主要内容 1 t(), T, transpose(), permute() 四种排列操作(包括转置)对比 t(), T 支持2维 transpose()支持多维tensor,一次性调整两个dimension permute() 支持多维tensor, 一次可调整多个dimension 2 tensor的底层存储形式, permutation和reshape对, 视
torch.transpose()正如前面所说的,它是转置,即交换维度,以及步长(Stride)。 torch.arange(24).reshape((2,3,4)).transpose(0,1)#tensor([[[ 0, 1, 2, 3],#[12, 13, 14, 15]],# #[[ 4, 5, 6, 7],#[16, 17, 18, 19]],# #[[ 8, 9, 10, 11],#[20, 21, 22, 23]]])torch...
torch.transpose(a, -1, 0) 这里,在上述情况下,我们给出了要转置的第一维和第二维。TypeError: transpose() received an invalid combination of arguments - got (Tensor), but expected one of: * (Tensor input, name dim0, name dim1) * (Tensor input, int dim0, int dim1) 在张量数据上使用转置...
transpose cat/concat/concatenate 而且支持torch::reshape这种静态函数和tensor.reshape这种对象函数。下面是一些例子: // 变形操作 bar = foo.reshape({2, -1}); bar = foo.flatten(); bar = foo.squeeze(); bar = foo.unsqueeze(0); bar = torch::unsqueeze(foo, -1); bar = foo.transpose(0, 1...
placeholderrepresents a function input. Thenameattribute specifies the name this value will take on.targetis similarly the name of the argument.argsholds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input.kwargsis don’t-care. Placeholders correspond...
ConvTranspose3d Unfold Fold Pooling layers MaxPool1d MaxPool2d MaxPool3d MaxUnpool1d MaxUnpool2d MaxUnpool3d AvgPool1d AvgPool2d AvgPool3d FractionalMaxPool2d LPPool1d LPPool2d AdaptiveMaxPool1d AdaptiveMaxPool2d AdaptiveMaxPool3d AdaptiveAvgPool1d AdaptiveAvgPool2d AdaptiveAvgPool3d Padding layers...
torch.addcmul(tensor, value=1, tensor1, tensor2, out=None)→ Tensor用tensor2对tensor1逐元素相乘,并对结果乘以标量值value然后加到tensor。张量的形状不需要匹配,但元素数量必须一致。如果输入是FloatTensor or DoubleTensor类型,则value 必须为实数,否则须为整数。
(input)# exact output size can be also specified as an argumentinput = torch.randn(1, 16, 12, 12)downsample = nn.Conv2d(16, 16, 3, stride=2, padding=1)upsample = nn.ConvTranspose2d(16, 16, 3, stride=2, padding=1)h = downsample(input)h.size()output = upsample(h, output_...
torch.nn.ConvTranspose2d 转置卷积 =00groups=1,bias=True,dilation=1,padding_mode='zeros') 其中,各参数的含义如下: in_channels(int):输入张量的通道数 out_channels(int):输出张量的通道数 kernel_size(int or tuple):卷积核大小 stride(int or tuple,optional):卷积步长,决定上采样的倍数...
torch.tensor().permute(2,1,0) 技术标签: Pytorch pytorch 参考: permute函数 python pytorch permute函数 [Python] 维度交换函数:transpose(m,n,r)和permute(m,n,r) import torch from torch import nn import numpy as np b=np.array([[[ 0, 1, 2,3], [ 4,5,6,7], [ 8,9, 10,11]],...