TypeError: google.visualization is undefined #9

AltenLi · 2015-03-20T07:55:41Z

while I'm using it offline, the graph of training can't be shown...
Could you pack the google package into the source?
Thanks!

lukeyeager · 2015-03-20T16:29:56Z

I can't actually. https://developers.google.com/chart/interactive/faq#offline

This is what I'm working on today, in fact - switching to use a different chart library which will allow me to download it and distribute it with DIGITS. I'm looking at using either Chart.js or c3.js.

AltenLi · 2015-03-21T07:08:17Z

Great thanks for you!
Looking for your good news

* initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * a typo made through * edited the gan examples to be compatable with TF 1.2 * lint * added to test optimizers other than sgd * pointed the celeba dataset to its main page

* Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * Add gradient hook * Add memn2n model * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Update memn2n with gradient hooks * Remove the selenium walkthrough * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Update GAN plug-in to create CelebA dataset * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Add animation task to GAN plugins * Fix shellcheck-related bug in PPA upload script * Add view task to see image attributes * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Add comments to GAN models * Update README * Fix GAN features script * Fix a bug introduced when fixing shellcheck lint * GAN app * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * Adding disclaimer * Display the filename of the image that caused the exception while loading. * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * Fix softmax visualization by scaling to image range * added the official store image and updated the documentation * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * reodered the installation order to see if it builds due to TF using numpy 1.13 now * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * changes to example documentation * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Script changes for tensorflow (#1) * Basic Tensorflow Support Added some initial tf tools Implemented UI Fixes for tensorflow 0.10 Removed tf-slim as its not part of the 0.10 master Added the lmdb reader with a tf.cond that needs replacement Implemented train and val seperation with a templating Fixed issue with dequeueing both runners by pulling both graphs Implemented training and validation rythm Added support for both png and jpg and added 16 bit support Implemented mean subtraction - but needs rework to load as constant Added an optimized implementation of mean subtraction Further optimized the mean loading by using a shared constant Wrapped the data loader in a factory to easily support more data types Implemented cropping Implemented floating point support. Implemented seperate LMDB database. Implemented regression support. Added some brief nosetests. Need to invoke accuracy only on classification though. Implemented variable restoration. Needs thorough testing Implemented inferencing, not entirely polished Moved some code into functions, started on modularization a bit Implemented digits custom helper functions Implemented custom printing ops Implemented autoencoder total rewrite of summaries Implemented output to console from scalar summaries Fixes for summary outputs: only simple scalar values are parsed to console Implemented binary segmentation and necessary fixes Some updates on binary seg Implemented all possible optimizers and started work on learning rate shaper Started work on the lr policies Fixes for learning_rates, implemented optimizers, tested variable summary output to UI Implemented and tested all learning rates and optimizers Introduces new model definition and improvements in loss handling and graph layout Major refactoring of main code. Implemented new model description. Implemented and tested inferencing. Implemented and tested weight/snapshot loading. All-round minor updates and fixes Fixes in summary cumulator and implemented an RNN model Fixes for mean subtraction in tf and tf-ui, implemented data order selection in image-view extension Implemented support for mean file of format: png, jpg, binaryproto - the latter being the fault that DIGITS will provide. Added support for runtime statistics and some allround fixes Added static tensorboard style network visualization for tensorflow. Added output of traces (no vis yet). Added a loader while waiting for network vis. Minor syntax cleanups. Implemented alexnet standard network Pulled in updates for travis build and added tensorflow install Added two more files for Mr Travis Implemented tensorflow configuration Added tf config to doc Fixes for ubuntu deployment of tf. Moved tf tools Fixes for tf ubuntu Fixes for tf ubuntu Some fixes and updates for TF in Travis Fix in network viz test Implemented default sinlge-gpu support and some nosetests Fixes for inference Added siamese network, bugfixes, minor features, some utility tf functions Added siamese network and example png Better error-ui format for network viz Added an alternative simpler siamese network that doesnt need a seperate db, minor error update Preliminary version of hdf5 implemented Implemented fine-tuning by renaming variables Implemented visualisation of variables and the activations of the Ops they belong to. Fix in inf vis naming Fixes in visualualisation shapes and naming Implemented softmax upon classification Implemented all nosetests for tf classification, and many allround bugfixes Implemented generic nosetests - some need work Fix for travis to find python exe Implemented a better file format deducer, and implemented a bare minimal TFRecord-reader Added top_n accuracy shortcut Implemented on-line data augmentation for TF, 5 types. Some