aboutsummaryrefslogtreecommitdiffhomepage
Commit message (Collapse)AuthorAge
* suggest is_training not known at construction time (#9723)Gravatar Androbin2017-05-06
| | | | | | * suggest is_training not known at construction time * Slight modification to keep style with line 162
* Including batch_norm as the normalizer function by default, as mentioned in ↵Gravatar Kwotsin2017-05-06
| | | | | | | | | | function description (#9652) * fixed separable_conv2d description error and included batch_norm by default as mentioned in description * Update layers.py * Update layers.py
* Link to gcc_s and gcc if compiler is GCC version 5. Fixes issue #9593 (#9642)Gravatar Erik Smistad2017-05-05
|
* Making sure GLSTMCell is visible through tf.contrib.rnn.GLSTMCell (#9704)Gravatar Oleksii Kuchaiev2017-05-05
| | | | | | * Making sure GLSTMCell is visible through tf.contrib.rnn.GLSTMCell * GLSTM: better way to infer batch size
* Merge pull request #9706 from vrv/branch_155249446Gravatar Vijay Vasudevan2017-05-05
|\ | | | | Branch 155249446
| * Rolling back bad internal merge commit that makes Android fail.Gravatar Vijay Vasudevan2017-05-05
| |
| * merge fixGravatar Vijay Vasudevan2017-05-05
| |
| * Merge commit for internal changesGravatar Vijay Vasudevan2017-05-05
|/|
| * Remove opensource_only dir.Gravatar Yifei Feng2017-05-05
| |
| * Add a profiler that dumps data in pprof format.Gravatar Anna R2017-05-05
| | | | | | | | Change: 155249446
| * Add bilinear interpolation to tf.contrib.image.Gravatar Dan Ringwalt2017-05-05
| | | | | | | | Change: 155247916
| * Use the proper units to encode frequenciesGravatar Benoit Steiner2017-05-05
| | | | | | | | Change: 155247835
| * Set inline <script> tags to strict modeGravatar A. Unique TensorFlower2017-05-05
| | | | | | | | | | | | | | | | The "const" and "let" keywords cause problems in some browsers when not running in strict mode. Fixes #9075 Change: 155245440
* | Fix build scripts for MKL (#9698)Gravatar Shanqing Cai2017-05-05
| |
| * Modify make_export_strategy to work with core Estimator.Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155243616
| * Clean up TensorBoard build and fix sync processGravatar Justine Tunney2017-05-05
| | | | | | | | Change: 155237534
| * Internal change.Gravatar Alexandre Passos2017-05-05
| | | | | | | | Change: 155236037
* | Fix error of version_info.cc not being generated on windows if building ↵Gravatar Erik Smistad2017-05-05
| | | | | | | | python bindings is disabled in CMake (#9660)
| * Updated numbers after running benchmarks on updated ResNet model.Gravatar Toby Boyd2017-05-05
| | | | | | | | Change: 155230686
| * - Adds a tutorial for dense kernel methods.Gravatar Petros Mol2017-05-05
| | | | | | | | | | - Adds a README file to contrib/kernel_methods Change: 155228213
| * Use hlo_matchers in more tests.Gravatar Justin Lebar2017-05-05
| | | | | | | | Change: 155225266
| * Add d3 v4Gravatar Justine Tunney2017-05-05
| | | | | | | | | | | | | | | | | | The old version will be deleted when the migration is completed. The new version can be referenced with the following build labels: - @org_d3js_v4 (for d3.js) - //tensorflow/tensorboard/components/tf_imports:d3v4.d.ts Change: 155224862
| * Fix a bug in save_model_cli 'show'.Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155217646
| * Added cross compatibility to contrib feature columns: sparse_column_with_*, ↵Gravatar Mustafa Ispir2017-05-05
| | | | | | | | | | | | weighted_sparse_column, one_hot_column, embedding_column Change: 155217545
| * Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155214850
| * [XLA] Remove useless log message when dumping HLO GraphDef.Gravatar Eric Liu2017-05-05
| | | | | | | | | | This produces too much output that is not helpful. Change: 155212076
| * Go: Update generated wrapper functions for TensorFlow ops.Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155210529
| * Removing unnecessary lines from gitignoreGravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155210210
| * Merge changes from github.Gravatar Dan Ringwalt2017-05-05
| | | | | | | | Change: 155209832
| * Add `categorical_column_with_identity`.Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155209179
| * Open sourced the analytical cost modelGravatar Benoit Steiner2017-05-05
| | | | | | | | Change: 155208347
| * Update load functionality in SavedModel loader to use the Session graph and ↵Gravatar Sukriti Ramesh2017-05-05
| | | | | | | | | | | | not the default graph. Change: 155207584
| * Automated rollback of change 155096835Gravatar A. Unique TensorFlower2017-05-05
| | | | | | | | Change: 155203119
* | Misspellings on the saved_model_cli.py (#9684)Gravatar Chris Hoyean Song2017-05-05
| | | | | | information => information
| * Added missing 's' on and in `bijectors` guide, fixing the links.Gravatar Mark Daoust2017-05-05
| | | | | | | | | | fixed link to `kl_divergence` in `distributions` guide. Change: 155196210
| * [TF:XLA] Update LLVM revision to SVN revision r302214.Gravatar Peter Hawkins2017-05-05
| | | | | | | | Change: 155192906
* | Merge pull request #9677 from vrv/branch_155159972Gravatar Vijay Vasudevan2017-05-04
|\ \ | | | | | | Branch 155159972
* | | This fixes some issue introduced in the previous version where RTTI (#9671)Gravatar Guenther Schmuelling2017-05-04
| | | | | | | | | | | | | | | | | | was removed from the exclusion list. Because of this the number of symbols in the def file was close to 64K for gpu builds and yesterday a few added symbols pushed us over the 64K limit for the windows linker. Adding RTTI back to the exclusion list.
| * | Merge commit for internal changesGravatar Vijay Vasudevan2017-05-04
|/| | | |/
| * Implement ClusterSpec Propagation in TF MasterGravatar Brennan Saeta2017-05-04
| | | | | | | | | | | | | | | | | | | | | | ClusterSpec propagation is a capability upgrade for TensorFlow that should make it much easier to (1) build distributed TensorFlow clusters, and (2) handle node failures. The ClusterSpec propagation capability allows TensorFlow workers to be booted independently of each other, and with no knowledge about others. The client can then construct a ClusterDef (ClusterSpec), and then send it to the TF master at session creation. The master in turn then propagates the ClusterDef along to all of the workers. Change: 155159972
| * Android demo: Allow DetectorActivity to gracefully degrade if no native ↵Gravatar Andrew Harp2017-05-04
| | | | | | | | | | | | | | ObjectTracker support is found. If libtensorflow_demo.so is not found in the APK, rendered boxes will simply be stationary and will be replaced whenever new results come in. Partially addresses #6385 Change: 155159326
| * RNN checkpoint migration toolGravatar Shanqing Cai2017-05-04
| | | | | | | | Change: 155158477
| * Add `categorical_column_with_vocabulary_list`.Gravatar A. Unique TensorFlower2017-05-04
| | | | | | | | Change: 155158042
| * Automated rollback of change 155136555Gravatar Justine Tunney2017-05-04
| | | | | | | | Change: 155156366
* | replace sleep macro with an inline function (#9663)Gravatar Erik Smistad2017-05-04
