In general, if we are expecting the users to use the base class,
such as `_ConvNd`, we should rename it to something like
`BaseConv`. However, because this base class is only used inside of the
AO packages, there is no need to expose it to the users.
Test Plan:
```
python test/test_quantization.py
python test/test_module_init.py
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77344
Approved by: https://github.com/jerryzh168
For a GroupNorm module, if num_channels is not divisible by num_groups, we need to report an error when defining a module other than at the running step.
example:
```
import torch
m = torch.nn.GroupNorm(5, 6)
x = torch.randn(1, 6, 4, 4)
y = m(x)
```
before:
```
Traceback (most recent call last):
File "group_norm_test.py", line 8, in <module>
y = m(x)
File "/home/xiaobinz/miniconda3/envs/pytorch_mater/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1111, in _call_impl
return forward_call(*input, **kwargs)
File "/home/xiaobinz/miniconda3/envs/pytorch_mater/lib/python3.7/site-packages/torch/nn/modules/normalization.py", line 271, in forward
input, self.num_groups, self.weight, self.bias, self.eps)
File "/home/xiaobinz/miniconda3/envs/pytorch_mater/lib/python3.7/site-packages/torch/nn/functional.py", line 2500, in group_norm
return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: Expected number of channels in input to be divisible by num_groups, but got input of shape [1, 6, 4, 4] and num_groups=5
```
after:
```
Traceback (most recent call last):
File "group_norm_test.py", line 6, in <module>
m = torch.nn.GroupNorm(5, 6)
File "/home/xiaobinz/miniconda3/envs/pytorch_test/lib/python3.7/site-packages/torch/nn/modules/normalization.py", line 251, in __init__
raise ValueError('num_channels must be divisible by num_groups')
```
This PR also update the doc of num_groups.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74293
Approved by: https://github.com/jbschlosser
Summary:
Action following https://github.com/pytorch/pytorch/issues/66232
This change does require some context: there were several suggestions regarding what to do about this group of tests: tests that are core and crucial to all of PyTorch and are too broad to be owned by one team.
1. Let's add a "module: core" and put people behind it! This idea sounds appealing unless you are one of the people backing the label. From talking to albanD among others, this idea of putting all these core tests on the shoulder of a few people or one team isn't super fair and I have not yet found anyone willing to take on this job.
2. Taking advantage of the fact that we already have a triaging oncall that takes turns triaging issues, we can leave these tests essentially unlabeled and allow the oncall to triage these tests. Since these tests are crucial to PyTorch, we'll add the "high priority" label to mark them different from other unowned tests (see https://github.com/pytorch/pytorch/issues/67552).
3. I _could_ still create an unbacked label "module: core" and attribute these tests there, but I don't like the idea of creating a facade that the tests are "triaged" to a label when no one is actually taking a look.
Now we could potentially break these tests down into smaller files so that each piece _could_ be owned by a team, but 1. I don't know if this is currently feasible and 2. This approach does not prevent that from happening in the future.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67553
Reviewed By: albanD
Differential Revision: D32025004
Pulled By: janeyx99
fbshipit-source-id: 1fb1aa4c27e305695ab6e80ae3d02f90519939c0
Summary:
Fixes https://github.com/pytorch/pytorch/issues/27655
This PR adds a C++ and Python version of ReflectionPad3d with structured kernels. The implementation uses lambdas extensively to better share code from the backward and forward pass.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59791
Reviewed By: gchanan
Differential Revision: D29242015
Pulled By: jbschlosser
fbshipit-source-id: 18e692d3b49b74082be09f373fc95fb7891e1b56
