torch.cat,torch.concat, torch.concatenate

最新推荐文章于 2024-06-07 21:20:41 发布

原创最新推荐文章于 2024-06-07 21:20:41 发布 · 3.4k 阅读

2 ·

CC 4.0 BY-SA版权

文章标签：

#pytorch #深度学习 #python

Pytorch 专栏收录该内容

4 篇文章

订阅专栏

文章介绍了PyTorch库中的torch.cat(),torch.concat(),torch.concatenate()这三个函数的等效性，它们用于沿指定维度合并多个张量。这些函数适用于形状一致或空张量的拼接，并且可以视为torch.split()和torch.chunk()的逆操作。

部署运行你感兴趣的模型镜像

torch.cat, torch.concat, torch.concatenate将向量按照指定的维度进行拼接。这三个函数是同一个函数，互为彼此的别名。函数的定义函数写在torch.cat。

TORCH.CONCATENATE
torch.concatenate(tensors, axis=0, out=None) → Tensor
Alias of torch.cat().

TORCH.CONCAT
torch.concat(tensors, dim=0, *, out=None) → Tensor
Alias of torch.cat().

torch.cat(tensors, dim=0, *, out=None) → Tensor
Concatenates the given sequence of seq tensors in the given dimension. 
All tensors must either have the same shape (except in the concatenating dimension) or be empty.

torch.cat() can be seen as an inverse operation for torch.split() and torch.chunk().

torch.cat() can be best understood via examples.

SEE ALSO

torch.stack() concatenates the given sequence along a new dimension.

Parameters
tensors (sequence of Tensors) – any python sequence of tensors of the same type. 
Non-empty tensors provided must have the same shape, except in the cat dimension.

dim (int, optional) – the dimension over which the tensors are concatenated

Keyword Arguments
out (Tensor, optional) – the output tensor.

您可能感兴趣的与本文相关的镜像