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"
26 #include "misc/feature/Shape.h"
28 #include "tflite/Diff.h"
29 #include "tflite/Quantization.h"
30 #include "tflite/interp/FunctionBuilder.h"
37 using namespace tflite;
38 using namespace nnfw::tflite;
40 TEST(NNAPI_Quickcheck_softmax_2, simple_test)
45 nnfw::misc::env::IntAccessor("VERBOSE").access(verbose);
46 nnfw::misc::env::IntAccessor("TOLERANCE").access(tolerance);
48 #define FLOAT_VALUE(NAME, VALUE) FloatVar NAME##_Value(#NAME, VALUE);
49 #define INT_VALUE(NAME, VALUE) IntVar NAME##_Value(#NAME, VALUE);
50 #include "softmax_2.lst"
54 const int32_t IFM_C = 1;
55 const int32_t IFM_H = IFM_H_Value();
56 const int32_t IFM_W = IFM_W_Value();
57 const float BETA = BETA_Value();
59 #define PRINT_NEWLINE() \
61 std::cout << std::endl; \
63 #define PRINT_VALUE(value) \
65 std::cout << " " << #value << ": " << (value) << std::endl; \
76 int SEED = std::chrono::system_clock::now().time_since_epoch().count();
78 nnfw::misc::env::IntAccessor("SEED").access(SEED);
80 // Initialize random number generator
81 std::minstd_rand random(SEED);
83 const nnfw::misc::feature::Shape ifm_shape{IFM_C, IFM_H, IFM_W};
85 const int32_t OFM_C = IFM_C;
86 const int32_t OFM_H = IFM_H;
87 const int32_t OFM_W = IFM_W;
89 auto setup = [&](Interpreter &interp) {
90 // Comment from 'context.h'
92 // Parameters for asymmetric quantization. Quantized values can be converted
93 // back to float using:
94 // real_value = scale * (quantized_value - zero_point);
96 // Q: Is this necessary?
97 TfLiteQuantizationParams quantization = make_default_quantization();
99 // On AddTensors(N) call, T/F Lite interpreter creates N tensors whose index is [0 ~ N)
100 interp.AddTensors(2);
102 // Configure Output Tensor
103 interp.SetTensorParametersReadWrite(0, kTfLiteFloat32 /* type */, "output" /* name */,
104 {1, IFM_H * IFM_W} /* dims */, quantization);
106 // Configure Input Tensor
107 interp.SetTensorParametersReadWrite(1, kTfLiteFloat32 /* type */, "input" /* name */,
108 {1, IFM_H * IFM_W} /* batch_size, input_size */,
113 // NOTE AddNodeWithParameters take the ownership of param, and deallocate it with free
114 // So, param should be allocated with malloc
115 auto param = make_alloc<TfLiteSoftmaxParams>();
119 // Run Softmax and store its result into Tensor #0
120 // - Read IFM from Tensor #1
121 interp.AddNodeWithParameters({1}, {0}, nullptr, 0, reinterpret_cast<void *>(param),
122 BuiltinOpResolver().FindOp(BuiltinOperator_SOFTMAX, 1));
124 // Set Tensor #1 as Input #0, and Tensor #0 as Output #0
125 interp.SetInputs({1});
126 interp.SetOutputs({0});
129 const nnfw::tflite::FunctionBuilder builder(setup);
131 RandomTestParam param;
133 param.verbose = verbose;
134 param.tolerance = tolerance;
136 int res = RandomTestRunner{SEED, param}.run(builder);