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ncnn/tests/test_requantize.cpp
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Justin Fung 6a1fce7802 RVV1.0 Packed INT8 Convolution (#6763) 
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: nihui <nihuini@tencent.com>
Co-authored-by: nihui <shuizhuyuanluo@126.com>
2026-10-05 23:03:55 +08:00

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// Copyright 2021 Tencent
// SPDX-License-Identifier: BSD-3-Clause
#include "testutil.h"
#include "layer_type.h"
static int test_requantize(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta)
{
ncnn::ParamDict pd;
pd.set(0, scale_in_data_size);
pd.set(1, scale_out_data_size);
pd.set(2, bias_data_size);
ncnn::Mat activation_params(2);
activation_params[0] = alpha;
activation_params[1] = beta;
pd.set(3, activation_type);
pd.set(4, activation_params);
std::vector<ncnn::Mat> weights(bias_data_size ? 3 : 2);
weights[0] = RandomMat(scale_in_data_size);
weights[1] = RandomMat(scale_out_data_size);
if (bias_data_size)
weights[2] = RandomMat(bias_data_size);
Randomize(weights[0], 0.0001, 0.001);
Randomize(weights[1], 10, 100);
int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING;
int ret = test_layer("Requantize", pd, weights, a, 1, flag);
if (ret != 0)
{
fprintf(stderr, "test_requantize failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]);
}
return ret;
}
static int test_requantize(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size)
{
return 0
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f)
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f)
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f)
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1))
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f)
|| test_requantize(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f);
}
static int test_requantize_relu_empty_activation_params(const ncnn::Mat& a)
{
ncnn::ParamDict pd;
pd.set(0, 1);
pd.set(1, 1);
pd.set(2, 0);
pd.set(3, 1);
std::vector<ncnn::Mat> weights(2);
weights[0] = RandomMat(1);
weights[1] = RandomMat(1);
Randomize(weights[0], 0.0001, 0.001);
Randomize(weights[1], 10, 100);
int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING | TEST_LAYER_DISABLE_AUTO_INPUT_PACKING;
int ret = test_layer("Requantize", pd, weights, a, 1, flag);
if (ret != 0)
{
fprintf(stderr, "test_requantize_relu_empty_activation_params failed a.dims=%d a=(%d %d %d %d)\n", a.dims, a.w, a.h, a.d, a.c);
}
return ret;
}
static int test_requantize_pack1(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta)
{
ncnn::ParamDict pd;
pd.set(0, scale_in_data_size);
pd.set(1, scale_out_data_size);
pd.set(2, bias_data_size);
ncnn::Mat activation_params(2);
activation_params[0] = alpha;
activation_params[1] = beta;
pd.set(3, activation_type);
pd.set(4, activation_params);
std::vector<ncnn::Mat> weights(bias_data_size ? 3 : 2);
weights[0] = RandomMat(scale_in_data_size);
weights[1] = RandomMat(scale_out_data_size);
if (bias_data_size)
weights[2] = RandomMat(bias_data_size);
Randomize(weights[0], 0.0001, 0.001);
Randomize(weights[1], 10, 100);
int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING | TEST_LAYER_DISABLE_AUTO_INPUT_PACKING;
int ret = test_layer("Requantize", pd, weights, a, 1, flag);
if (ret != 0)
{
fprintf(stderr, "test_requantize_pack1 failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]);
}
return ret;
}
static int test_requantize_pack1(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size)
{
return 0
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f)
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f)
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f)
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1))
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f)
|| test_requantize_pack1(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f);
}
static int test_requantize_pack8(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size, int activation_type, float alpha, float beta)
{
ncnn::ParamDict pd;
pd.set(0, scale_in_data_size);
pd.set(1, scale_out_data_size);
pd.set(2, bias_data_size);
ncnn::Mat activation_params(2);
activation_params[0] = alpha;
activation_params[1] = beta;
pd.set(3, activation_type);
pd.set(4, activation_params);
std::vector<ncnn::Mat> weights(bias_data_size ? 3 : 2);
weights[0] = RandomMat(scale_in_data_size);
