Port legacy reflection_pad1d to ATen (#15480)
Summary:
1. Avoided using `THCDeviceTensor` by re-calculating the mapping from cuda (blockIdx, threadIdx) to input/output tensor index.
2. Changed Camelcase naming to underscore naming.
Profiling:
Legacy:
```bash
$py.test test/test_nn.py -k ReflectionPad1d -v -s
....
=========== 2 passed, 1258 deselected, 800 warnings in 4.35 seconds ============
```
Now:
```bash
$py.test test/test_nn.py -k ReflectionPad1d -v -s
...
=========== 2 passed, 1258 deselected, 800 warnings in 4.03 seconds ============
```
I have two questions about the code. Any insights are appreciated. gchanan zou3519
1. I can verify that [this magic](https://github.com/pytorch/pytorch/blob/master/aten/src/THCUNN/TemporalReflectionPadding.cu#L32-L36) correctly maps output index to input index in different cases. But, I have no idea about how did you come up with this algorithm that merges three categories (in left padding, in original input, in right padding) into a single statement?
2. Why do we need [get contiguous](https://github.com/pytorch/pytorch/blob/master/aten/src/THNN/generic/TemporalReflectionPadding.c#L80) tensors when calculating forward and backward propagation?
Reflection_pad2d porting will come in the next PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15480
Differential Revision: D13544924
Pulled By: mrshenli
fbshipit-source-id: 182045434f210032a82cab721a190da0cd781fbf
