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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.
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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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python pytorch中 .view()函数讲解 - CSDN博客
特殊用法view(-1) ... view函数的语法如下: ```python new_tensor = tensor.view(*shape) ``` 其中,tensor是待改变形状的张量,shape是目标形状,可以是一个元组或多个整数。值得注意的是,新张量的元素个数必须与原始张量的元素个数相同,否则会报错。 以下是一个示例: ```python import torch x = torch.randn ...
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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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torch — PyTorch 2.7 documentation
Create a view of an existing torch.Tensor input with specified size, stride and storage_offset. from_file. Creates a CPU tensor with a storage backed by a memory-mapped file. from_numpy. Creates ... from an external library into a torch.Tensor. frombuffer. Creates a 1-dimensional Tensor from an object that implements the Python buffer protocol. zeros. Returns a tensor filled with the scalar value 0, with the shape defined by the variable argument size. zeros_like. Returns a tensor filled ...
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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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PyTorch中的view()函数用法示例及其参数详解_.view(-1)-CSDN博客
引言:首先介绍一下,我们会在哪里遇到这个函数呢?最常见的就是在利用pytorch库搭建网络时,时不时的冒出一个,如果不会!你总是看不懂,以后也看不懂,如果有时间,大家一起来看看这个函数吧!1.tensor.view()函数。 (装逼)this fuction is also a resize fuction ,其实按照我们通俗的理解就是reshape,只不过这里是reshape的是张量,也就是将张量重新调整为自己想要的维度(形状 ...
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python - What's the difference between `reshape()` and `view()` in ...
torch.view has existed for a long time. It will return a tensor with the new shape. The returned tensor will share the underling data with the original tensor. See the documentation here.. On the other hand, it seems that torch.reshape has been introduced recently in version 0.4.According to the document, this method will. Returns a tensor with the same data and number of elements as input, but with the specified shape.
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1.torch.view(参数a,参数b,…) - CSDN博客
相当于numpy中resize()的功能,但是用法可能不太一样。我的理解是: 把原先tensor中的数据按照行优先的顺序排成一个一维的数据(这里应该是因为要求地址是连续存储的),然后按照参数组合成其他维度的tensor。比如说是不管你原先的数据是[[[1,2,3],[4,5,6]]]还是[1,2,3,4,5,6],因为它们排成一维向量都是6个元素,所以只要view后面的参数一致,得到的结果都...
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torch x = x.view(-1, ...)理解 - CSDN博客
在函数的参数中经常可以看到-1例如x.view(-1, 4) 这里-1表示一个不确定的数,就是你如果不确定你想要reshape成几行,但是你很肯定要reshape成4列,那不确定的地方就可以写成-1. 例如一个长度的16向量x, x.view(-1, 4)等价于x.view(4, 4) x.view(-1, 2)等价于x.view(8,2) 以此类推