weights[1] = RandomMat(scale_out_data_size);
if (bias_data_size)
weights[2] = RandomMat(bias_data_size);
Randomize(weights[0], 0.0001, 0.001);
Randomize(weights[1], 10, 100);
int flag = TEST_LAYER_DISABLE_AUTO_INPUT_CASTING;
// ordinary cases cover dims=1/2/3; retain the packed dims=4 cases
if (a.dims != 4)
flag |= TEST_LAYER_DISABLE_GPU_TESTING;
#if !__riscv
flag |= TEST_LAYER_ENABLE_FORCE_INPUT_PACK8;
#endif
int ret = test_layer("Requantize", pd, weights, a, 1, flag);
if (ret != 0)
{
fprintf(stderr, "test_requantize_pack8 failed a.dims=%d a=(%d %d %d %d) scale_in_data_size=%d scale_out_data_size=%d bias_data_size=%d act=%d actparams=[%f,%f]\n", a.dims, a.w, a.h, a.d, a.c, scale_in_data_size, scale_out_data_size, bias_data_size, activation_type, activation_params[0], activation_params[1]);
}
return ret;
}
static int test_requantize_pack8(const ncnn::Mat& a, int scale_in_data_size, int scale_out_data_size, int bias_data_size)
{
return 0
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 0, 0.f, 0.f)
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 1, 0.f, 0.f)
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 2, RandomFloat(0, 1), 0.f)
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 3, RandomFloat(-1, 0), RandomFloat(0, 1))
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 4, 0.f, 0.f)
|| test_requantize_pack8(a, scale_in_data_size, scale_out_data_size, bias_data_size, 5, 0.f, 0.f);
}
static int test_requantize_0()
{
return 0
|| test_requantize_pack1(RandomIntMat(3, 3, 32), 32, 32, 0)
|| test_requantize_pack1(RandomIntMat(3, 3, 64), 1, 1, 64)
|| test_requantize_pack1(RandomIntMat(3, 3, 128), 128, 1, 128)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 12)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 12)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 1)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 12, 0)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 12)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 1)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 1, 12, 0)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 12)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 1)
|| test_requantize_pack1(RandomIntMat(7, 9, 12), 12, 1, 0)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 13)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 13)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 1)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 13, 0)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 13)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 1)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 1, 13, 0)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 13)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 1)
|| test_requantize_pack1(RandomIntMat(3, 5, 13), 13, 1, 0);
}
static int test_requantize_1()
{
return 0
|| test_requantize_pack1(RandomIntMat(9, 32), 32, 32, 0)
|| test_requantize_pack1(RandomIntMat(9, 64), 1, 1, 64)
|| test_requantize_pack1(RandomIntMat(9, 128), 128, 1, 128)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 12)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 12)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 1)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 12, 0)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 12)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 1)
|| test_requantize_pack1(RandomIntMat(17, 12), 1, 12, 0)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 12)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 1)
|| test_requantize_pack1(RandomIntMat(17, 12), 12, 1, 0)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 15)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 15)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 1)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 15, 0)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 15)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 1)
|| test_requantize_pack1(RandomIntMat(19, 15), 1, 15, 0)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 15)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 1)
|| test_requantize_pack1(RandomIntMat(19, 15), 15, 1, 0);
}
static int test_requantize_2()
{
return 0
|| test_requantize_pack1(RandomIntMat(124), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(124), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(127), 1, 1, 1)
