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ncnn/tests/test_deconvolutiondepthwise1d.cpp
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nihui 5ea98309e3 layer param hardening (#7003) 
* harden layer parameter validation

Original patches and author identities:
https://github.com/Tencent/ncnn/pull/6912 (beilzx)
https://github.com/Tencent/ncnn/pull/6919 (FluxMind-O)
https://github.com/Tencent/ncnn/pull/6928 (lxcxjxhx)
https://github.com/Tencent/ncnn/pull/6948 (ktz03)
https://github.com/Tencent/ncnn/pull/6950 (ktz03)
https://github.com/Tencent/ncnn/pull/6971 (LI)
https://github.com/Tencent/ncnn/pull/6974 (LI)
https://github.com/Tencent/ncnn/pull/6977 (LI)

Co-authored-by: beilzx <2069360659@qq.com>
Co-authored-by: FluxMind-O <3283918317@qq.com>
Co-authored-by: lxcxjxhx <lxcxjxhx@users.noreply.github.com>
Co-authored-by: ktz03 <2484593937@qq.com>
Co-authored-by: LI <2484593937@qq.com>
2026-09-15 19:18:46 +08:00

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// Copyright 2022 Tencent
// SPDX-License-Identifier: BSD-3-Clause
#include "testutil.h"
#include "layer_type.h"
#include <limits.h>
static int test_deconvolutiondepthwise1d(int w, int h, int outh, int kernel, int dilation, int stride, int pad, int bias, int group, int output_pad_right, int output_w)
{
ncnn::Mat a = RandomMat(w, h);
if (output_w > 0 && pad != -233 && pad != -234)
{
pad = -233;
}
ncnn::ParamDict pd;
pd.set(0, outh);
pd.set(1, kernel);
pd.set(2, dilation);
pd.set(3, stride);
pd.set(4, pad);
pd.set(5, bias);
pd.set(6, outh / group * h / group * kernel * group);
pd.set(7, group);
int activation_type = RAND() % 5; // 0 1 2 3 4
ncnn::Mat activation_params(2);
activation_params[0] = RandomFloat(-1, 0); // alpha
activation_params[1] = RandomFloat(0, 1); // beta
pd.set(9, activation_type);
pd.set(10, activation_params);
pd.set(18, output_pad_right);
pd.set(20, output_w);
std::vector<ncnn::Mat> weights(2);
weights[0] = RandomMat(outh / group * h / group * kernel * group);
weights[1] = RandomMat(outh);
int ret = test_layer("DeconvolutionDepthWise1D", pd, weights, a);
if (ret != 0)
{
fprintf(stderr, "test_deconvolutiondepthwise1d failed w=%d h=%d outh=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d group=%d act=%d actparams=[%f,%f] output_pad_right=%d output_w=%d\n", w, h, outh, kernel, dilation, stride, pad, bias, group, activation_type, activation_params[0], activation_params[1], output_pad_right, output_w);
}
return ret;
}
static int test_deconvolutiondepthwise1d_0()
{
static const int kdsp[16][4] = {
{1, 1, 1, 0},
{1, 1, 2, 0},
{2, 1, 1, 1},
{2, 1, 2, -233},
{3, 1, 1, 1},
{3, 1, 2, 1},
{3, 2, 1, 1},
{4, 1, 1, -233},
{4, 1, 2, -234},
{4, 2, 1, -234},
{5, 1, 1, 2},
{5, 1, 2, 2},
{5, 2, 2, 2},
{7, 1, 1, 3},
{7, 1, 2, 3},
{7, 2, 1, -233},
};
for (int i = 0; i < 16; i++)
{
const int k = kdsp[i][0];
const int d = kdsp[i][1];
const int s = kdsp[i][2];
const int p = kdsp[i][3];
int ret = 0
|| test_deconvolutiondepthwise1d(15, 1, 1, k, d, s, p, 1, 1, 0, 0)
|| test_deconvolutiondepthwise1d(15, 2, 2, k, d, s, p, 0, 1, 1, 7)
|| test_deconvolutiondepthwise1d(15, 2, 2, k, d, s, p, 1, 2, 1, 0)
|| test_deconvolutiondepthwise1d(15, 3, 3, k, d, s, p, 0, 3, 0, 0)
|| test_deconvolutiondepthwise1d(15, 4, 2, k, d, s, p, 1, 2, 0, 7)
|| test_deconvolutiondepthwise1d(15, 4, 4, k, d, s, p, 0, 4, 2, 0)
|| test_deconvolutiondepthwise1d(15, 7, 7, k, d, s, p, 1, 7, 2, 0)
|| test_deconvolutiondepthwise1d(15, 8, 8, k, d, s, p, 0, 2, 0, 7)
|| test_deconvolutiondepthwise1d(15, 8, 8, k, d, s, p, 1, 8, 0, 0)
|| test_deconvolutiondepthwise1d(15, 12, 12, k, d, s, p, 0, 4, 3, 0)
|| test_deconvolutiondepthwise1d(15, 15, 15, k, d, s, p, 1, 15, 3, 7)
|| test_deconvolutiondepthwise1d(15, 16, 8, k, d, s, p, 0, 2, 0, 0)
|| test_deconvolutiondepthwise1d(15, 16, 16, k, d, s, p, 1, 16, 0, 0);
if (ret != 0)
return -1;
}
return 0;
}
static int test_deconvolutiondepthwise1d_dynamic(int w, int h, int outh, int kernel, int dilation, int stride, int pad, int bias, int group, int output_pad_right, int output_w)
{
ncnn::Mat a = RandomMat(w, h);
if (output_w > 0 && pad != -233 && pad != -234)
{
pad = -233;
}
ncnn::ParamDict pd;
pd.set(0, 0);
pd.set(1, 0);
pd.set(2, dilation);
pd.set(3, stride);
pd.set(4, pad);
pd.set(5, bias);
pd.set(6, 0);
pd.set(7, group);
pd.set(28, 1); // dynamic weight
int activation_type = RAND() % 5; // 0 1 2 3 4
ncnn::Mat activation_params(2);
