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.

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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。

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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…

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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。

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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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1.torch.view(参数a,参数b,…) - CSDN博客

view()函数是用于对Tensor(张量)进行形状变化的函数,如一个Tensor的size是3x2,可以通过view()函数将其形状转为2x3。但是需要注意的是进行操作的张量必须是contiguous()的,即在在内存中连续的。(不连续可以使用tensor.contiguous()操作转为连续)。一、view()函数基本操作 函数定义:view(*args) [Ps:...

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python中view()函数怎么用? - CSDN博客

python中view()函数怎么用? qq_44275582: 一维向量,用逗号隔开来才算多维. python中view()函数怎么用? Tree-大马: 大佬,view里面的16*5*5是三维张量还是啥呀? 记录Linux下不同版本Python3的安装、环境变量配置、虚拟环境创建. LaoYuanPython: 抢到沙发,谢谢分享! 原创不易 ...

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【PyTorch】Tensorを操作する関数(transpose、view、reshape) - Qiita

view. viewもよく使われる関数です。 1つ目の引数に-1を入れることで、2つ目の引数で指定した値にサイズ数を自動的に調整してくれます。 Tensorの要素数が指定したサイズ数に合わない(割り切れない)場合、エラーになります。

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torch x = x.view(-1, ...)理解 - CSDN博客

这篇文章主要介绍了对pytorch中x = x.view(x.size(0), -1) 的理解说明,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧 在pytorch的CNN代码中经常会看到 x.view(x.size(0), -1) 首先,在pytorch中的view()函数就是用来改变tensor的形状的,例如将2行3列的tensor变为1行6列,其中-1表示会自适应的调整 ...

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numpy.ndarray.view() in Python | GeeksforGeeks

numpy.ndarray.view() helps to get a new view of array with the same data. Syntax: ndarray.view(dtype=None, type=None) Parameters: dtype : Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a. type : Python type, optional Returns : ndarray or matrix. Code #1: Python3

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