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Revision Author Date Message Commit Date
1f9b938 Add some doc 17 May 2016, 13:33:35 UTC
7c6cdf0 Merge pull request #269 from lukeyeager/rockspec-cxx-flags Add CMAKE_CXX_FLAGS to rockspec 11 May 2016, 20:19:07 UTC
37f9196 Add CMAKE_CXX_FLAGS to rockspec Helps with building on Ubuntu 16.04 11 May 2016, 20:10:35 UTC
3495625 Merge pull request #267 from apaszke/spatial_nll Add SpatialClassNLLCriterion (with pre-Kepler support) 01 May 2016, 18:48:42 UTC
ef166c8 Add SpatialClassNLLCriterion (with pre-Kepler support) 01 May 2016, 18:37:05 UTC
c9b0b3f Merge pull request #266 from torch/revert-250-spatial_nll Revert "Add SpatialClassNLLCriterion" 01 May 2016, 16:41:49 UTC
c097e16 Revert "Add SpatialClassNLLCriterion" 01 May 2016, 16:41:28 UTC
89cf5f1 Merge pull request #261 from torch/dilated Adding SpatialDilatedConvolution 28 April 2016, 18:18:43 UTC
229a980 Merge pull request #250 from apaszke/spatial_nll Add SpatialClassNLLCriterion 28 April 2016, 03:46:40 UTC
dca99d8 Adding SpatialDilatedConvolution 27 April 2016, 22:21:54 UTC
3d97620 Merge pull request #260 from torch/multilabelmargin adding CUDA version of MultiLabelMarginCriterion + tests 27 April 2016, 19:20:06 UTC
2b9dff8 adding CUDA version of MultiLabelMarginCriterion + tests 27 April 2016, 18:56:00 UTC
9558c29 Merge pull request #259 from torch/dptfixes2 fixes to DataParallelTable for no parameter networks 27 April 2016, 18:54:20 UTC
b0c106c fixes to DataParallelTable for no parameter networks 27 April 2016, 18:52:02 UTC
6474907 Add SpatialClassNLLCriterion 26 April 2016, 19:04:05 UTC
17038fd Merge pull request #258 from apaszke/dpt_clearstate Fix clearState in DataParallelTable 25 April 2016, 21:53:10 UTC
8737702 Fix clearState in DataParallelTable Make it return the module, just like all other modules do. 25 April 2016, 21:51:39 UTC
24daf02 Merge pull request #257 from ngimel/clearState fix clearState for DataParallelTable 25 April 2016, 16:33:26 UTC
d764ff2 fix clearState for DataParallelTable 25 April 2016, 16:14:02 UTC
6c3c3f3 fixing tests sizes in Reflection and Replication padding tests to be valid (#255) 20 April 2016, 20:02:11 UTC
ca1b6e8 Fix VolumetrixMaxPooling tests (#254) 19 April 2016, 21:45:35 UTC
f03b92f add noBias for nn.Linear and nn.SpatialConvolution (#252) add tests testing done add noBias for nn.Linear and nn.SpatialConvolution add check in THCUNN_assertSameGPU add noBias for nn.Linear and nn.SpatialConvolution minor edits add noBias for nn.Linear and nn.SpatialConvolution 18 April 2016, 15:27:25 UTC
4e56a81 add backpropagation for bachnormalization in evaluation mode (#251) add tests for batchnormalization in evaluation mode fix bugs BatchNormalization: compute save_mean and save_std in evaluattion mode 16 April 2016, 17:33:48 UTC
3d75c1e distkldiv test fix 13 April 2016, 15:41:41 UTC
dd13411 Remove use of broken THInf macro, which caused UB * [VolmetricMaxPooling] Remove use of broken THInf macro, which caused UB * [SpatialFractionalMaxPooling] Remove use of broken THInf macro, which caused UB 12 April 2016, 18:01:23 UTC
1b0c643 [LookupTable] Add Max-norm constraints to LookupTable (#240) 11 April 2016, 20:40:44 UTC
2fee130 Merge pull request #244 from hughperkins/cunn-test-alias Add alias cunn.test(), following eg format of cutorch.test() 08 April 2016, 15:13:10 UTC
d9e4072 Merge pull request #243 from hughperkins/remove-testsuite-warning remove warnings about testsuite 08 April 2016, 14:47:10 UTC
0687c41 Add alias cunn.test(), following eg format of cutorch.test() 08 April 2016, 13:37:02 UTC
d168951 remove warnings about testsuite 08 April 2016, 13:28:14 UTC
c9f24c7 Merge pull request #239 from caldweln/cuda make margin parameterizable 22 March 2016, 13:45:00 UTC
cb3122d make margin parameterizable 22 March 2016, 09:08:14 UTC
64959b2 Merge pull request #223 from ebetica/sparse_linear Adding SparseLinear with CUDA 18 March 2016, 18:33:51 UTC
cc683ed Adding SparseLinear for CUDA 18 March 2016, 18:14:10 UTC
667f47b Merge pull request #238 from anibali/inplace_elu In-place ELU 14 March 2016, 17:16:10 UTC