activation_params[0] = RandomFloat(-1, 0); // alpha
activation_params[1] = RandomFloat(0, 1); // beta
pd.set(9, activation_type);
pd.set(10, activation_params);
pd.set(18, output_pad_right);
pd.set(20, output_w);
std::vector<ncnn::Mat> as(bias ? 3 : 2);
as[0] = a;
as[1] = RandomMat(kernel, outh / group, h);
if (bias)
as[2] = RandomMat(outh);
std::vector<ncnn::Mat> weights(0);
int ret = test_layer("DeconvolutionDepthWise1D", pd, weights, as);
if (ret != 0)
{
fprintf(stderr, "test_deconvolutiondepthwise1d_dynamic failed w=%d h=%d outh=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d group=%d act=%d actparams=[%f,%f] output_pad_right=%d output_w=%d\n", w, h, outh, kernel, dilation, stride, pad, bias, group, activation_type, activation_params[0], activation_params[1], output_pad_right, output_w);
}
return ret;
}
static int test_deconvolutiondepthwise1d_1()
{
static const int kdsp[16][4] = {
{1, 1, 1, 0},
{1, 1, 2, 0},
{2, 1, 1, 1},
{2, 1, 2, -233},
{3, 1, 1, 1},
{3, 1, 2, 1},
{3, 2, 1, 1},
{4, 1, 1, -233},
{4, 1, 2, -234},
{4, 2, 1, -234},
{5, 1, 1, 2},
{5, 1, 2, 2},
{5, 2, 2, 2},
{7, 1, 1, 3},
{7, 1, 2, 3},
{7, 2, 1, -233},
};
for (int i = 0; i < 16; i++)
{
const int k = kdsp[i][0];
const int d = kdsp[i][1];
const int s = kdsp[i][2];
const int p = kdsp[i][3];
int ret = 0
|| test_deconvolutiondepthwise1d_dynamic(15, 1, 1, k, d, s, p, 1, 1, 0, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 2, 2, k, d, s, p, 0, 1, 1, 7)
|| test_deconvolutiondepthwise1d_dynamic(15, 2, 2, k, d, s, p, 1, 2, 1, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 3, 3, k, d, s, p, 0, 3, 0, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 4, 2, k, d, s, p, 1, 2, 0, 7)
|| test_deconvolutiondepthwise1d_dynamic(15, 4, 4, k, d, s, p, 0, 4, 2, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 7, 7, k, d, s, p, 1, 7, 2, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 8, 8, k, d, s, p, 0, 2, 0, 7)
|| test_deconvolutiondepthwise1d_dynamic(15, 8, 8, k, d, s, p, 1, 8, 0, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 12, 12, k, d, s, p, 0, 4, 3, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 15, 15, k, d, s, p, 1, 15, 3, 7)
|| test_deconvolutiondepthwise1d_dynamic(15, 16, 8, k, d, s, p, 0, 2, 0, 0)
|| test_deconvolutiondepthwise1d_dynamic(15, 16, 16, k, d, s, p, 1, 16, 0, 0);
if (ret != 0)
return -1;
}
return 0;
}
static int test_deconvolutiondepthwise1d_activation_params_text()
{
#if NCNN_STRING
const char* params[] = {"0=1 1=1 6=1 9=3 -23310=2,-1,2", "0=1 1=1 6=1 9=3 -23310=2,-1.0,2.0"};
for (int i = 0; i < 2; i++)
{
TestParamDict pd;
if (pd.load_param(params[i]) != 0 || pd.type(10) != 5 + i)
return -1;
std::vector<ncnn::Mat> weights(1);
weights[0].create(1);
weights[0][0] = 1.f;
ncnn::Mat a(2, 1);
a[0] = -3.f;
a[1] = 3.f;
ncnn::Mat reference(2, 1);
reference[0] = -1.f;
reference[1] = 2.f;
ncnn::Mat b;
int ret = test_layer_naive(ncnn::LayerType::DeconvolutionDepthWise1D, pd, weights, a, b, 0);
if (ret == 0)
ret = CompareMat(reference, b, 0.f);
if (ret != 0)
{
fprintf(stderr, "test_deconvolutiondepthwise1d_activation_params_text failed params=%s ret=%d\n", params[i], ret);
return ret;
}
const ncnn::Mat original = pd.get(10, ncnn::Mat());
const int* p = original;
if (i == 0 ? (p[0] != -1 || p[1] != 2) : (original[0] != -1.f || original[1] != 2.f))
{
fprintf(stderr, "test_deconvolutiondepthwise1d_activation_params_text modified params=%s\n", params[i]);
return -1;
}
}
#endif
return 0;
}
#if NCNN_VALIDATION
static int test_deconvolutiondepthwise1d_load_param_activation(const ncnn::ParamDict& base, int activation_type, const ncnn::Mat& activation_params, int expected_ret)
{
ncnn::ParamDict pd = base;
pd.set(9, activation_type);
pd.set(10, activation_params);
return test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, pd, expected_ret);
}
static int test_deconvolutiondepthwise1d_load_param()
{
ncnn::ParamDict base;
base.set(0, 8);
base.set(1, 3);
base.set(6, 216);
base.set(7, 2);
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 0) != 0)
return -1;
ncnn::Mat params(2);
params[0] = 0.1f;
params[1] = 0.5f;
int ret = 0
