WeightedRandomSampler throws warning for copy constructor

[ptrblck]

🐛 Minor Bug

Passing a weights tensor to WeigthedRandomSampler throws a warning:

UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).

This is due to this line of code.

Reported by Wafaa_Wardah in this post.

To Reproduce

Steps to reproduce the behavior:

import torch
from torch.utils.data import WeightedRandomSampler

weights = torch.randn(10)
sampler = WeightedRandomSampler(weights=weights, num_samples=10)

Environment

• PyTorch Version (e.g., 1.0): 1.0.0.dev20190104

Possible bug fix:

I think the easiest way to fix this issue would be to change the current line from

self.weights = torch.tensor(weights, dtype=torch.double)

to

self.weights = torch.as_tensor(weights, dtype=torch.double)

CC @ssnl Let me know, if that would be sufficient and I can create a fast PR for this.

Best,
ptrblck