2 * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
8 * http://www.apache.org/licenses/LICENSE-2.0
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
17 #include "gtest/gtest.h"
19 #include "tflite/ext/kernels/register.h"
20 #include "tensorflow/lite/model.h"
21 #include "tensorflow/lite/builtin_op_data.h"
25 #include "misc/environment.h"
27 #include "tflite/Diff.h"
28 #include "tflite/Quantization.h"
29 #include "tflite/interp/FunctionBuilder.h"
37 using namespace tflite;
38 using namespace nnfw::tflite;
40 TEST(NNAPI_Quickcheck_concat_1, simple_test)
45 nnfw::misc::env::IntAccessor("VERBOSE").access(verbose);
46 nnfw::misc::env::IntAccessor("TOLERANCE").access(tolerance);
49 int SEED = std::chrono::system_clock::now().time_since_epoch().count();
51 nnfw::misc::env::IntAccessor("SEED").access(SEED);
53 #define INT_VALUE(NAME, VALUE) IntVar NAME##_Value(#NAME, VALUE);
54 #include "concat_1.lst"
57 // TODO Allow users to set concat axis!
58 const int32_t CONCAT_COUNT = CONCAT_COUNT_Value();
60 const int32_t IFM_H = IFM_H_Value();
61 const int32_t IFM_W = IFM_W_Value();
64 const int32_t OFM_H = IFM_H;
65 const int32_t OFM_W = IFM_W;
67 std::cout << "Configurations:" << std::endl;
68 #define PRINT_NEWLINE() \
70 std::cout << std::endl; \
72 #define PRINT_VALUE(value) \
74 std::cout << " " << #value << ": " << (value) << std::endl; \
79 PRINT_VALUE(CONCAT_COUNT);
87 // Randomize IFM depth
88 std::default_random_engine generator(SEED);
89 std::uniform_int_distribution<int> distribution(1, 8);
91 std::vector<int32_t> depths;
93 for (int32_t n = 0; n < CONCAT_COUNT; ++n)
95 const auto depth = distribution(generator);
98 depths.emplace_back(depth);
101 auto setup = [&](Interpreter &interp) {
102 // Comment from 'context.h'
104 // Parameters for asymmetric quantization. Quantized values can be converted
105 // back to float using:
106 // real_value = scale * (quantized_value - zero_point);
108 // Q: Is this necessary?
109 TfLiteQuantizationParams quantization = make_default_quantization();
111 // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N)
112 interp.AddTensors(depths.size() + 1);
115 interp.SetTensorParametersReadWrite(0, kTfLiteFloat32 /* type */, "output" /* name */,
116 {1 /*N*/, OFM_H, OFM_W, OFM_C} /* dims */, quantization);
119 std::vector<int> ifm_indexes;
121 for (uint32_t n = 0; n < depths.size(); ++n)
123 const auto ifm_index = 1 + n;
124 const auto IFM_C = depths.at(n);
126 interp.SetTensorParametersReadWrite(ifm_index, kTfLiteFloat32 /* type */, "input" /* name */,
127 {1 /*N*/, IFM_H, IFM_W, IFM_C} /* dims */, quantization);
129 ifm_indexes.emplace_back(ifm_index);
134 // NOTE AddNodeWithParameters take the ownership of param, and deallocate it with free
135 // So, param should be allocated with malloc
136 auto param = make_alloc<TfLiteConcatenationParams>();
138 param->activation = kTfLiteActNone;
141 // Run Convolution and store its result into Tensor #0
142 // - Read IFM from Tensor #1
143 interp.AddNodeWithParameters(ifm_indexes, {0}, nullptr, 0, reinterpret_cast<void *>(param),
144 BuiltinOpResolver().FindOp(BuiltinOperator_CONCATENATION, 1));
146 // Set Tensor #1 as Input #0, and Tensor #0 as Output #0
147 interp.SetInputs(ifm_indexes);
148 interp.SetOutputs({0});
151 const nnfw::tflite::FunctionBuilder builder(setup);
153 RandomTestParam param;
155 param.verbose = verbose;
156 param.tolerance = tolerance;
158 int res = RandomTestRunner{SEED, param}.run(builder);