frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-20 21:14:14 +08:00
Code Issues Packages Projects Releases Wiki Activity

fix readme, bump version

Browse Source
This commit is contained in:
Soumith Chintala
2017-01-14 17:47:35 -05:00
committed by GitHub
parent 2290798a83
commit 133c1e927f
1 changed files with 5 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
README.md
View File

@ -1,4 +1,4 @@
# pytorch [alpha-5]
# pytorch [alpha-6]
- [About PyTorch?](#about-pytorch)
- [Installation](#installation)
@ -148,9 +148,10 @@ After that, we will reevaluate progress, and if we are ready, we will hit beta-0
* ~~alpha-2: sharing tensors across processes for hogwild training or data-loading processes. a rewritten optim package for this new nn.~~
* ~~alpha-3: binary installs, contbuilds, etc.~~
* ~~alpha-4: multi-GPU support, cudnn integration, imagenet / resnet example~~
* alpha-5: a ton of examples across vision, nlp, speech, RL -- this phase might make us rethink parts of the APIs, and hence want to do this in alpha than beta
* alpha-6: Putting a simple and efficient story around multi-machine training. Probably simplistic like torch-distlearn. Building the website, release scripts, more documentation, etc.
* ~~alpha-5: a ton of examples across vision, nlp, speech, RL -- this phase might make us rethink parts of the APIs, and hence want to do this in alpha than beta~~
* alpha-6: Building the website, release scripts, more documentation, etc.
* beta-0: First public release
* beta-1: Putting a simple and efficient story around multi-machine training. See: https://github.com/pytorch/pytorch/issues/241 and https://github.com/apaszke/pytorch-dist for current progress.
The beta phases will be leaning more towards working with all of you, convering your use-cases, active development on non-core aspects.
@ -239,7 +240,7 @@ queue = multiprocessing.Queue()
buffers = [torch.Tensor(2, 2) for i in range(4)]
for b in buffers:
queue.put(b)
processes = [multiprocessing.Process(target=fill, args=(queue,)).start() for i in range(10)]
processes = [multiprocessing.Process(target=fill, args=(queue,)).start() for i in range(10)]
```
```python