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| | #include "layer/deformableconv2d.h" |
| | #include "testutil.h" |
| |
|
| | static int test_deformableconv2d(int w, int h, int c, int outch, int kernel, int dilation, int stride, int pad, int bias) |
| | { |
| | const int kernel_extent_w = dilation * (kernel - 1) + 1; |
| | const int kernel_extent_h = dilation * (kernel - 1) + 1; |
| | const int out_w = (w + pad + pad - kernel_extent_w) / stride + 1; |
| | const int out_h = (h + pad + pad - kernel_extent_h) / stride + 1; |
| | std::vector<ncnn::Mat> a(3); |
| | a[0] = RandomMat(w, h, c); |
| | a[1] = RandomMat(out_w, out_h, kernel * kernel * 2); |
| | a[2] = RandomMat(out_w, out_h, kernel * kernel); |
| |
|
| | ncnn::ParamDict pd; |
| | pd.set(0, outch); |
| | pd.set(1, kernel); |
| | pd.set(2, dilation); |
| | pd.set(3, stride); |
| | pd.set(4, pad); |
| | pd.set(5, bias); |
| | pd.set(6, outch * c * kernel * kernel); |
| |
|
| | 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> weights(bias ? 2 : 1); |
| | weights[0] = RandomMat(outch * c * kernel * kernel); |
| | if (bias) |
| | weights[1] = RandomMat(outch); |
| |
|
| | float epsilon = 0.001; |
| | int ret = test_layer<ncnn::DeformableConv2D>("DeformableConv2D", pd, weights, a, 1, epsilon); |
| | if (ret != 0) |
| | { |
| | fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); |
| | } |
| |
|
| | { |
| | ncnn::Option opt; |
| | opt.num_threads = 1; |
| | opt.use_packing_layout = true; |
| | opt.use_fp16_packed = false; |
| | opt.use_fp16_storage = false; |
| | opt.use_fp16_arithmetic = false; |
| | opt.use_bf16_storage = false; |
| | opt.use_shader_pack8 = false; |
| | opt.use_image_storage = false; |
| | opt.use_sgemm_convolution = false; |
| | opt.use_winograd_convolution = false; |
| |
|
| | ret = test_layer_opt<ncnn::DeformableConv2D>("DeformableConv2D", pd, weights, opt, a, 1, epsilon); |
| | if (ret != 0) |
| | { |
| | fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); |
| | } |
| | } |
| |
|
| | { |
| | ncnn::Option opt; |
| | opt.num_threads = 1; |
| | opt.use_packing_layout = true; |
| | opt.use_fp16_packed = true; |
| | opt.use_fp16_storage = true; |
| | opt.use_fp16_arithmetic = true; |
| | opt.use_bf16_storage = true; |
| | opt.use_shader_pack8 = true; |
| | opt.use_image_storage = true; |
| | opt.use_sgemm_convolution = false; |
| | opt.use_winograd_convolution = false; |
| |
|
| | ret = test_layer_opt<ncnn::DeformableConv2D>("DeformableConv2D", pd, weights, opt, a, 1, epsilon); |
| | if (ret != 0) |
| | { |
| | fprintf(stderr, "test_deformableconv2d failed w=%d h=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d act=%d actparams=[%f,%f]\n", w, h, c, outch, kernel, dilation, stride, pad, bias, activation_type, activation_params[0], activation_params[1]); |
| | } |
| | } |
| |
|
| | return ret; |
| | } |
| |
|
| | static int test_deformableconv2d_0() |
| | { |
| | static const int kdsp[10][4] = { |
| | {1, 1, 1, 0}, |
| | {1, 1, 2, 0}, |
| | {2, 1, 1, 1}, |
| | {2, 1, 2, 0}, |
| | {3, 1, 1, 1}, |
| | {3, 1, 2, 1}, |
| | {3, 2, 1, 1}, |
| | {4, 1, 2, 1}, |
| | {5, 1, 2, 2}, |
| | {5, 2, 2, 2}, |
| | }; |
| |
|
| | for (int i = 6; i < 8; 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_deformableconv2d(9, 7, 1, 1, k, d, s, p, 1) |
| | || test_deformableconv2d(9, 7, 4, 13, k, d, s, p, 0) |
| | || test_deformableconv2d(9, 7, 13, 4, k, d, s, p, 1) |
| | || test_deformableconv2d(9, 7, 4, 8, k, d, s, p, 0) |
| | || test_deformableconv2d(9, 7, 8, 4, k, d, s, p, 1) |
| | || test_deformableconv2d(9, 7, 8, 13, k, d, s, p, 0) |
| | || test_deformableconv2d(9, 7, 13, 8, k, d, s, p, 1) |
| | || test_deformableconv2d(9, 7, 16, 16, k, d, s, p, 0) |
| | || test_deformableconv2d(16, 16, 1 * 3, 1 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 1 * 3, 4 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 1 * 3, 8 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 1 * 3, 16 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 4 * 3, 1 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 4 * 3, 4 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 4 * 3, 8 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 4 * 3, 16 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 8 * 3, 1 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 8 * 3, 4 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 8 * 3, 8 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 8 * 3, 16 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 16 * 3, 1 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 16 * 3, 4 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 16 * 3, 8 * 3, k, d, s, p, 1) |
| | || test_deformableconv2d(16, 16, 16 * 3, 16 * 3, k, d, s, p, 1); |
| |
|
| | if (ret != 0) |
| | return -1; |
| | } |
| |
|
| | return 0; |
| | } |
| |
|
| | int main() |
| | { |
| | SRAND(7767517); |
| |
|
| | return test_deformableconv2d_0(); |
| | } |
| |
|