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| | #include "layer/convolution1d.h" |
| | #include "testutil.h" |
| |
|
| | static int test_convolution1d(int w, int h, int outh, int kernel, int dilation, int stride, int pad, int bias) |
| | { |
| | ncnn::Mat a = RandomMat(w, h); |
| |
|
| | 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 * h * kernel); |
| |
|
| | int activation_type = RAND() % 6; |
| | ncnn::Mat activation_params(2); |
| | activation_params[0] = RandomFloat(-1, 0); |
| | activation_params[1] = RandomFloat(0, 1); |
| | pd.set(9, activation_type); |
| | pd.set(10, activation_params); |
| |
|
| | std::vector<ncnn::Mat> weights(bias ? 2 : 1); |
| | weights[0] = RandomMat(outh * h * kernel); |
| | if (bias) |
| | weights[1] = RandomMat(outh); |
| |
|
| | int ret = test_layer<ncnn::Convolution1D>("Convolution1D", pd, weights, a); |
| | if (ret != 0) |
| | { |
| | fprintf(stderr, "test_convolution1d failed w=%d h=%d outh=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, outh, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); |
| | } |
| |
|
| | return ret; |
| | } |
| |
|
| | static int test_convolution1d_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, 2}, |
| | {4, 1, 2, -233}, |
| | {4, 2, 1, -234}, |
| | {5, 1, 1, -234}, |
| | {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]; |
| | const int b0 = i % 2; |
| | const int b1 = 1 - b1; |
| |
|
| | int ret = 0 |
| | || test_convolution1d(9, 1, 1, k, d, s, p, b0) |
| | || test_convolution1d(9, 1, 3, k, d, s, p, b1) |
| | || test_convolution1d(9, 1, 7, k, d, s, p, b0) |
| | || test_convolution1d(9, 1, 15, k, d, s, p, b1) |
| | || test_convolution1d(9, 1, 31, k, d, s, p, b0) |
| | || test_convolution1d(9, 3, 1, k, d, s, p, b1) |
| | || test_convolution1d(9, 3, 3, k, d, s, p, b0) |
| | || test_convolution1d(9, 3, 7, k, d, s, p, b1) |
| | || test_convolution1d(9, 3, 15, k, d, s, p, b0) |
| | || test_convolution1d(9, 3, 31, k, d, s, p, b1) |
| | || test_convolution1d(9, 7, 1, k, d, s, p, b0) |
| | || test_convolution1d(9, 7, 3, k, d, s, p, b1) |
| | || test_convolution1d(9, 7, 7, k, d, s, p, b0) |
| | || test_convolution1d(9, 7, 15, k, d, s, p, b1) |
| | || test_convolution1d(9, 7, 31, k, d, s, p, b0) |
| | || test_convolution1d(9, 15, 1, k, d, s, p, b1) |
| | || test_convolution1d(9, 15, 3, k, d, s, p, b0) |
| | || test_convolution1d(9, 15, 7, k, d, s, p, b1) |
| | || test_convolution1d(9, 15, 15, k, d, s, p, b0) |
| | || test_convolution1d(9, 15, 31, k, d, s, p, b1) |
| | || test_convolution1d(9, 31, 1, k, d, s, p, b0) |
| | || test_convolution1d(9, 31, 3, k, d, s, p, b1) |
| | || test_convolution1d(9, 31, 7, k, d, s, p, b0) |
| | || test_convolution1d(9, 31, 15, k, d, s, p, b1) |
| | || test_convolution1d(25, 28, 31, k, d, s, p, b0) |
| | || test_convolution1d(25, 31, 28, k, d, s, p, b1) |
| | || test_convolution1d(25, 28, 28, k, d, s, p, b0) |
| | || test_convolution1d(25, 24, 28, k, d, s, p, b1) |
| | || test_convolution1d(25, 24, 31, k, d, s, p, b0) |
| | || test_convolution1d(25, 28, 24, k, d, s, p, b1) |
| | || test_convolution1d(25, 31, 24, k, d, s, p, b0) |
| | || test_convolution1d(25, 24, 24, k, d, s, p, b1) |
| | || test_convolution1d(25, 28, 48, k, d, s, p, b0) |