|| test_deconvolutiondepthwise1d_load_param_activation(base, 0, ncnn::Mat(), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 0, ncnn::Mat(0), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 0, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 0, params.range(0, 1), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 1, ncnn::Mat(), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 1, ncnn::Mat(0), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 1, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 1, params.range(0, 1), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 2, ncnn::Mat(), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 2, ncnn::Mat(0), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 2, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 2, params.range(0, 1), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 3, ncnn::Mat(), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 3, ncnn::Mat(0), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 3, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 3, params.range(0, 1), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 4, ncnn::Mat(), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 4, ncnn::Mat(0), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 4, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 4, params.range(0, 1), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 5, ncnn::Mat(), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 5, ncnn::Mat(0), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 5, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 5, params.range(0, 1), 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 6, ncnn::Mat(), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 6, ncnn::Mat(0), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 6, params, 0)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 6, params.range(0, 1), -1)
|| test_deconvolutiondepthwise1d_load_param_activation(base, 7, ncnn::Mat(), -1);
if (ret != 0)
return ret;
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 10, 1, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 10, 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::DeconvolutionDepthWise1D, base, 10, bad[i], -1) != 0)
return -1;
}
ret = 0
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 0, 0, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 1, 0, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 2, 0, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 3, 0, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 1, INT_MAX, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 6, 217, -1);
if (ret != 0)
return ret;
const int groups[] = {0, -1, -8, INT_MIN, 3};
for (int i = 0; i < 5; i++)
{
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 7, groups[i], -1) != 0)
return -1;
}
{
ncnn::ParamDict pd = base;
pd.set(0, INT_MIN);
pd.set(7, -1); // avoid evaluating INT_MIN % -1
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, pd, -1) != 0)
return -1;
}
return 0;
}
static int test_deconvolutiondepthwise1d_load_param_dynamic()
{
ncnn::ParamDict base;
base.set(0, 5);
base.set(1, 1);
base.set(6, 10);
base.set(7, 2);
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, -1) != 0)
return -1;
ncnn::ParamDict dynamic = base;
dynamic.set(28, 1);
const int num_outputs[] = {0, -1, 5, INT_MIN, INT_MAX};
for (int i = 0; i < 5; i++)
{
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, dynamic, 0, num_outputs[i], 0) != 0)
return -1;
}
return 0
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, base, 0, 2, 0)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, dynamic, 7, 0, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, dynamic, 7, -1, -1)
|| test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, dynamic, 7, INT_MIN, -1);
}
static int test_deconvolutiondepthwise1d_load_param_text()
{
#if NCNN_STRING
const char* params[] = {"0=1 1=1 6=1 9=3 -23310=2,-1,2", "0=1 1=1 6=1 9=3 -23310=2,-1.0,2.0"};
for (int i = 0; i < 2; i++)
{
TestParamDict pd;
if (pd.load_param(params[i]) != 0 || pd.type(10) != 5 + i)
return -1;
if (test_layer_param(ncnn::LayerType::DeconvolutionDepthWise1D, pd, 0) != 0)
return -1;
}
#endif
return 0;
}
#endif // NCNN_VALIDATION
int main()
{
SRAND(7767517);
return 0
|| test_deconvolutiondepthwise1d_0()
|| test_deconvolutiondepthwise1d_1()
|| test_deconvolutiondepthwise1d_activation_params_text()
#if NCNN_VALIDATION
|| test_deconvolutiondepthwise1d_load_param()
|| test_deconvolutiondepthwise1d_load_param_text()
|| test_deconvolutiondepthwise1d_load_param_dynamic()
#endif // NCNN_VALIDATION
;
}
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