Files
ncnn/tests/test_unaryop.cpp
kongxin 776cd837c3 vulkan: use roundEven for UnaryOp round (#7119)
GLSL round() leaves the direction of halfway cases to the implementation.
MoltenVK rounds them away from zero, while every cpu implementation rounds
half to even, so 0.5 / 2.5 / -0.5 came out as 1 / 3 / -1 on Apple gpus.

Add exact halfway inputs to test_unaryop for op_type 18.
2026-10-17 18:28:49 +08:00

175 lines
4.2 KiB
C++

// Copyright 2020 Tencent
// SPDX-License-Identifier: BSD-3-Clause
#include "testutil.h"
#include "layer_type.h"
#include <limits.h>
#define OP_TYPE_MAX 28
static int op_type = 0;
static int test_unaryop(const ncnn::Mat& _a, int flag = 0)
{
ncnn::Mat a = _a;
if (op_type == 2 || op_type == 3)
{
// large dynamic range for floor ceil
for (int i = 0; i < a.total(); i++)
{
a[i] *= 1000;
}
}
if (op_type == 5 || op_type == 6 || op_type == 8 || op_type == 17)
{
// value must be positive for sqrt rsqrt log
Randomize(a, 0.001f, 2.f);
}
if (op_type == 25)
{
// value must be >= 1 for acosh
Randomize(a, 1.001f, 2.f);
}
if (op_type == 11 || op_type == 12 || op_type == 13)
{
// smaller range for tan asin acos
Randomize(a, -1.f, 1.f);
}
if (op_type == 26)
{
// keep away from +/-1 so bf16 input casting does not round into the singularity
Randomize(a, -0.99f, 0.99f);
}
if (op_type == 27)
{
// leave margin above -1 for reduced precision log1p
Randomize(a, -0.99f, 2.f);
}
#if __powerpc__
// nearbyintf produces wrong result in halfway cases, why ?
// too troublesome to resolve the compiler or qemu problem
// so just skip them --- nihui
if (op_type == 18)
{
// drop 0.4 ~ 0.6
for (int i = 0; i < a.total(); i++)
{
float v = a[i];
float vv = fabs(v - (int)v);
while (vv > 0.4f && vv < 0.6f)
{
v = RandomFloat(-15, 15);
vv = fabs(v - (int)v);
}
a[i] = v;
}
}
#else
if (op_type == 18)
{
// exact halfway values round to even
const float halfway[8] = {0.5f, 1.5f, 2.5f, 3.5f, -0.5f, -1.5f, -2.5f, -3.5f};
for (int i = 0; i < 8 && i < (int)a.total(); i++)
{
a[i] = halfway[i];
}
}
#endif // __powerpc__
ncnn::ParamDict pd;
pd.set(0, op_type);
std::vector<ncnn::Mat> weights(0);
int ret = test_layer("UnaryOp", pd, weights, a, 0.001, flag);
if (ret != 0)
{
fprintf(stderr, "test_unaryop failed a.dims=%d a=(%d %d %d %d) op_type=%d\n", a.dims, a.w, a.h, a.d, a.c, op_type);
}
return ret;
}
// cpu pack8/pack16 cases reuse the Vulkan pack4 path covered by the pack4 cases
// keep the 1d sizes for dispatch boundary coverage
static int test_unaryop_0()
{
return 0
|| test_unaryop(RandomMat(11, 3, 2, 16), TEST_LAYER_DISABLE_GPU_TESTING)
|| test_unaryop(RandomMat(10, 2, 2, 12))
|| test_unaryop(RandomMat(6, 1, 5, 13));
}
static int test_unaryop_1()
{
return 0
|| test_unaryop(RandomMat(11, 7, 16), TEST_LAYER_DISABLE_GPU_TESTING)
|| test_unaryop(RandomMat(10, 4, 12))
|| test_unaryop(RandomMat(6, 5, 13));
}
static int test_unaryop_2()
{
return 0
|| test_unaryop(RandomMat(12, 16), TEST_LAYER_DISABLE_GPU_TESTING)
|| test_unaryop(RandomMat(10, 12))
|| test_unaryop(RandomMat(14, 15));
}
static int test_unaryop_3()
{
return 0
|| test_unaryop(RandomMat(128))
|| test_unaryop(RandomMat(12))
|| test_unaryop(RandomMat(15));
}
#if NCNN_VALIDATION
static int test_unaryop_load_param()
{
ncnn::ParamDict base;
if (test_layer_param(ncnn::LayerType::UnaryOp, base, 0) != 0)
return -1;
for (int i = 0; i <= 27; i++)
{
if (test_layer_param(ncnn::LayerType::UnaryOp, base, 0, i, 0) != 0)
return -1;
}
const int invalid[] = {-1, 28, INT_MIN, INT_MAX};
for (int i = 0; i < 4; i++)
{
if (test_layer_param(ncnn::LayerType::UnaryOp, base, 0, invalid[i], -1) != 0)
return -1;
}
return 0;
}
#endif // NCNN_VALIDATION
int main()
{
SRAND(7767517);
for (op_type = 0; op_type < OP_TYPE_MAX; op_type++)
{
int ret = 0
|| test_unaryop_0()
|| test_unaryop_1()
|| test_unaryop_2()
|| test_unaryop_3();
if (ret != 0)
return ret;
}
return 0
#if NCNN_VALIDATION
|| test_unaryop_load_param()
#endif // NCNN_VALIDATION
;
}