| | || test_convolution1d(25, 31, 48, k, d, s, p, b1) |
| | || test_convolution1d(25, 24, 48, k, d, s, p, b0) |
| | || test_convolution1d(25, 48, 28, k, d, s, p, b1) |
| | || test_convolution1d(25, 48, 31, k, d, s, p, b0) |
| | || test_convolution1d(25, 48, 24, k, d, s, p, b1) |
| | || test_convolution1d(25, 31, 31, k, d, s, p, b0) |
| | || test_convolution1d(25, 48, 48, k, d, s, p, b1); |
| |
|
| | if (ret != 0) |
| | return -1; |
| | } |
| |
|
| | return 0 |
| | || test_convolution1d(7, 1, 4, 3, 1, 1, 1, 1) |
| | || test_convolution1d(14, 1, 4, 3, 1, 2, 1, 1) |
| | || test_convolution1d(15, 4, 4, 3, 1, 1, 1, 1) |
| | || test_convolution1d(15, 8, 8, 3, 1, 1, 1, 1) |
| | || test_convolution1d(11, 8, 16, 3, 1, 1, 1, 1) |
| | || test_convolution1d(13, 16, 24, 3, 1, 1, 1, 1) |
| | || test_convolution1d(8, 16, 24, 3, 1, 1, 1, 0) |
| | || test_convolution1d(4, 16, 24, 3, 1, 1, 1, 1) |
| | || test_convolution1d(4, 16, 24, 3, 1, 1, 1, 0) |
| | || test_convolution1d(6, 64, 64, 3, 1, 2, 0, 1); |
| | } |
| |
|
| | static int test_convolution1d_dynamic(int w, int h, int outh, int kernel, int dilation, int stride, int pad, int bias) |
| | { |
| | ncnn::Mat a = RandomMat(w, h); |
| |
|
| | 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(19, 1); |
| |
|
| | int activation_type = RAND() % 7; |
| | ncnn::Mat activation_params(2); |
| | activation_params[0] = (activation_type == 6) ? RandomFloat(0, 1) : RandomFloat(-1, 0); |
| | activation_params[1] = RandomFloat(0, 1); |
| | pd.set(9, activation_type); |
| | pd.set(10, activation_params); |
| |
|
| | std::vector<ncnn::Mat> as(bias ? 3 : 2); |
| | as[0] = a; |
| | as[1] = RandomMat(kernel, h, outh); |
| | if (bias) |
| | as[2] = RandomMat(outh); |
| |
|
| | std::vector<ncnn::Mat> weights(0); |
| |
|
| | int ret = test_layer<ncnn::Convolution1D>("Convolution1D", pd, weights, as); |
| | if (ret != 0) |
| | { |
| | fprintf(stderr, "test_convolution1d_dynamic failed w=%d h=%d outh=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, outh, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); |
| | } |
| |
|
| | return ret; |
| | } |
| |
|
| | static int test_convolution1d_1() |
| | { |
| | static const int kdsp[7][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, -234}, |
| | }; |
| |
|
| | for (int i = 0; i < 7; 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_convolution1d_dynamic(11, 1, 1, k, d, s, p, 1) |
| | || test_convolution1d_dynamic(11, 4, 13, k, d, s, p, 0) |
| | || test_convolution1d_dynamic(11, 13, 4, k, d, s, p, 1) |
| | || test_convolution1d_dynamic(11, 12, 12, k, d, s, p, 0) |
| | || test_convolution1d_dynamic(11, 8, 12, k, d, s, p, 1) |
| | || test_convolution1d_dynamic(11, 8, 13, k, d, s, p, 0) |
| | || test_convolution1d_dynamic(11, 13, 8, k, d, s, p, 1) |
| | || test_convolution1d_dynamic(11, 12, 16, k, d, s, p, 0) |
| | || test_convolution1d_dynamic(11, 15, 15, k, d, s, p, 0) |
| | || test_convolution1d_dynamic(11, 16, 16, k, d, s, p, 0); |
| |
|
| | if (ret != 0) |
| | return -1; |
| | } |
| |
|
| | return 0; |
| | } |
| |
|
| | int main() |
| | { |
| | SRAND(7767517); |
| |
|
| | return test_convolution1d_0() || test_convolution1d_1(); |
| | } |
| |
|