1 files changed, 138 insertions, 0 deletions
diff --git a/tools/nnapi_quickcheck/tests/topk_v2_1.cpp b/tools/nnapi_quickcheck/tests/topk_v2_1.cpp
new file mode 100644
index 000000000..bb9d8535e
--- /dev/null
+++ b/tools/nnapi_quickcheck/tests/topk_v2_1.cpp
@@ -0,0 +1,138 @@
+/*
+ * 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 <chrono>
+#include <iostream>
+
+using namespace tflite;
+using namespace tflite::ops::builtin;
+
+TEST(NNAPI_Quickcheck_topk_v2_1, 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 "topk_v2_1.lst"
+#undef INT_VALUE
+
+  const int32_t INPUT_DATA = INPUT_DATA_Value();
+  const int32_t K = K_Value();
+
+  const int32_t OUTPUT_VALUES = K;
+  const int32_t OUTPUT_INDICES = K;
+
+  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);
+  PRINT_VALUE(K);
+  PRINT_NEWLINE();
+
+  PRINT_VALUE(OUTPUT_VALUES);
+  PRINT_VALUE(OUTPUT_INDICES);
+#undef PRINT_VALUE
+#undef PRINT_NEWLINE
+
+  // Fill the K data
+  int32_t k_data[1] = {K};
+
+  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?
+    // A: This may be necessary, because quantization values(scale, zero_point) of TENSOR_INT32 and
+    // TENSOR_QUANT8_ASYMM are passed on to the runtime.
+    TfLiteQuantizationParams quantization = make_default_quantization();
+
+    // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N)
+    interp.AddTensors(4);
+
+    // Configure INPUT_DATA
+    interp.SetTensorParametersReadWrite(0, kTfLiteFloat32 /* type */, "input" /* name */,
+                                        {INPUT_DATA} /* dims */, quantization);
+
+    // Configure K
+    interp.SetTensorParametersReadOnly(1, kTfLiteInt32 /* type */, "k" /* name */, {1} /* dims */,
+                                       quantization, reinterpret_cast<const char *>(k_data),
+                                       sizeof(k_data));
+
+    // Configure OUTPUT_VALUES
+    interp.SetTensorParametersReadWrite(2, kTfLiteFloat32 /* type */, "output_values" /* name */,
+                                        {OUTPUT_VALUES} /* dims */, quantization);
+
+    // Configure OUTPUT_INDICES
+    interp.SetTensorParametersReadWrite(3, kTfLiteInt32 /* type */, "output_indices" /* name */,
+                                        {OUTPUT_INDICES} /* dims */, quantization);
+
+    // Add TopK_V2 Node
+    // Run TopK_V2 and store its result into Tensor #2 and #3
+    //  - Read input data and K from Tensor #0 and #1, respectively
+    interp.AddNodeWithParameters({0, 1}, {2, 3}, nullptr, 0, nullptr,
+                                 BuiltinOpResolver().FindOp(BuiltinOperator_TOPK_V2, 1));
+
+    // Set Tensor #0 as Input, and Tensor #2 and #3 as Output
+    interp.SetInputs({0});
+    interp.SetOutputs({2, 3});
+  };
+
+  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);
+}