DOC Adds code comment for _ConvNd.reset_parameters (#58931)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/55741 by adding a comment regarding the behavior of `kaiming_uniform_`
The docstring is correct in this case. For example:
```python
import math
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
in_channels = 120
groups = 2
kernel = (3, 8)
m = nn.Conv2d(in_channels=in_channels, groups=groups,
out_channels=100, kernel_size=kernel)
k = math.sqrt(groups / (in_channels * math.prod(kernel)))
print(f"k: {k:0.6f}")
print(f"min weight: {m.weight.min().item():0.6f}")
print(f"max weight: {m.weight.max().item():0.6f}")
```
outputs:
```
k: 0.026352
min weight: -0.026352
max weight: 0.026352
```
And when we plot the distribution, it is uniform with the correct bounds:
```python
_ = plt.hist(m.weight.detach().numpy().ravel())
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58931
Reviewed By: anjali411
Differential Revision: D28689863
Pulled By: jbschlosser
fbshipit-source-id: 98eebf265dfdaceed91f1991fc4b1592c0b3cf37
