错误提示“given groups=1, weight of size [32, 3, 6, 6], expected input[1”表明输入数据的形状与卷积层的期望不匹配。这里,我将分点解释可能的原因和解决方案: 1. 理解RuntimeError信息内容 错误信息指出,卷积层期望的输入通道数(in_channels)与实际提供的输入通道数不一致。具体来说,卷积层的权重形状...
RuntimeError: Given groups=1, weight of size [6, 256, 3, 3], expected input[8, 64, 64, 64] to hav... 遇到问题:缝合两个网络模型时,输入维度不一致导致模型,训练报错。 解决思路:先用troch.flatten()函数把tensor张量展开成一维张量,在使用[:xx]截取需要维度元素总数,最后使用view()函数重塑成需...
self.padding, self.dilation, self.groups) RuntimeError: Given groups=1, weight of size [64, 18, 4, 4], expected input[2, 4, 256, 256] to have 18 channels, but got 4 channels instead
(256 + 64, 128, 128) self.dec1 = DecoderBlock(128, 128, 32) self.dec0 = ConvRelu(32, 32) self.final = nn.Conv2d(32, num_classes, kernel_size=1) def forward(self, x): conv1 = self.conv1(x) conv2 = self.conv2(conv1) conv3 = self.conv3(conv2) conv4 = self.conv4...
修改训练数据集:网络原本使用MNIST数据集进行训练,现改为使用CIFAR10来进行训练。报错:RuntimeError: Given groups=1, weight of size [6, 1, 13, 13], expected input[1, 3, 32, 32] to have 1 channels, but got 3 channels instead 原因:通道数不匹配,MINIST使用灰度图像,CIFAR10使用RGB图像。
简介:RuntimeError: Given groups=1, weight of size 64 128 1 7, expected input[16, 如果输入和输出匹配的情况下有这样的错误,请检查在定义卷积的时候有没有名字重复的, 例: ("2conv1,3_bn1", ConvBN(channelNum * 4, channelNum * 2, [1, 3])), ...
我认为问题出在BatchNorm()layer ==>self.bn1 = nn.BatchNorm2d(16)上。
EasyNVR是基于RTSP/Onvif协议的视频平台，可支持将接入的视频流进行全平台、全终端的分发，分发的视频流...
1.运行train.py报错: RuntimeError: Given groups=1, weight of size [512, 1024, 1, 1], expected input[1, 512, 8, 8] to have 1024 channels, but got 512 channels instead 2.解决办法: parser.add_argument('--cfg', type=str, default='', help='model.yaml path') ...
RuntimeError: Given groups=1, weight of size [32, 128, 1, 1], expected input[1, 64, 32, 32] to have 128 channels, but got 64 channels instead Hello, thank you for your interest in our work! This issue seems to lack the minimum requirements for a proper response, or is insufficie...