908e558 In-place ELU 10 March 2016, 01:01:29 UTC
3827fcd Merge pull request #237 from apaszke/err_msg_fix THNN -> THCUNN in assertSameGPU 09 March 2016, 12:46:04 UTC
6ef8d65 THNN -> THCUNN in assertSameGPU 09 March 2016, 09:15:17 UTC
8a5347d Merge pull request #235 from apaszke/err_msg Add an error message for checkGPU assertion 08 March 2016, 21:57:02 UTC
ee63c24 Add THCUNN_h.lua to .gitignore 08 March 2016, 21:01:24 UTC
5b3dc54 Add an error message for checkGPU 08 March 2016, 21:00:59 UTC
c841015 Merge pull request #234 from fmassa/THCUNN_header Reuse headers from THCUNN.h in THCUNN.lua 08 March 2016, 18:19:43 UTC
5b02b61 Reuse headers from THCUNN.h in THCUNN.lua 08 March 2016, 18:00:09 UTC
fc2a0b3 fix cuda arch for cuda 6.5 06 March 2016, 16:55:47 UTC
514c0c0 Merge pull request #230 from szagoruyko/patch-3 Remove CMakeLists CUDA 5 os x workaround 01 March 2016, 00:09:49 UTC
1e02bf9 remove CMakeLists CUDA 5 os x bugfix not relevant as we are on 6.5 at least 29 February 2016, 23:46:37 UTC
a974027 Merge pull request #229 from torch/cleanup removing useless unit.cu, utils.h and utils.cu 29 February 2016, 23:36:43 UTC
a6aa130 removing useless unit.cu, utils.h and utils.cu 29 February 2016, 23:36:20 UTC
41c750f Merge pull request #228 from torch/softmargincriterion SoftMarginCriterion 29 February 2016, 21:19:08 UTC
932bb48 SoftMarginCriterion 29 February 2016, 21:17:44 UTC
629f028 Merge pull request #214 from Jerrynet/master Do flattenParameters() only once 29 February 2016, 19:02:56 UTC
fef7354 Merge pull request #227 from fmassa/conv_assert Add extra checks for convolution parameters 27 February 2016, 16:22:56 UTC
e73c473 Add checks for convolution parameters 27 February 2016, 11:11:38 UTC
f3b07db Merge pull request #224 from colesbury/bn Add per-activation BatchNormalization implementation. 26 February 2016, 04:06:52 UTC
8cd0609 Add per-activation BatchNormalization implementation. The batch normalization code now works for 2D (per-activation), 4D (spatial) and 5D (volumetric) tensors. The per-activation case is not optimized. 25 February 2016, 20:02:06 UTC
9a297de Merge pull request #225 from torch/reflect adding SpatialReflectionPadding and SpatialReplicationPadding 25 February 2016, 01:24:37 UTC
86ef4ae adding SpatialReflectionPadding and SpatialReplicationPadding 25 February 2016, 01:23:10 UTC
ef1f945 Merge pull request #222 from fbesse/volumetric_full_fix Fixed VolumetricFullConvolution. 23 February 2016, 19:05:57 UTC
2b5dd14 Merge pull request #219 from jhjin/master Remove redundant and unused headers 20 February 2016, 03:25:15 UTC
508eae3 Remove redundant and unused headers Clean-up after the THCUNN conversion 20 February 2016, 02:34:52 UTC
12ada98 Merge pull request #218 from torch/multimargweight added weights to MultiMarginCriterion 20 February 2016, 01:47:59 UTC
56c3ed2 added weights to MultiMarginCriterion 20 February 2016, 01:42:47 UTC
de6acba Merge pull request #217 from torch/padValue adding padValue to LookupTable 19 February 2016, 23:48:14 UTC
c00281f adding padValue to LookupTable 19 February 2016, 23:36:40 UTC
2456639 fix merge typo 19 February 2016, 21:03:40 UTC
7be711d Merge pull request #215 from torch/multmargfix Fix sizeAverage bug in MultiMarginCriterion (divide by nbatch, not ndim) 19 February 2016, 20:14:48 UTC
6c19d69 multmargsizeavgfix 19 February 2016, 20:11:55 UTC
be370df Do flattenParameters() only once Prevent parameters to be flattened more than once 19 February 2016, 13:11:55 UTC
0e23843 Reimplemented VolumetricFullConvolution in the same fashion as SpatialFullConvolution. 18 February 2016, 15:33:00 UTC
c837a7f Merge pull request #207 from fmassa/THCUNN_fmassa2 THCUNN Spatial* conversion 17 February 2016, 23:52:59 UTC
f25d5b6 Merge pull request #212 from colesbury/master Zero gradients on secondary GPUs after accGradParameters 17 February 2016, 21:59:35 UTC
95f351f Zero gradients on secondary GPUs after accGradParameters Before this change, calling forward & backward multiple times without calling zeroGradParameters would compute an incorrect gradient. Fixes #209 17 February 2016, 21:28:11 UTC
