--- /dev/null
+/*
+ * 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 "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;
+
+int main(int argc, char **argv)
+{
+ // 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));
+
+ // 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;
+
+ return RandomTestRunner{SEED, param}.run(builder);
+}