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https://stackoverflow.com/questions/50792316/what-does-1-of-view-...

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What does `-1` of `view ()` mean in PyTorch? - Stack Overflow

if you are wondering what x.view(-1) does it flattens the vector. Why? Because it has to construct a new view with only 1 dimension and infer the dimension -- so it flattens it. In addition it seems this operation avoids the very nasty bugs .resize() brings since the order of the elements seems to be respected.

https://blog.csdn.net/Dust_Evc/article/details/121785089

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python pytorch中 .view()函数讲解 - CSDN博客

PyTorch中的.view()函数是一个用于改变张量形状的方法。它类似于NumPy中的.reshape()函数，可以通过重新排列张量的维度来改变其形状，而不改变张量的数据。在深度学习中，.view()函数常用于调整输入数据的形状以适应模型的输入要求，或者在网络层之间传递数据时进行形状的转换。

https://www.geeksforgeeks.org/how-does-the-view-method-work-in-py...

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How Does the "View" Method Work in Python PyTorch?

Here, .view(2, -1) reshapes the tensor into 2 rows, and the number of columns (12) is inferred automatically. Example 3: Making a Tensor Contiguous. If your tensor is not contiguous, you need to call .contiguous() before using .view(). Python

https://zhuanlan.zhihu.com/p/485688233

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【Pytorch】视图函数.view()用法汇总 - 知乎 - 知乎专栏

在使用pytorch定义神经网络时，经常会看到类似如下的.view()用法，这里对其用法做出讲解与演示。一、普通用法 (手动调整size) view()相当于reshape、resize，重新调整Tensor的形状。import torch a1 = torch.arang…

https://stackoverflow.com/questions/42479902/what-does-view-do-in...

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python - What does `view ()` do in PyTorch? - Stack Overflow

view() reshapes the tensor without copying memory, similar to numpy's reshape(). Given a tensor a with 16 elements:. import torch a = torch.range(1, 16) To reshape this tensor to make it a 4 x 4 tensor, use:. a = a.view(4, 4) Now a will be a 4 x 4 tensor.Note that after the reshape the total number of elements need to remain the same.

https://blog.51cto.com/u_12865/6444492

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python中view的用法 python view(-1) - 51CTO博客

python中view的用法 python view(-1)，使用pytorch框架定义神经网络时，经常会在代码中看到view()函数view()的作用相当于numpy中的reshape，重新定义矩阵的形状。一、例1普通用法：importtorchv1=torch.range(1,16)v2=v1.view(4,4)其中v1为116大小的张量，包含16个元素。v2为44大小的张量，同样包含16个元素。

https://blog.csdn.net/weixin_42018581/article/details/102502077

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PyTorch中的view()函数用法示例及其参数详解_.view(-1)-CSDN博客

1. view() tensor.view()方法可以调整tensor的形状，但必须保证调整前后元素总数一致。view不会修改自身的数据，返回的新tensor与原tensor共享内存，即更改一个，另一个也随之改变。在实际应用中，可能经常需要添加或者减少某一维度，这是sequeeze()和unsequeeze()这两个方法就派上了用场。

https://www.cnblogs.com/geeksongs/p/15034108.html

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【Pytorch】：x.view() view()方法的使用 - Geeksongs - 博客园

在pytorch当中，我们经常会用到x.view()方法来进行数据维度的变化，但是这个方法具体该如何使用呢？下面我来记录一下笔记：一.按照传入数字使数据维度进行转换首先，我们可以传入我们想要的维度，然后按照传入的数字对数据进行维度变化。比如，x.view()当中可以放入列表或者是单个数字，比如

https://stackoverflow.com/questions/57234095/what-is-the-differen...

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python - What is the difference between .flatten() and .view(-1) in ...

In addition to @adeelh's comment, there is another difference: torch.flatten() results in a .reshape(), and the differences between .reshape() and .view() are: [...] torch.reshape may return a copy or a view of the original tensor. You can not count on that to return a view or a copy. Another difference is that reshape() can operate on both contiguous and non-contiguous tensor while view() can ...

https://blog.csdn.net/u013593554/article/details/131365170

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Python函数.view(1,-1）和 .view(-1,1)有什么区别 - CSDN博客

文章浏览阅读3.6k次，点赞5次，收藏14次。.view(1,-1)将多维张量转换为行向量，而.view(-1,1)转换为列向量，两种方法均保持张量元素总数不变。它们根据原始张量的形状和指定的维度自动推断另一个维度，常用于数据重塑。

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