看一下stack的直观解释，动词可以简单理解为：把……放成一堆、把……放成一摞。
torch.stack方法用于沿着一个新的维度 join（也可称为cat）一系列的张量（可以是2个张量或者是更多），它会插入一个新的维度，并让张量按照这个新的维度进行张量的cat操作。值得注意的是：张量序列中的张量必须要有相同的shape和dimension。
import torch
ogfW = 50
fW = ogfW // 10 #5
ogfH = 40
fH = ogfH // 10 ##4
print("====>>xs"*8)
xs = torch.linspace(0, ogfW - 1, fW, dtype=torch.float).view(1, fW).expand(fH, fW)
print(torch.linspace(0, ogfW - 1, fW, dtype=torch.float))
print(torch.linspace(0, ogfW - 1, fW, dtype=torch.float).view(1, fW))
print(xs)print("====>>ys"*8)
ys = torch.linspace(0, ogfH - 1, fH, dtype=torch.float).view(fH, 1).expand(fH, fW)
print(torch.linspace(0, ogfH - 1, fH, dtype=torch.float))
print(torch.linspace(0, ogfH - 1, fH, dtype=torch.float).view(fH, 1))
print(ys)
print("====>>frustum"*8)
print("===>>>shape xs=", xs.shape)
print("===>>>shape ys=", ys.shape)
frustum = torch.stack((xs, ys), -1)
print("===>>>shape frustum=", frustum.shape)
print(frustum)
====>>xs====>>xs====>>xs====>>xs====>>xs====>>xs====>>xs====>>xs
tensor([ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000])
tensor([[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]])
tensor([[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]])
====>>ys====>>ys====>>ys====>>ys====>>ys====>>ys====>>ys====>>ys
tensor([ 0., 13., 26., 39.])
tensor([[ 0.],[13.],[26.],[39.]])
tensor([[ 0., 0., 0., 0., 0.],[13., 13., 13., 13., 13.],[26., 26., 26., 26., 26.],[39., 39., 39., 39., 39.]])
====>>frustum====>>frustum====>>frustum====>>frustum====>>frustum====>>frustum====>>frustum====>>frustum
===>>>shape xs= torch.Size([4, 5])
===>>>shape ys= torch.Size([4, 5])
===>>>shape frustum= torch.Size([4, 5, 2])
tensor([[[ 0.0000, 0.0000],[12.2500, 0.0000],[24.5000, 0.0000],[36.7500, 0.0000],[49.0000, 0.0000]],[[ 0.0000, 13.0000],[12.2500, 13.0000],[24.5000, 13.0000],[36.7500, 13.0000],[49.0000, 13.0000]],[[ 0.0000, 26.0000],[12.2500, 26.0000],[24.5000, 26.0000],[36.7500, 26.0000],[49.0000, 26.0000]],[[ 0.0000, 39.0000],[12.2500, 39.0000],[24.5000, 39.0000],[36.7500, 39.0000],[49.0000, 39.0000]]])Process finished with exit code 0
3维
import torch
D = 3
ogfW = 50
fW = ogfW // 10 #5
ogfH = 40
fH = ogfH // 10 ##4
ds = torch.arange(*[-6,-3,1], dtype=torch.float).view(-1, 1, 1).expand(-1, fH, fW)xs = torch.linspace(0, ogfW - 1, fW, dtype=torch.float).view(1, 1, fW).expand(D, fH, fW)
print(torch.linspace(0, ogfW - 1, fW, dtype=torch.float))
print(torch.linspace(0, ogfW - 1, fW, dtype=torch.float).view(1, 1, fW))
print(xs)ys = torch.linspace(0, ogfH - 1, fH, dtype=torch.float).view(1, fH, 1).expand(D, fH, fW)
print("=="*20)
print(torch.linspace(0, ogfH - 1, fH, dtype=torch.float))
print(torch.linspace(0, ogfH - 1, fH, dtype=torch.float).view(1, fH, 1))
print(ys)
print("==>>"*20)
print("===>>>shape xs=", xs.shape)
print("===>>>shape ys=", ys.shape)
frustum = torch.stack((xs, ys, ds), -1)
print("===>>>shape frustum=", frustum.shape)
print(frustum)
tensor([ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000])
tensor([[[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]]])
tensor([[[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]],[[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]],[[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000],[ 0.0000, 12.2500, 24.5000, 36.7500, 49.0000]]])
========================================
tensor([ 0., 13., 26., 39.])
