# What pytorch means by buffers?

**URL:** <https://discuss.pytorch.org/t/what-pytorch-means-by-buffers/120266>\
**Category:** Uncategorized\
**Created:** [May 5, 2021, 2:12am UTC](https://discuss.pytorch.org/t/what-pytorch-means-by-buffers/120266 "2021-05-05T02:12:25Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![seyeeet](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/seyeeet/32/21931_2.png) [@seyeeet](https://discuss.pytorch.org/u/seyeeet)\
**Post date:** [June 8, 2021, 4:55pm UTC](https://discuss.pytorch.org/t/what-pytorch-means-by-buffers/120266/3 "2021-06-08T16:55:24Z")

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I understand, thanks.

- is there a way to know all the buffers in a model?
- in case of bn that you mentioned how I can get the mean and std values? I reach to this point, but not sure how to get mean and std

```auto
import torchvision
import torch.nn as nn
import torch.nn.functional as F
resnet = torchvision.models.resnet50()
resnet.layer1[0].bn1.state_dict

```

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