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The torch.view method in PyTorch is used to reshape a tensor without changing its data. It returns a new tensor with the same data but a different shape1.
Example
import torchx = torch.randn(4, 4)print(x.size()) # torch.Size([4, 4])y = x.view(16)print(y.size()) # torch.Size([16])z = x.view(-1, 8) # -1 infers the dimension from other dimensionsprint(z.size()) # torch.Size([2, 8])Important Considerations
Contiguity
For a tensor to be viewed, the new view size must be compatible with its original size and stride. If not, it will not be possible to view the tensor without copying it (e.g., via contiguous()). When unsure, use reshape(), which returns a view if shapes are compatible and copies otherwise2.
Shared Data
The view tensor shares the same underlying data with its base tensor. Modifying the view will reflect in the base tensor as well2.
Limitations
What does `-1` of `view ()` mean in PyTorch? - Stack Overflow
Jun 11, 2018 · If you have a = torch.arange(1, 18) you can view it various ways like a.view(-1,6),a.view(-1,9), a.view(3,-1) etc.
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torch.Tensor.view — PyTorch 2.6 documentation
torch.Tensor.view¶ Tensor. view (* shape) → Tensor ¶ Returns a new tensor with the same data as the self tensor but of a different shape. The returned tensor shares the same data and must …
What does .view(-1) do? - PyTorch Forums
Jan 23, 2021 · The view(-1) operation flattens the tensor, if it wasn’t already flattened as seen here: x = torch.randn(2, 3, 4) print(x.shape) > torch.Size([2, 3, 4]) x = x.view(-1) print(x.shape) …
torch x = x.view(-1, ...)理解 - CSDN博客
Sep 4, 2018 · view(1, -1)：这种形式的 .view() 操作将张量重新塑造为一个行数为 1，列数自动推断的二维张量。如果张量原来的形状是 (a, b, c)，则 .view(1, -1) 将其转换为 (1, a * b * c) 的形状。
torch:)——PyTorch: view( )用法详解 - CSDN博客
Nov 13, 2020 · PyTorch 中的view ( ) 函数 相当于 numpy 中的resize ( )函数，都是用来重构 (或者调整)张量维度的，用法稍有不同。 1. view (参数a, 参数b, 参数c…) >>> re = torch.tensor([1, 2, 3, 4, 5, 6]) >>> result = re.view(3,2) >>> result. i.e. …
What is the difference of .flatten() and .view(-1) in PyTorch?
Jul 27, 2019 · The overhead that flatten() function introduces is only from its internal simple computation of the tensor’s output shape and the actual call to the view() method or similar. …
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PyTorch Tensor.view() method (with example) - Sling Academy
Jul 14, 2023 · A view of a tensor is a new tensor that shares the same underlying data with the original tensor but has a different shape or size. The Tensor.view() method is used to reshape …
PyTorch中的view()函数用法示例及其参数详解_.view(-1)-CSDN博客
Oct 11, 2019 · 首先，view ( ) 是对 PyTorch 中的 Tensor 操作的，若非 Tensor 类型，可使用 data = torch.tensor(data) 来进行转换。 (1) 作用：该函数返回一个有__相同数据__但不同大小的 …
Pytorch View (-1) Function Explained - Restackio
Learn how to use the Pytorch view (-1) function for reshaping tensors efficiently in your deep learning projects. In PyTorch, a tensor can serve as a View of another tensor, sharing the …
python - PyTorch View -1 Placeholder - reshape
Feb 25, 2025 · When you use -1 for a dimension in view() or reshape(), PyTorch calculates the size of that dimension so that the total number of elements in the resulting tensor matches the …
How Does the “View” Method Work in Python PyTorch?
Aug 23, 2024 · You can use -1 in .view() to let PyTorch automatically infer the appropriate size for one of the dimensions. Python import torch # Create a 3D tensor tensor = torch . randn ( 2 , 3 , …
PyTorch View Tutorial [With 11 Examples] - Python Guides
Sep 2, 2022 · In this section, we will learn about the PyTorch view in python. The PyTorch view () function is used to convert the tensor into a 2D format which is rows and columns. And we …
python - Optimizing Tensor Flattening in PyTorch: Performance …
flattened_tensor = tensor.view(-1) This flattens the tensor using the view() method. tensor.view(-1) reshapes the tensor into a 1D tensor. The -1 tells PyTorch to automatically calculate the size of …
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