MaxPool3d(return_indices=True) returns junk indices, both on CPU and GPU. Here is an example: pool3d = nn.MaxPool3d(kernel_size=2,stride=2,return_indices=True) img3d = Variable(torch.rand(1,1,4,4,4)) out, indices = pool3d(img3d) print(indices) The output looks like this: ...
pool1=nn.MaxPool3d(kernel_size=(1,3,3),stride=(1,2,2),padding=(0,1,1)) self.conv2=BasicConv3d(64,64,kernel_size=1,stride=1) self.conv3=BasicConv3d(64,192,kernel_size=3,stride=1,padding=1) self.pool2=nn.MaxPool3d(kernel_size=(1,3,3),stride=(1,2,2),padding=(0,1,...
max_pool3d(F.relu(self.bn1(self.conv1(x))),(2,2,2))#conv->relu->pool x = F.max_pool3d(F.relu(self.conv1(x)),(2,2,2))#conv->relu->pool x = F.max_pool3d(F.relu(self.conv2(x)),(2,2,2))#conv->relu->pool x = F.max_pool3d(F.relu(self.conv3(x)),(2,2,...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Add type check for `dilation` in `torch.quantized_max_pool3d()` · pytorch/pytorch@6813117
nn.MaxPool3d:三维最大池化。 nn.MaxUnpool1d:一维最大逆池化。 nn.MaxUnpool2d:二维最大逆池化,将包含最大值索引的输出作为输入,其中所有非最大值都设置为零。 >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True)>>> unpool = nn.MaxUnpool2d(2, stride=2)>>> input = torch.tensor...
1)torch.nn.MaxPool1d它用于在由多个输入平面组成的输入信号上应用一维最大池。 2)torch.nn.MaxPool2d它用于在由多个输入平面组成的输入信号上应用2D max池。 3)torch.nn.MaxPool3d它用于在由多个输入平面组成的输入信号上应用3D max池。 4)torch.nn.MaxUnpool1d它用于计算MaxPool1d的局部逆。
torch.nn.functional.max_pool3d(input, kernel_size, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices=False)source对由几个输入平面组成的输入进行3D最大池化。 有关详细信息和输出形状,参考MaxPool3dtorch.nn.functional.max_unpool1d(input, indices, kernel_size, stride=None, ...
torch.nn.functional.avg_pool3d(input, kernel_size, stride=None) 在kt x kh x kw区域中应用步长为dt x dh x dw的二维平均池化操作。输出特征的数量等于 input planes / dt。 torch.nn.functional.max_pool1d(input, kernel_size, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices...
MaxPool3d MaxUnpool1d MaxUnpool2d MaxUnpool3d AvgPool1d AvgPool2d AvgPool3d FractionalMaxPool2d LPPool1d LPPool2d AdaptiveMaxPool1d AdaptiveMaxPool2d AdaptiveMaxPool3d AdaptiveAvgPool1d AdaptiveAvgPool2d AdaptiveAvgPool3d Padding layers ReflectionPad1d ReflectionPad2d ReplicationPad1d ReplicationPad2d...
MaxPool2d MaxPool3d MaxUnpool1d MaxUnpool2d MaxUnpool3d AvgPool1d AvgPool2d AvgPool3d FractionalMaxPool2d LPPool1d LPPool2d AdaptiveMaxPool1d AdaptiveMaxPool2d AdaptiveMaxPool3d AdaptiveAvgPool1d AdaptiveAvgPool2d AdaptiveAvgPool3d Padding layers ...