| |
| * Include c++ gradients in c_api build rule.Gravatar Suharsh Sivakumar2017-05-04
| | | | | | | | | | | | #6268 #9150 Change: 155146664
| * [TF] optimization: SparseTensorDenseMatMul GPU kernel rewritten in pure cuda.Gravatar Eugene Brevdo2017-05-04
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Also added an additional GPU int32::max check that was missing. Performance seems to be between 1x-10x faster on average. The likely culprit on CPU slowdown was probably the unnecessary temp allocation for scratch space. Performance on a k40, compiled -c opt --config cuda --copt=-mavx: **BEFORE** Matrix sizes: A sparse [m, k] with % nonzero values between 1% and 80% B dense [k, n] % nnz n gpu m k dt(dense) dt(sparse) dt(sparse)/dt(dense) 0.01 50 True 100 100 0.000319954 0.000275495 0.861045 0.01 50 True 100 1000 0.000469565 0.000290895 0.619497 0.01 50 True 1000 100 0.000572815 0.000271131 0.473331 0.01 50 True 1000 1000 0.00133119 0.00042006 0.315554 0.01 50 False 100 100 0.00034191 0.000289171 0.845751 0.01 50 False 100 1000 0.0004796 0.00028483 0.593891 0.01 50 False 1000 100 0.000632371 0.000300461 0.475134 0.01 50 False 1000 1000 0.00134726 0.000576285 0.427746 0.01 100 True 100 100 0.000353755 0.00027729 0.783849 0.01 100 True 100 1000 0.000536649 0.00028337 0.528036 0.01 100 True 1000 100 0.000661941 0.00027933 0.421987 0.01 100 True 1000 1000 0.0014109 0.0006698 0.474732 0.01 100 False 100 100 0.00039546 0.00030159 0.762631 0.01 100 False 100 1000 0.00054909 0.00027276 0.49675 0.01 100 False 1000 100 0.000631344 0.00028231 0.447157 0.01 100 False 1000 1000 0.00141789 0.000657049 0.463398 0.2 50 True 100 100 0.00033689 0.000280155 0.831591 0.2 50 True 100 1000 0.000563495 0.00064159 1.13859 0.2 50 True 1000 100 0.00058635 0.00067611 1.15308 0.2 50 True 1000 1000 0.00153552 0.00486242 3.16662 0.2 50 False 100 100 0.000333545 0.000267555 0.802154 0.2 50 False 100 1000 0.000544 0.00066272 1.21824 0.2 50 False 1000 100 0.00058253 0.000670955 1.15179 0.2 50 False 1000 1000 0.00153017 0.00480928 3.14298 0.2 100 True 100 100 0.00036919 0.000288659 0.781872 0.2 100 True 100 1000 0.00067063 0.00110059 1.64113 0.2 100 True 1000 100 0.00066443 0.00108547 1.63369 0.2 100 True 1000 1000 0.00180991 0.00961579 5.31286 0.2 100 False 100 100 0.00040061 0.000325365 0.812174 0.2 100 False 100 1000 0.00066774 0.00111843 1.67494 0.2 100 False 1000 100 0.000696205 0.00108078 1.55239 0.2 100 False 1000 1000 0.00179788 0.00960569 5.34278 0.5 50 True 100 100 0.00034819 0.00033425 0.959963 0.5 50 True 100 1000 0.00075176 0.00134084 1.78359 0.5 50 True 1000 100 0.000642445 0.00133641 2.08019 0.5 50 True 1000 1000 0.00233791 0.0124282 5.31597 0.5 50 False 100 100 0.000345069 0.000334586 0.96962 0.5 50 False 100 1000 0.00071701 0.00135879 1.89508 0.5 50 False 1000 100 0.000632119 0.00134036 2.12043 0.5 50 False 1000 1000 0.00240216 0.0126202 5.25368 0.5 100 True 100 100 0.000393934 0.00040344 1.02413 0.5 100 True 100 1000 0.000957675 0.002709 2.82873 0.5 100 True 1000 100 0.000756125 0.00242428 3.20619 0.5 100 True 1000 1000 0.00298202 0.0241416 8.09572 0.5 100 False 100 100 0.000395606 0.000433675 1.09623 0.5 100 False 100 1000 0.000963565 0.00248293 2.57682 0.5 100 False 1000 100 0.00079523 0.0024281 3.05333 0.5 100 False 1000 1000 0.00299668 0.0242615 8.09614 0.8 50 True 100 100 0.00036806 0.00040923 1.11186 0.8 50 True 100 1000 0.00091419 0.00207383 2.26848 0.8 50 True 1000 100 0.000684329 0.00196612 2.87307 0.8 50 True 1000 1000 0.00302433 0.0199798 6.60637 0.8 50 False 100 100 0.000368149 