|| test_requantize_pack1(RandomIntMat(127), 1, 1, 0)
|| test_requantize_pack1(RandomIntMat(127), 1, 1, 0, 2, 0.f, 0.f)
|| test_requantize_pack1(RandomIntMat(127), 1, 1, 0, 2, RandomFloat(-1, 0), 0.f)
|| test_requantize_relu_empty_activation_params(RandomIntMat(127));
}
static int test_requantize_3()
{
return 0
#ifndef __riscv
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 24)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 1)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 1, 0)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 24)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 1)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 24, 0)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 24)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 1)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 1, 24, 0)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 24)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 1)
|| test_requantize_pack8(RandomIntMat(5, 7, 24), 24, 1, 0)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 24)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 1)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 1, 0)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 24)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 1)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 24, 0)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 24)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 1)
|| test_requantize_pack8(RandomIntMat(15, 24), 1, 24, 0)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 24)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 1)
|| test_requantize_pack8(RandomIntMat(15, 24), 24, 1, 0)
|| test_requantize_pack8(RandomIntMat(128), 1, 1, 1)
|| test_requantize_pack8(RandomIntMat(128), 1, 1, 0);
#else
|| test_requantize(RandomIntMat(5, 7, 24), 1, 1, 24)
|| test_requantize(RandomIntMat(5, 7, 24), 1, 1, 1)
|| test_requantize(RandomIntMat(5, 7, 24), 1, 1, 0)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 24, 24)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 24, 1)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 24, 0)
|| test_requantize(RandomIntMat(5, 7, 24), 1, 24, 24)
|| test_requantize(RandomIntMat(5, 7, 24), 1, 24, 1)
|| test_requantize(RandomIntMat(5, 7, 24), 1, 24, 0)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 1, 24)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 1, 1)
|| test_requantize(RandomIntMat(5, 7, 24), 24, 1, 0)
|| test_requantize(RandomIntMat(15, 24), 1, 1, 24)
|| test_requantize(RandomIntMat(15, 24), 1, 1, 1)
|| test_requantize(RandomIntMat(15, 24), 1, 1, 0)
|| test_requantize(RandomIntMat(15, 24), 24, 24, 24)
|| test_requantize(RandomIntMat(15, 24), 24, 24, 1)
|| test_requantize(RandomIntMat(15, 24), 24, 24, 0)
|| test_requantize(RandomIntMat(15, 24), 1, 24, 24)
|| test_requantize(RandomIntMat(15, 24), 1, 24, 1)
|| test_requantize(RandomIntMat(15, 24), 1, 24, 0)
|| test_requantize(RandomIntMat(15, 24), 24, 1, 24)
|| test_requantize(RandomIntMat(15, 24), 24, 1, 1)
|| test_requantize(RandomIntMat(15, 24), 24, 1, 0)
|| test_requantize(RandomIntMat(128), 1, 1, 1)
|| test_requantize(RandomIntMat(128), 1, 1, 0)
|| test_requantize(RandomIntMat(127), 1, 1, 0, 2, RandomFloat(1, 2), 0.f);
#endif // __riscv
}
static int test_requantize_4()
{
return 0
|| test_requantize_pack1(RandomIntMat(3, 3, 1, 32), 32, 32, 0)
|| test_requantize_pack1(RandomIntMat(3, 3, 1, 64), 1, 1, 64)
|| test_requantize_pack1(RandomIntMat(3, 3, 1, 128), 128, 1, 128)
|| test_requantize_pack8(RandomIntMat(5, 3, 2, 24), 1, 1, 24)
|| test_requantize_pack8(RandomIntMat(5, 3, 2, 24), 24, 24, 0)
|| test_requantize_pack1(RandomIntMat(5, 3, 2, 12), 1, 1, 12)
|| test_requantize_pack1(RandomIntMat(5, 3, 2, 12), 12, 12, 0)
|| test_requantize_pack1(RandomIntMat(3, 5, 3, 13), 1, 13, 13)
|| test_requantize_pack1(RandomIntMat(3, 5, 3, 13), 13, 1, 0);
}
static int test_requantize_activation_params_text()
{
#if NCNN_STRING
const char* params[] = {"0=1 1=1 3=3 -23304=2,-1,2", "0=1 1=1 3=3 -23304=2,-1.0,2.0"};
for (int i = 0; i < 2; i++)
{
TestParamDict pd;
if (pd.load_param(params[i]) != 0 || pd.type(4) != 5 + i)
return -1;
std::vector<ncnn::Mat> weights(2);
weights[0].create(1);
weights[0][0] = 1.f;
weights[1].create(1);
weights[1][0] = 1.f;
ncnn::Mat a(2);
int* p = a;
p[0] = -3;
p[1] = 3;
ncnn::Mat reference(2);
