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643 Commits

Author SHA1 Message Date
Gregory Chanan
171638a451 Fix test_normalize NN test. 2017-05-09 14:25:06 -07:00
Gregory Chanan
ae2b2cbbec Make keepdim work with autograd. 2017-05-09 14:15:59 -07:00
Sergey Zagoruyko
6d693fe413 Add F.normalize (#1467) 2017-05-07 13:54:16 +02:00
Marvin CAO
e3f41a4962 Add high order gradient support for Sigmoid (#1496) 2017-05-07 13:00:20 +02:00
Ankit Vani
4e18d89791 added twice differentiation for a bunch of ops (#1426) 2017-05-04 06:47:14 -04:00
andrew giessel
2e7635b929 Add flexible bilinear upsampling aspect ratio redux (#1317) 2017-05-03 08:46:28 -04:00
Soumith Chintala
ecd51f8510 docs fixes 2017-05-02 15:42:33 -04:00
Soumith Chintala
7dd8571bc6 fix avg_pool docs in nn.functional 2017-04-30 08:44:43 -04:00
Adam Paszke
457d78a7d9 Use THCUNN backward kernels for Tanh and Sigmoid in Autograd (#1399) 2017-04-29 09:07:03 -04:00
Uridah Sami Ahmed
75f1989bec Add nn.Bilinear and tests 2017-04-28 10:11:30 -04:00
Shubham Jain
a35f507532 Update functional.py (#1298) 2017-04-19 11:07:12 -04:00
Edward Z. Yang
34546f022a Expose dilated convolutions. 
Fixes #1225.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>
 2017-04-18 17:13:02 -04:00
Edward Z. Yang
ab77742f6e Add some missing documentation for arguments. 
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
 2017-04-18 17:13:02 -04:00
Christian Sarofeen
e9ff57176b Fused pointwise kernels for GRU/LSTM 2017-04-11 13:42:06 -07:00
Christian Sarofeen
0b50f794e9 Use thnn version of Tanh/Sigmoid instead of autograd. (#1234) 2017-04-11 12:49:57 -07:00
Edgar Riba
9504246c32 add triplet margin loss (#1165) 2017-04-05 22:17:58 -04:00
Soumith Chintala
2979f4b989 add more functions to docs 2017-03-29 01:29:17 -04:00
Jason Kuen
f2c1071c33 Adaptive max and average pooling (1D & 2D) (#1084) 2017-03-26 17:09:28 +02:00
Edgar Riba
63f6c0d692 add Pairwise distance (#835) 2017-03-24 11:29:40 -04:00
ngimel
b3ab4b1094 Check torch.backends.cudnn.enabled, padding, and output_padding (#996) 
* Check torch.backends.cudnn.enabled
* Don't allow negative padding and output_padding values
 2017-03-22 19:42:11 -04:00
Kentaro Wada
7654b3f49e Add function to compute cross_entropy for 2D image (#802) 2017-03-16 17:34:04 +01:00
Soumith Chintala
13b1580613 add F.pad to docs 2017-03-15 00:09:14 -04:00
Sam Gross
34ce58c909 Parallelize backwards 2017-03-03 11:26:00 -08:00
Sergey Zagoruyko
12efd53dba ConstantPad2d and F.pad (#856) 2017-03-01 19:39:44 +01:00
Ofir Press
5e1d6a3691 Update functional.py (#862) 
Fixed documentation error in conv3d
 2017-02-27 10:42:02 -05:00
陈云
838842d4b2 fix documentation error. [issue #790](https://github.com/pytorch/pytorch/issues/790) (#831) 2017-02-23 08:59:29 +01:00
Joo-Kyung Kim
336eeee895 kernel_size as the default stride for avg_pool1d (#744) 
Following the documentation, let stride to be kernel_size if stride is not provided.
 2017-02-15 13:12:18 +05:30
Soumith Chintala
d4c9a3782b billinear -> bilinear, docs for upsampling, improved docs for Unpooling, pep8 tests fix (#617) 
* billinear -> bilinear, docs for upsampling, improved docs for Unpooling, pep8 tests fix
 2017-01-30 05:08:48 +05:30
Luke Yeager
3ed720079e [pep8] Fix most remaining lint manually 2017-01-28 01:15:51 +01:00
Luke Yeager
e7c1e6a8e3 [pep8] Fix most lint automatically with autopep8 
Here's the command I used to invoke autopep8 (in parallel!):

    git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i

Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.

Also configures flake8 to match pep8's behavior.

Also configures TravisCI to check the whole project for lint.
 2017-01-28 01:15:51 +01:00
Adam Paszke
f8d4f980b3 Add upsampling modules and functions 2017-01-24 17:30:50 -05:00
Alykhan Tejani
f8e89fbe11 fix docs for torch.nn.functional.conv1d (#536) 2017-01-21 10:41:52 -05:00
Adam Paszke
ee4c77c59f Docs improvements (#512) 
* Always compile .numpy() for all types

* Add torch.nn.functional docs and hidden headers

* Use sphinx to generate torchvision docs

* Remove unused import in ffi utils
 2017-01-19 17:28:49 -05:00
Sergey Zagoruyko
9c218b419f kl_div and docs (#429) 2017-01-17 19:24:01 -05:00
Adam Paszke
1dbf44c00d Add SmoothL1Loss to functional 2017-01-16 12:59:47 -05:00
Sam Gross
3a07228509 Add ConvTranspose1d module (#449) 2017-01-13 15:22:57 -05:00
Sam Gross
24a2f2e3a0 Add MaxUnpool1d module (#447) 2017-01-13 14:36:25 -05:00
Sam Gross
d5e45b2278 Add AvgPool1d which just uses AvgPool2d implementation (#439) 2017-01-12 15:07:11 -05:00
Sam Gross
fd92470e23 Add cuDNN bindings for BatchNorm (#421) 2017-01-07 15:35:24 -05:00
Adam Paszke
483490cc25 Move PixelShuffle implementation to functional 2016-12-30 23:02:57 +01:00
Adam Paszke
8d60e39fdc Rename torch.nn.functions to torch.nn._functions 2016-12-30 23:02:57 +01:00
Sam Gross
c367e0b64e Support dilated 1d and 3d convolutions (#372) 
Fixes #367
 2016-12-29 18:20:32 -05:00
Sergey Zagoruyko
62af45d99f Basic functional interface (#354) 2016-12-29 22:53:57 +01:00