c79b0c0 Merge pull request #211 from apaszke/master Instantiate impl field in older models 15 February 2016, 21:59:15 UTC
656adc3 Instantiate impl field in older models 15 February 2016, 21:56:41 UTC
99c34f8 Merge pull request #208 from torch/cunn include -> require 13 February 2016, 00:32:41 UTC
a6d720c include -> require 13 February 2016, 00:32:08 UTC
f3c3420 THNN conversion of Spatial* modules 11 February 2016, 14:33:42 UTC
19c1333 Moving Spatial* to lib/THCUNN 11 February 2016, 07:51:53 UTC
42ee94a Merge pull request #206 from torch/temporal_thcunn moving Temporal* to THCUNN 10 February 2016, 16:34:19 UTC
6e32345 moving Temporal* to THCUNN 10 February 2016, 16:30:28 UTC
ab2b009 Merge pull request #205 from ivankreso/master Fix thread configuration in inference mode 08 February 2016, 20:34:51 UTC
b1dc789 Fix thread configuration in inference mode 08 February 2016, 16:53:04 UTC
8fc9450 Merge pull request #204 from andreaskoepf/THCUNN_koepf_5 TCUHNN functional module conversions batch 5 (Volumetric*) 03 February 2016, 02:40:22 UTC
a4bbf8d Remove 'dimension aliases' from VolumetricConvolution 03 February 2016, 00:57:40 UTC
7473557 Add THCUNN conversion of Volumetric* modules 02 February 2016, 23:38:28 UTC
a3314eb Move Volumetric*.cu -> lib/THCUNN 02 February 2016, 23:38:28 UTC
469710a Merge pull request #189 from colesbury/master Add multi-threading support in DataParallelTable 02 February 2016, 19:46:07 UTC
97f66e1 Add multi-threading support in DataParallelTable This lets us use the fastest CUDNN R4 kernels with DPT, which have much higher launch overhead. With single-threaded dispatch, the launch overhead from these kernels delays the second, third, and fourth GPUs so much that it actually increases the total time. I've also included some other optimizations: - gradInput can be set to nil when the DataParallelTable is the top-level module; this saves time and memory - input can optionally be on the CPU; this saves memory on the first GPU, and is faster when the input is in pinned memory since the copies to each GPU happen concurrently. This change is mostly backwards compatible, with the below caveats: - The preferred way to add modules is by a single call to add with the list of GPUs i.e. add(module, {1, 2, 3, 4}) - DataParallelTable:get() only works with the first module 02 February 2016, 19:39:46 UTC
a1cdf09 Merge pull request #198 from andreaskoepf/THCUNN_koepf_4 THCUNN functional module conversions batch 4 02 February 2016, 14:16:03 UTC
563b1e7 minor bufix in LeakyReLU 02 February 2016, 04:41:10 UTC
cd76372 adding 5.2 cuda arch to cmake 02 February 2016, 04:18:29 UTC
c7ee6c3 Add THCUNN conversions of {RReLU, Sigmoid, SmoothL1Criterion, ...} Converted modules: RReLU Sigmoid SmoothL1Criterion SoftMax SoftPlus SoftShrink Sqrt Square Tanh Threshold 01 February 2016, 21:22:28 UTC
b382db0 Move {RReLU.cu, Sigmoid.cu, SmoothL1Criterion.cu,..} to lib/THCUNN Files moved: RReLU.cu Sigmoid.cu SmoothL1Criterion.cu SoftMax.cu SoftPlus.cu SoftShrink.cu Sqrt.cu Square.cu Tanh.cu Threshold.cu 01 February 2016, 20:55:50 UTC
707e087 Add THCUNN conversions of {MSE, Margin, MultiMargin}Criterion & PReLU 01 February 2016, 20:55:50 UTC
7a30e65 Move {MarginCriterion, MSECriterion, MultiMarginCriterion, PReLU}.cu -> lib/THCUNN 01 February 2016, 20:45:58 UTC
01d6c74 Merge pull request #203 from fmassa/THCUNN_fmassa_1 THCUNN functional conversion batch 3 01 February 2016, 13:06:35 UTC
a02b65f Add THNN conversion of {Spatial(Adaptive,Average,Max)Pooling} and SpatialConvolutionMM 27 January 2016, 22:02:53 UTC
95724b4 Move {SpatialConvolutionMM, Spatial(Adaptive,Average,Max)Pooling} to lib/TCUNN 27 January 2016, 21:59:39 UTC
edd692a Merge pull request #202 from kmul00/volmaxpool_pad Added padding option to Volumetric Max Pooling (CUDA) 27 January 2016, 20:18:31 UTC
eeff62e Added padding option to Volumetric Max Pooling (CUDA) modified: VolumetricMaxPooling.cu modified: test.lua 27 January 2016, 18:13:49 UTC
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