tensor([[[ 0.],[13.],[26.],[39.]]])
tensor([[[ 0., 0., 0., 0., 0.],[13., 13., 13., 13., 13.],[26., 26., 26., 26., 26.],[39., 39., 39., 39., 39.]],[[ 0., 0., 0., 0., 0.],[13., 13., 13., 13., 13.],[26., 26., 26., 26., 26.],[39., 39., 39., 39., 39.]],[[ 0., 0., 0., 0., 0.],[13., 13., 13., 13., 13.],[26., 26., 26., 26., 26.],[39., 39., 39., 39., 39.]]])
==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>==>>
===>>>shape xs= torch.Size([3, 4, 5])
===>>>shape ys= torch.Size([3, 4, 5])
===>>>shape frustum= torch.Size([3, 4, 5, 3])
tensor([[[[ 0.0000, 0.0000, -6.0000],[12.2500, 0.0000, -6.0000],[24.5000, 0.0000, -6.0000],[36.7500, 0.0000, -6.0000],[49.0000, 0.0000, -6.0000]],[[ 0.0000, 13.0000, -6.0000],[12.2500, 13.0000, -6.0000],[24.5000, 13.0000, -6.0000],[36.7500, 13.0000, -6.0000],[49.0000, 13.0000, -6.0000]],[[ 0.0000, 26.0000, -6.0000],[12.2500, 26.0000, -6.0000],[24.5000, 26.0000, -6.0000],[36.7500, 26.0000, -6.0000],[49.0000, 26.0000, -6.0000]],[[ 0.0000, 39.0000, -6.0000],[12.2500, 39.0000, -6.0000],[24.5000, 39.0000, -6.0000],[36.7500, 39.0000, -6.0000],[49.0000, 39.0000, -6.0000]]],[[[ 0.0000, 0.0000, -5.0000],[12.2500, 0.0000, -5.0000],[24.5000, 0.0000, -5.0000],[36.7500, 0.0000, -5.0000],[49.0000, 0.0000, -5.0000]],[[ 0.0000, 13.0000, -5.0000],[12.2500, 13.0000, -5.0000],[24.5000, 13.0000, -5.0000],[36.7500, 13.0000, -5.0000],[49.0000, 13.0000, -5.0000]],[[ 0.0000, 26.0000, -5.0000],[12.2500, 26.0000, -5.0000],[24.5000, 26.0000, -5.0000],[36.7500, 26.0000, -5.0000],[49.0000, 26.0000, -5.0000]],[[ 0.0000, 39.0000, -5.0000],[12.2500, 39.0000, -5.0000],[24.5000, 39.0000, -5.0000],[36.7500, 39.0000, -5.0000],[49.0000, 39.0000, -5.0000]]],[[[ 0.0000, 0.0000, -4.0000],[12.2500, 0.0000, -4.0000],[24.5000, 0.0000, -4.0000],[36.7500, 0.0000, -4.0000],[49.0000, 0.0000, -4.0000]],[[ 0.0000, 13.0000, -4.0000],[12.2500, 13.0000, -4.0000],[24.5000, 13.0000, -4.0000],[36.7500, 13.0000, -4.0000],[49.0000, 13.0000, -4.0000]],[[ 0.0000, 26.0000, -4.0000],[12.2500, 26.0000, -4.0000],[24.5000, 26.0000, -4.0000],[36.7500, 26.0000, -4.0000],[49.0000, 26.0000, -4.0000]],[[ 0.0000, 39.0000, -4.0000],[12.2500, 39.0000, -4.0000],[24.5000, 39.0000, -4.0000],[36.7500, 39.0000, -4.0000],[49.0000, 39.0000, -4.0000]]]])Process finished with exit code 0
部分转载于：
https://blog.csdn.net/dongjinkun/article/details/132590205
