Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://docs.pytorch.org/docs/stable/generated/torch.renorm.html below:

torch.renorm — PyTorch 2.7 documentation

torch.renorm(input, p, dim, maxnorm, *, out=None) → Tensor¶

Returns a tensor where each sub-tensor of input along dimension dim is normalized such that the p-norm of the sub-tensor is lower than the value maxnorm

Note

If the norm of a row is lower than maxnorm, the row is unchanged

Parameters

• input (Tensor) – the input tensor.

• p (float) – the power for the norm computation

• dim (int) – the dimension to slice over to get the sub-tensors

• maxnorm (float) – the maximum norm to keep each sub-tensor under

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> x = torch.ones(3, 3)
>>> x[1].fill_(2)
tensor([ 2.,  2.,  2.])
>>> x[2].fill_(3)
tensor([ 3.,  3.,  3.])
>>> x
tensor([[ 1.,  1.,  1.],
        [ 2.,  2.,  2.],
        [ 3.,  3.,  3.]])
>>> torch.renorm(x, 1, 0, 5)
tensor([[ 1.0000,  1.0000,  1.0000],
        [ 1.6667,  1.6667,  1.6667],
        [ 1.6667,  1.6667,  1.6667]])

Access comprehensive developer documentation for PyTorch

Get in-depth tutorials for beginners and advanced developers

Find development resources and get your questions answered

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4