reference[0] = -1.f;
reference[1] = 2.f;
ncnn::Mat b;
int ret = test_layer_naive(ncnn::LayerType::Requantize, pd, weights, a, b, 0);
if (ret == 0)
ret = CompareMat(reference, b, 0.f);
if (ret != 0)
{
fprintf(stderr, "test_requantize_activation_params_text failed params=%s ret=%d\n", params[i], ret);
return ret;
}
const ncnn::Mat original = pd.get(4, ncnn::Mat());
const int* q = original;
if (i == 0 ? (q[0] != -1 || q[1] != 2) : (original[0] != -1.f || original[1] != 2.f))
{
fprintf(stderr, "test_requantize_activation_params_text modified params=%s\n", params[i]);
return -1;
}
}
#endif
return 0;
}
#if NCNN_VALIDATION
static int test_requantize_load_param_activation(const ncnn::ParamDict& base, int activation_type, const ncnn::Mat& activation_params, int expected_ret)
{
ncnn::ParamDict pd = base;
pd.set(3, activation_type);
pd.set(4, activation_params);
return test_layer_param(ncnn::LayerType::Requantize, pd, expected_ret);
}
static int test_requantize_load_param()
{
ncnn::ParamDict base;
base.set(0, 1);
base.set(1, 1);
if (test_layer_param(ncnn::LayerType::Requantize, base, 0) != 0)
return -1;
ncnn::Mat params(2);
params[0] = 0.1f;
params[1] = 0.5f;
int ret = 0
|| test_requantize_load_param_activation(base, 0, ncnn::Mat(), 0)
|| test_requantize_load_param_activation(base, 0, ncnn::Mat(0), 0)
|| test_requantize_load_param_activation(base, 0, params, 0)
|| test_requantize_load_param_activation(base, 0, params.range(0, 1), 0)
|| test_requantize_load_param_activation(base, 1, ncnn::Mat(), 0)
|| test_requantize_load_param_activation(base, 1, ncnn::Mat(0), 0)
|| test_requantize_load_param_activation(base, 1, params, 0)
|| test_requantize_load_param_activation(base, 1, params.range(0, 1), 0)
|| test_requantize_load_param_activation(base, 2, ncnn::Mat(), -1)
|| test_requantize_load_param_activation(base, 2, ncnn::Mat(0), -1)
|| test_requantize_load_param_activation(base, 2, params, 0)
|| test_requantize_load_param_activation(base, 2, params.range(0, 1), 0)
|| test_requantize_load_param_activation(base, 3, ncnn::Mat(), -1)
|| test_requantize_load_param_activation(base, 3, ncnn::Mat(0), -1)
|| test_requantize_load_param_activation(base, 3, params, 0)
|| test_requantize_load_param_activation(base, 3, params.range(0, 1), -1)
|| test_requantize_load_param_activation(base, 4, ncnn::Mat(), 0)
|| test_requantize_load_param_activation(base, 4, ncnn::Mat(0), 0)
|| test_requantize_load_param_activation(base, 4, params, 0)
|| test_requantize_load_param_activation(base, 4, params.range(0, 1), 0)
|| test_requantize_load_param_activation(base, 5, ncnn::Mat(), 0)
|| test_requantize_load_param_activation(base, 5, ncnn::Mat(0), 0)
|| test_requantize_load_param_activation(base, 5, params, 0)
|| test_requantize_load_param_activation(base, 5, params.range(0, 1), 0)
|| test_requantize_load_param_activation(base, 6, ncnn::Mat(), -1)
|| test_requantize_load_param_activation(base, 6, ncnn::Mat(0), -1)
|| test_requantize_load_param_activation(base, 6, params, 0)
|| test_requantize_load_param_activation(base, 6, params.range(0, 1), -1)
|| test_requantize_load_param_activation(base, 7, ncnn::Mat(), -1);
if (ret != 0)
return ret;
if (test_layer_param(ncnn::LayerType::Requantize, base, 4, 1, -1)
|| test_layer_param(ncnn::LayerType::Requantize, base, 4, 1.f, -1))
return -1;
ncnn::Mat missing_data(0);
missing_data.w = 1;
const ncnn::Mat bad[] = {ncnn::Mat(2, (size_t)1u), ncnn::Mat(2, (size_t)2u), ncnn::Mat(2, 2), ncnn::Mat(2, (size_t)16u, 4), missing_data};
for (int i = 0; i < 5; i++)
{
if (test_layer_param(ncnn::LayerType::Requantize, base, 4, bad[i], -1) != 0)
return -1;
}
return 0;
}
static int test_requantize_load_param_text()
{
#if NCNN_STRING
const char* params[] = {"0=1 1=1 3=3 -23304=2,-1,2", "0=1 1=1 3=3 -23304=2,-1.0,2.0"};
for (int i = 0; i < 2; i++)
{
TestParamDict pd;
if (pd.load_param(params[i]) != 0 || pd.type(4) != 5 + i)
return -1;
if (test_layer_param(ncnn::LayerType::Requantize, pd, 0) != 0)
return -1;
}
#endif
return 0;
}
#endif // NCNN_VALIDATION
int main()
{
SRAND(7767517);
return 0
|| test_requantize_4()
|| test_requantize_0()
|| test_requantize_1()
|| test_requantize_2()
|| test_requantize_3()
|| test_requantize_activation_params_text()
#if NCNN_VALIDATION
|| test_requantize_load_param()
|| test_requantize_load_param_text()
#endif // NCNN_VALIDATION
;
}
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