torch学习笔记（1）

torch-nn学习：Simpley Layer

torch7入门续集（三）：Simple Layers

use of unsqueeze():

1 module = nn.Unsqueeze(pos [, numInputDims])

1 input = torch.Tensor(2,4,3)          # input: 2*4*3
2 print(input.unsqueeze(0).size())     # prints-torch.size([1,2,3,4])

use of view():

1 input = torch.Tensor(2,4,3)          # input: 2*4*3
2 print(input.view(1,-1,-1,-1).size()) # print-torch.size([1,2,4,3])

squeeze 若指定维度，则把对应维度压缩，否则压缩所有维度为1的维度。

eg. B = squeeze(A)，B与A有相同的元素，但所有只有一行或一列的维度(singleton dimension)被去除掉了。

 1 module = nn.Squeeze([dim, numInputDims])
 2 x=torch.rand(2,1,2,1,2)
 3 > x
 4 (1,1,1,.,.) =
 5   0.6020  0.8897
 6 (2,1,1,.,.) =
 7   0.4713  0.2645
 8 (1,1,2,.,.) =
 9   0.4441  0.9792
10 (2,1,2,.,.) =
11   0.5467  0.8648
12
13 > torch.squeeze(x,2)
14 (1,1,.,.) =
15   0.6020  0.8897
16 (2,1,.,.) =
17   0.4713  0.2645
18 (1,2,.,.) =
19   0.4441  0.9792
20 (2,2,.,.) =
21   0.5467  0.8648
22 [torch.DoubleTensor of dimension 2x2x1x2]

dropout

未完待续