0.000615025 1.67058 0.8 50 False 100 1000 0.0008786 0.00205821 2.3426 0.8 50 False 1000 100 0.00067889 0.00195498 2.87967 0.8 50 False 1000 1000 0.00290009 0.0191242 6.59434 0.8 100 True 100 100 0.000452549 0.00063767 1.40906 0.8 100 True 100 1000 0.00126929 0.00391422 3.08378 0.8 100 True 1000 100 0.000919235 0.00386167 4.20096 0.8 100 True 1000 1000 0.00423295 0.0431824 10.2015 0.8 100 False 100 100 0.000428261 0.000626891 1.46381 0.8 100 False 100 1000 0.00120801 0.00395877 3.27711 0.8 100 False 1000 100 0.00080466 0.00385143 4.78641 0.8 100 False 1000 1000 0.00370808 0.0403527 10.8824 **AFTER** Matrix sizes: A sparse [m, k] with % nonzero values between 1% and 80% B dense [k, n] % nnz n gpu m k dt(dense) dt(sparse) dt(sparse)/dt(dense) 0.01 50 True 100 100 0.000312485 0.00020528 0.656927 0.01 50 True 100 1000 0.0004655 0.00020095 0.431686 0.01 50 True 1000 100 0.000567449 0.000203935 0.359389 0.01 50 True 1000 1000 0.00132323 0.00027171 0.205339 0.01 50 False 100 100 0.000319945 0.000197511 0.617328 0.01 50 False 100 1000 0.000466419 0.000210185 0.450635 0.01 50 False 1000 100 0.0005581 0.000199865 0.358117 0.01 50 False 1000 1000 0.00129479 0.000451496 0.348702 0.01 100 True 100 100 0.000364131 0.000196835 0.540561 0.01 100 True 100 1000 0.00053398 0.000206494 0.386708 0.01 100 True 1000 100 0.00062722 0.000203185 0.323946 0.01 100 True 1000 1000 0.00138674 0.000335904 0.242227 0.01 100 False 100 100 0.000361339 0.000195 0.53966 0.01 100 False 100 1000 0.000531831 0.000207155 0.389513 0.01 100 False 1000 100 0.00062245 0.000197015 0.316515 0.01 100 False 1000 1000 0.0014007 0.000328825 0.234757 0.2 50 True 100 100 0.00033185 0.000262895 0.792209 0.2 50 True 100 1000 0.00054391 0.000586189 1.07773 0.2 50 True 1000 100 0.000581805 0.000531535 0.913597 0.2 50 True 1000 1000 0.00153913 0.00142783 0.927687 0.2 50 False 100 100 0.00033572 0.000266831 0.794803 0.2 50 False 100 1000 0.000534315 0.000585151 1.09514 0.2 50 False 1000 100 0.000580961 0.00033344 0.573947 0.2 50 False 1000 1000 0.0015055 0.00143968 0.956284 0.2 100 True 100 100 0.000371666 0.00026337 0.708621 0.2 100 True 100 1000 0.000667235 0.00056811 0.851439 0.2 100 True 1000 100 0.000671356 0.000400575 0.596666 0.2 100 True 1000 1000 0.00178568 0.00250393 1.40222 0.2 100 False 100 100 0.000370425 0.000254935 0.688223 0.2 100 False 100 1000 0.000661175 0.000601134 0.909191 0.2 100 False 1000 100 0.0006944 0.00039817 0.573401 0.2 100 False 1000 1000 0.00176969 0.0024947 1.40968 0.5 50 True 100 100 0.000346885 0.000263295 0.759028 0.5 50 True 100 1000 0.00073113 0.00107669 1.47263 0.5 50 True 1000 100 0.000672774 0.000493085 0.732914 0.5 50 True 1000 1000 0.00260436 0.003335 1.28054 0.5 50 False 100 100 0.00036242 0.000273196 0.753809 0.5 50 False 100 1000 0.000753295 0.00107086 1.42157 0.5 50 False 1000 100 0.00064886 0.000501654 0.773132 0.5 50 False 1000 1000 0.00241105 0.0033146 1.37475 0.5 100 True 100 100 0.000401269 0.00027831 0.693573 0.5 100 True 100 1000 0.00094245 0.00111468 1.18275 0.5 100 True 1000 100 0.00075719 0.00074962 0.990003 0.5 100 True 1000 1000 0.00297528 0.00601445 2.02147 0.5 100 False 100 100 0.000408576 0.00026246 0.642377 0.5 100 False 100 1000 0.00094272 0.00112762 1.19613 0.5 100 False 1000 100 0.000762925 0.00074343 0.974446 0.5 100 False 1000 1000 0.00314936 0.00604122 1.91824 0.8 50 True 100 100 0.00036589 0.000331376 0.905669 0.8 50 True 100 1000 0.00086403 0.00171248 1.98197 0.8 50 True 1000 100 0.00067048 0.000715261 1.06679 0.8 50 True 1000 1000 0.00284684 0.00527865 1.85422 0.8 50 False 