【pytorch】常用函数randperm

PyTorch的randperm函数详解

最新推荐文章于 2025-07-13 14:29:11 发布

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本文详细介绍了PyTorch中randperm函数的使用方法，包括参数解释、默认设置及示例代码。该函数用于生成指定范围内的随机排列张量，适用于深度学习和数据科学中的各种场景。

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torch. randperm ( n, out=None, dtype=torch.int64, layout=torch.strided, device=None, requires_grad=False ) → LongTensor

Returns a random permutation of integers from 0 to n - 1.

Parameters

n (int) – the upper bound (exclusive)
out (Tensor, optional) – the output tensor.
dtype (torch.dtype, optional) – the desired data type of returned tensor. Default: torch.int64.
layout (torch.layout, optional) – the desired layout of returned Tensor. Default: torch.strided.
device (torch.device, optional) – the desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.
requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default: False.

Example:

    >>> torch.randperm(4)
tensor([2, 1, 0, 3])

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