1. Dear sir, thanks for your email. I am still thinking about ordering the machine. How is the guarantee receiving the machine after doing the payment? (Please persuade your customer to trust you )
时间: 2023-03-11 08:42:35 浏览: 169
非常感谢您的邮件。我们保证出货后,客户可以收到质量符合标准的机器,我们的服务工程师也会提供有效的技术支持,保证机器可以正常使用。我们一直以提供高质量的产品和优质的服务赢得客户的信任,相信我们的产品可以给您带来完美的体验。
相关问题
Entries in a stack are "ordered". What is the meaning of this statement?
The statement "entries in a stack are ordered" means that the elements or items in a stack are arranged in a specific manner, usually in a last-in-first-out (LIFO) manner, where the most recently added item is the first one to be removed. This ordering is essential to the functioning of a stack, as it ensures that items are removed in the correct order and that the integrity of the data structure is maintained.
number of dimensions in the tensor input does not match the length of the desired ordering of dimensions i.e. input.dim() = 3 is not equal to len(dims) = 5
这个错误通常是由于输入的张量的维度数不符合所需的维度数。例如,当你尝试对一个形状为(1, 2, 3)的三维张量进行维度重排时,如果你使用了一个长度为5的维度顺序,那么就会报出这个错误。
要解决这个问题,你需要检查输入张量的维度数和所需维度顺序的长度是否一致。如果不一致,你需要修改维度顺序,使其与张量的维度数一致。你可以使用`torch.permute`函数进行维度重排,也可以使用`torch.transpose`函数进行维度交换。例如,对于一个形状为(1, 2, 3)的三维张量,如果你需要将其维度顺序改为(0, 2, 3, 1, 4),你可以使用以下代码:
```
import torch
x = torch.randn(1, 2, 3)
new_order = (0, 2, 3, 1, 4)
x = x.permute(new_order)
```
或者:
```
import torch
x = torch.randn(1, 2, 3)
new_order = (0, 2, 1)
x = x.transpose(new_order[0], new_order[1], new_order[2], 3, 4)
```
请注意,这只是一个示例,具体的维度顺序可能因情况而异。