# 或者: from torchvision.models.resnet importconv3x3[as 别名]def__init__(self, config_channels, prefix, channels, stride=1):nn.Module.__init__(self) channels_in = config_channels.channels self.conv1 =conv3x3(config_channels.channels, config_channels(channels,'%s.conv1.weight'% prefix), ...
staticvoidconv3x3s1_winograd23_transform_kernel_sse(constMat&kernel,Mat&kernel_tm,intinch,intoutch){kernel_tm.create(4*4,inch,outch);// Gconstfloatktm[4][3]={{1.0f,0.0f,0.0f},{1.0f/2,1.0f/2,1.0f/2},{1.0f/2,-1.0f/2,1.0f/2},{0.0f,0.0f,1.0f}};#pragma omp parallel for...
IMG_conv_3x3_i8_c8s(y,p_info->out, (p_info->width * p_info->height),p_info->width, mask,0); 加入之后,代码在↑处卡住,一直不出结果,无法输出结果图像。如下: 但是将代码改为sobel算子之后,可以出边缘检测的结果: IMG_sobel_3x3_8(y, p_info->out,p_info->width, p_inf...
还是没有输出? unsignedcharin[900*1024]; unsignedcharout_conv[900*1024]; charmask3[9]={0,-1,0,-1,4,-1,0,-1,0}; char*mask=mask3; IMG_conv_3x3_i8_c8s(in,out_conv,640*3,480,mask,9);//卷积运算 这是我测试用的代码,为什么这个函数执行后目的地址全0了呢?是我的模版找的问题吗...
conv3x3s2进行过理论分析，由于stride2数据重叠部分少，用winograd的加速比不高，所以不推荐用winograd， 建议直接用im2col+gemm。
ncnn is a high-performance neural network inference framework optimized for the mobile platform - arm neon optimization for conv3x3s1 winograd42 (#2664) · Tencent/ncnn@ab56083
Multi-platform high performance deep learning inference engine (飞桨多端多平台高性能深度学习推理引擎) - [X86] optimize depthwise conv2d3x3 (#5434) (#5477) · XYZ-916/Paddle-Lite@1999436
mobilenetv2和resnet比较,Resnet中:原始BottleNeck:实现的功能:通道维度下降-->通道维度保持不变-->通道维度上升实现的时候,是1x1conv-->3x3conv-->1x1convMobileNet_v2中:提出了逆残差模块,Inverted_residual:实现的功能:通道维度上升-->通道维度保
GlobalStep
能否跟踪到具体卡在了IMG_conv_3x3_i8_c8s函数里的哪行代码还是跑飞了？heap, stack等是否都正常？