mix vulkan winograd f23 and f43 (#3639)

* mix vulkan winograd f23 and f43

* larget epsilon for winograd optimization test

src/layer/vulkan/convolution_vulkan.h

@@ -50,12 +50,14 @@ public:
     // winograd23 and winograd43
     ncnn::Layer* winograd_padding;
     ncnn::Layer* winograd_crop;
-    VkMat weight_data_gpu_tm;
-    VkImageMat weight_data_gpu_tm_image;
+    VkMat weight_data_gpu_tm_winograd23;
+    VkImageMat weight_data_gpu_tm_winograd23_image;
     Pipeline* pipeline_convolution_3x3s1d1_winograd23_transform_input;
     Pipeline* pipeline_convolution_3x3s1d1_winograd23_gemm;
     Pipeline* pipeline_convolution_3x3s1d1_winograd23_transform_output;
 
+    VkMat weight_data_gpu_tm_winograd43;
+    VkImageMat weight_data_gpu_tm_winograd43_image;
     Pipeline* pipeline_convolution_3x3s1d1_winograd43_transform_input;
     Pipeline* pipeline_convolution_3x3s1d1_winograd43_gemm;
     Pipeline* pipeline_convolution_3x3s1d1_winograd43_transform_output;

tests/test_convolution.cpp

@@ -40,7 +40,12 @@ static int test_convolution(int w, int h, int c, int outch, int kernel, int dila
     if (bias)
         weights[1] = RandomMat(outch);
 
-    int ret = test_layer<ncnn::Convolution>("Convolution", pd, weights, a);
+    float epsilon = 0.001;
+    // larget epsilon for winograd optimization
+    if (kernel == 3 && dilation == 1 && stride == 1 && c >= 16 && outch >= 16)
+        epsilon = 0.002;
+
+    int ret = test_layer<ncnn::Convolution>("Convolution", pd, weights, a, epsilon);
     if (ret != 0)
     {
         fprintf(stderr, "test_convolution 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]);