + interp.SetTensorParametersReadWrite(1, kTfLiteFloat32 /* type */, "input" /* name */, + {IFM_N, IFM_H, IFM_W, IFM_C} /* dims */, quantization); + + // Configure Output Tensor + std::vector<int> ofm_indexes; + + for (uint32_t n = 0; n < NUM_SPLIT; ++n) + { + const auto ofm_index = 2 + n; + + interp.SetTensorParametersReadWrite(ofm_index, kTfLiteFloat32 /* type */, "output" /* name */, + {OFM_N, OFM_H, OFM_W, OFM_C} /* dims */, quantization); + + ofm_indexes.emplace_back(ofm_index); + } + + auto *param = reinterpret_cast<TfLiteSplitParams *>(malloc(sizeof(TfLiteSplitParams))); + + param->num_splits = NUM_SPLIT; + + // Add SPLIT Node + // Run SPLIT and store its result into Tensor #0 + // - Read axis and IFM from Tensor #0 and #1, respectively + interp.AddNodeWithParameters({0, 1}, ofm_indexes, nullptr, 0, reinterpret_cast<void *>(param), + BuiltinOpResolver().FindOp(BuiltinOperator_SPLIT, 1)); + + // Set Tensor #1 as Input #0, and Tensor #2 ~ #NUM_SPLIT+1 as Output #0 + interp.SetInputs({1}); + interp.SetOutputs(ofm_indexes); + }; + + 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); +} |