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Diffstat (limited to 'tools/nnapi_quickcheck/tests/gather_2.cpp')
-rw-r--r-- | tools/nnapi_quickcheck/tests/gather_2.cpp | 136 |
1 files changed, 136 insertions, 0 deletions
diff --git a/tools/nnapi_quickcheck/tests/gather_2.cpp b/tools/nnapi_quickcheck/tests/gather_2.cpp new file mode 100644 index 000000000..b3cb3c6ef --- /dev/null +++ b/tools/nnapi_quickcheck/tests/gather_2.cpp @@ -0,0 +1,136 @@ +/* + * 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/interp/FunctionBuilder.h" + +#include <chrono> +#include <iostream> + +using namespace tflite; +using namespace tflite::ops::builtin; + +TEST(NNAPI_Quickcheck_gather_2, simple_test) +{ + // Set random seed + int SEED = std::chrono::system_clock::now().time_since_epoch().count(); + + nnfw::util::env::IntAccessor("SEED").access(SEED); + + // Set random test parameters + 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 "gather_2.lst" +#undef INT_VALUE + + const int32_t INPUT_DATA_H = INPUT_DATA_H_Value(); + const int32_t INPUT_DATA_W = INPUT_DATA_W_Value(); + const int32_t INDEX_DATA = INDEX_DATA_Value(); + + const int32_t OUTPUT_DATA_H = INPUT_DATA_H; + const int32_t OUTPUT_DATA_W = INDEX_DATA; + + 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(INPUT_DATA_H); + PRINT_VALUE(INPUT_DATA_W); + PRINT_VALUE(INDEX_DATA); + PRINT_NEWLINE(); + + PRINT_VALUE(OUTPUT_DATA_H); + PRINT_VALUE(OUTPUT_DATA_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); + // + // Q: Is this necessary? + TfLiteQuantizationParams quantization; + + quantization.scale = 1; + quantization.zero_point = 0; + + // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N) + interp.AddTensors(3); + + // Configure INPUT_DATA + interp.SetTensorParametersReadWrite(0, kTfLiteFloat32 /* type */, "input" /* name */, + {INPUT_DATA_H, INPUT_DATA_W} /* dims */, quantization); + + // Configure INDEX_DATA + interp.SetTensorParametersReadWrite(1, kTfLiteInt32 /* type */, "index" /* name */, + {INDEX_DATA} /* dims */, quantization); + + // Configure OUTPUT_VALUES + interp.SetTensorParametersReadWrite(2, kTfLiteFloat32 /* type */, "output_data" /* name */, + {OUTPUT_DATA_H, OUTPUT_DATA_W} /* dims */, quantization); + + auto *param = reinterpret_cast<TfLiteGatherParams *>(malloc(sizeof(TfLiteGatherParams))); + + param->axis = 0; + + // Add GATHER Node + // Run GATHER and store its result into Tensor #2 + // - Read input data and index_data from Tensor #0 and #1, respectively + interp.AddNodeWithParameters({0, 1}, {2}, nullptr, 0, reinterpret_cast<void *>(param), + BuiltinOpResolver().FindOp(BuiltinOperator_GATHER, 1)); + + // Set Tensor #0 and #1 as Input, and Tensor #2 as Output + interp.SetInputs({0, 1}); + interp.SetOutputs({2}); + }; + + 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); +} |