100 100 0.000357161 0.000540144 1.51233 0.8 50 False 100 1000 0.000884765 0.00170428 1.92625 0.8 50 False 1000 100 0.000666975 0.000737065 1.10509 0.8 50 False 1000 1000 0.0028149 0.00530442 1.88441 0.8 100 True 100 100 0.00041237 0.00034323 0.832335 0.8 100 True 100 1000 0.00122102 0.00179725 1.47192 0.8 100 True 1000 100 0.000807976 0.00111246 1.37684 0.8 100 True 1000 1000 0.00379081 0.00968211 2.5541 0.8 100 False 100 100 0.000426315 0.000339085 0.795386 0.8 100 False 100 1000 0.00144096 0.00179819 1.2479 0.8 100 False 1000 100 0.000951196 0.0011155 1.17274 0.8 100 False 1000 1000 0.0039524 0.00980128 2.47983 Change: 155142876
| * Fix documentation in supervisor.Gravatar Yutaka Leon2017-05-04
| | | | | | | | Change: 155140112
* | Added identity op and a fix for LRN (#9641)Gravatar Vivek Rane2017-05-04
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | * relu grad and maxpooling grad fixes for perf * Graph layout pass and conversion pass changes This commit makes following changes: - Enables support for ReluGrad and BiasAddGrad - Adds support for detecting depthwise/batchwise pooling - Adds more unit tests for Graph rewrite pass - Improvements to handling control-flow edges - Bug fixes * Defaulting to Eigen when LRN depth_radius!=2 * Fixed mkl_conv_grad_filter.cc for conv_ops_tests.py * Style fix to mkl_matmul and remove unnecessary 'MKL' label on matmul kernel * Style fixes based on clang-format to mkl_conv_* and mkl_matmul * Bug fixes * Adding OP_REQUIRES_OK check in Concat * Making some style changes * Enabled the configuration of MKL settings * relu grad and maxpooling grad fixes for perf * Graph layout pass and conversion pass changes This commit makes following changes: - Enables support for ReluGrad and BiasAddGrad - Adds support for detecting depthwise/batchwise pooling - Adds more unit tests for Graph rewrite pass - Improvements to handling control-flow edges - Bug fixes * Defaulting to Eigen when LRN depth_radius!=2 * Fixed mkl_conv_grad_filter.cc for conv_ops_tests.py * Style fix to mkl_matmul and remove unnecessary 'MKL' label on matmul kernel * Style fixes based on clang-format to mkl_conv_* and mkl_matmul * Bug fixes * Adding OP_REQUIRES_OK check in Concat * Making some style changes * Enabled the configuration of MKL settings * Fixing graph unit tests with Mkl op name change to _Mkl; Fixed missing _ in MklToTf op * Fixed missing libdl.so.2 in BUILD file * Fixes for unit test build failures. * Changes in mkl_conv_grad_filter_ops.cc for Google code style * Fixes to remove dead code * removed the dead code and added a TODO for mkl implementation to handle this case in the future * Enabling MklIdentityOp * Calling MKL for all values of depth radius in LRN * Fixed buildifier sanity check error * Adding support for google's CI automation * Updated link to new MKL version * Enabling MklIdentityOp * Calling MKL for all values of depth radius in LRN * Fix for missing locate binary * Fix for missing locate command in CI * Adding updatedb to populate the database after installing mlocate * Fixed buildifier issue * setting tf_need_mkl=0 in libtf files * Added third_party/mkl/* to .gitignore * Added third_party/eigen3/mkl_include to .gitignore * In configured, set MKL-enabling options only for Linux. * Enabling MklIdentityOp * Calling MKL for all values of depth radius in LRN * Making style fix in LRN * Fixed Indentation
| * Fix mac build.Gravatar Yutaka Leon2017-05-04
| | | | | | | | Change: 155140054
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-29 11:10:11 +0000