minor bugfixes. Need to do something with image whitening though during validation and inf.. Added tensorflow data augmentation test Minor fixes and improvements from linter Implemented minimal and bare multigpu and fixes to get it running for greg Preliminary version of tfrecord writer for classification Some changes to optimize dataloading for tfr More fixes for tfrecrods Fix generic data loading Minor breaking changes but updates in namescoping Implemented new model structure. Improvements to multi-gpu handling. Updates to namespaces. Implemented accounting for regularization. Many allround updates Implemented proper visualisation for gpu devices Minor updates and converted alexnet and vgg16 to new format Fix in tfrecord shape WIP on timeline traces Finalized support for tensorflow timeline traces Fixed alexnet for tf Fix merge errors Minify tf-graph-basic.build.js * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add gradient hook * Add memn2n model * Update memn2n with gradient hooks * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Update GAN plug-in to create CelebA dataset * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Add animation task to GAN plugins * Add view task to see image attributes * Add comments to GAN models * Update README * Fix GAN features script * GAN app * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Adding disclaimer * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Tf documentation (#4) * Worked on Tensorflow docs * milestone * changed some typos * added into the documentation for how to specify which weights to train * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * changed docs for freezing variables * added more to the documentation * capitalized some letters * fixed api problem for multi gpus * fixes to docs WRT to PR * changes WRT to PR comments * added the cudnn versioning problem with tf * added images for tensorflow image * updated dl for tensorflow to 1.2 * updated pip command * Greg gan work (#3) GAN support for DIGITS * Tensorflow Work * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * Add gradient hook * Add memn2n model * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Update memn2n with gradient hooks * Remove the selenium walkthrough * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Update GAN plug-in to create CelebA dataset * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Add animation task to GAN plugins * Fix shellcheck-related bug in PPA upload script * Add view task to see image attributes * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Add comments to GAN models * Update README * Fix GAN features script * Fix a bug introduced when fixing shellcheck lint * GAN app * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * Adding disclaimer * Display the filename of the image that caused the exception while loading. * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * Fix softmax visualization by scaling to image range * added the official store image and updated the documentation * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * reodered the installation order to see if it builds due to TF using numpy 1.13 now * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * changes to example documentation * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Tf documentation (#4) * Worked on Tensorflow docs * milestone * changed some typos * added into the documentation for how to specify which weights to train * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * changed docs for freezing variables * added more to the documentation * capitalized some letters * fixed api problem for multi gpus * fixes to docs WRT to PR * changes WRT to PR comments * added the cudnn versioning problem with tf * added images for tensorflow image * updated dl for tensorflow to 1.2 * updated pip command fixed linting removed debug lines in scripts * cleaning up residues from the travis script * fixed a broken link * cleaned up more residue * somehow openblas made it through merge * lint fix * updated documentation for using tensorboard * added warnings for using tensorboard not on chrome * changed to using bootbox.alert() * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * updated googlenet with the best working model and add a note about the auxillary branches * lint * initial prototype fix * lint * removed debug prints * lint * Tf gans review (NVIDIA#9) * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * a typo made through * edited the gan examples to be compatable with TF 1.2 * lint * added to test optimizers other than sgd * pointed the celeba dataset to its main page * removed a tf-events file * Googlenet implementation initial commit for googlenet implementation mile stone on inception module finished googlenet inference finished googlenet and refactored a bit of other networks commiting to test this at the office fixed googlenet to get it working somehow a bad version went through switching to documentation removed softmax before loss in googlenet initial prototype fix updated gitignore updated googlenet with the best working model and add a note about the auxillary branches * Updated tensorboard documentation updated documentation for using tensorboard added warnings for using tensorboard not on chrome changed to using bootbox.alert() * Fixed linting lint initial prototype fix lint removed debug prints lint * Tf gans review (NVIDIA#9) * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * a typo made through * edited the gan examples to be compatable with TF 1.2 * lint * added to test optimizers other than sgd * pointed the celeba dataset to its main page * merged rebase changes from development repo * removing ADAM tests for caffe and torch due to incompatability * readded adam tests but commented out torch due to tuning issues * set version to 6.0

* Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * Add gradient hook * Add memn2n model * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Update memn2n with gradient hooks * Remove the selenium walkthrough * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Update GAN plug-in to create CelebA dataset * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Add animation task to GAN plugins * Fix shellcheck-related bug in PPA upload script * Add view task to see image attributes * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Add comments to GAN models * Update README * Fix GAN features script * Fix a bug introduced when fixing shellcheck lint * GAN app * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * Adding disclaimer * Display the filename of the image that caused the exception while loading. * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * Fix softmax visualization by scaling to image range * added the official store image and updated the documentation * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * reodered the installation order to see if it builds due to TF using numpy 1.13 now * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * changes to example documentation * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Script changes for tensorflow (#1) * Basic Tensorflow Support Added some initial tf tools Implemented UI Fixes for tensorflow 0.10 Removed tf-slim as its not part of the 0.10 master Added the lmdb reader with a tf.cond that needs replacement Implemented train and val seperation with a templating Fixed issue with dequeueing both runners by pulling both graphs Implemented training and validation rythm Added support for both png and jpg and added 16 bit support Implemented mean subtraction - but needs rework to load as constant Added an optimized implementation of mean subtraction Further optimized the mean loading by using a shared constant Wrapped the data loader in a factory to easily support more data types Implemented cropping Implemented floating point support. Implemented seperate LMDB database. Implemented regression support. Added some brief nosetests. Need to invoke accuracy only on classification though. Implemented variable restoration. Needs thorough testing Implemented inferencing, not entirely polished Moved some code into functions, started on modularization a bit Implemented digits custom helper functions Implemented custom printing ops Implemented autoencoder total rewrite of summaries Implemented output to console from scalar summaries Fixes for summary outputs: only simple scalar values are parsed to console Implemented binary segmentation and necessary fixes Some updates on binary seg Implemented all possible optimizers and started work on learning rate shaper Started work on the lr policies Fixes for learning_rates, implemented optimizers, tested variable summary output to UI Implemented and tested all learning rates and optimizers Introduces new model definition and improvements in loss handling and graph layout Major refactoring of main code. Implemented new model description. Implemented and tested inferencing. Implemented and tested weight/snapshot loading. All-round minor updates and fixes Fixes in summary cumulator and implemented an RNN model Fixes for mean subtraction in tf and tf-ui, implemented data order selection in image-view extension Implemented support for mean file of format: png, jpg, binaryproto - the latter being the fault that DIGITS will provide. Added support for runtime statistics and some allround fixes Added static tensorboard style network visualization for tensorflow. Added output of traces (no vis yet). Added a loader while waiting for network vis. Minor syntax cleanups. Implemented alexnet standard network Pulled in updates for travis build and added tensorflow install Added two more files for Mr Travis Implemented tensorflow configuration Added tf config to doc Fixes for ubuntu deployment of tf. Moved tf tools Fixes for tf ubuntu Fixes for tf ubuntu Some fixes and updates for TF in Travis Fix in network viz test Implemented default sinlge-gpu support and some nosetests Fixes for inference Added siamese network, bugfixes, minor features, some utility tf functions Added siamese network and example png Better error-ui format for network viz Added an alternative simpler siamese network that doesnt need a seperate db, minor error update Preliminary version of hdf5 implemented Implemented fine-tuning by renaming variables Implemented visualisation of variables and the activations of the Ops they belong to. Fix in inf vis naming Fixes in visualualisation shapes and naming Implemented softmax upon classification Implemented all nosetests for tf classification, and many allround bugfixes Implemented generic nosetests - some need work Fix for travis to find python exe Implemented a better file format deducer, and implemented a bare minimal TFRecord-reader Added top_n accuracy shortcut Implemented on-line data augmentation for TF, 5 types. Some minor bugfixes. Need to do something with image whitening though during validation and inf.. Added tensorflow data augmentation test Minor fixes and improvements from linter Implemented minimal and bare multigpu and fixes to get it running for greg Preliminary version of tfrecord writer for classification Some changes to optimize dataloading for tfr More fixes for tfrecrods Fix generic data loading Minor breaking changes but updates in namescoping Implemented new model structure. Improvements to multi-gpu handling. Updates to namespaces. Implemented accounting for regularization. Many allround updates Implemented proper visualisation for gpu devices Minor updates and converted alexnet and vgg16 to new format Fix in tfrecord shape WIP on timeline traces Finalized support for tensorflow timeline traces Fixed alexnet for tf Fix merge errors Minify tf-graph-basic.build.js * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add gradient hook * Add memn2n model * Update memn2n with gradient hooks * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Update GAN plug-in to create CelebA dataset * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Add animation task to GAN plugins * Add view task to see image attributes * Add comments to GAN models * Update README * Fix GAN features script * GAN app * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Adding disclaimer * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Tf documentation (#4) * Worked on Tensorflow docs * milestone * changed some typos * added into the documentation for how to specify which weights to train * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * changed docs for freezing variables * added more to the documentation * capitalized some letters * fixed api problem for multi gpus * fixes to docs WRT to PR * changes WRT to PR comments * added the cudnn versioning problem with tf * added images for tensorflow image * updated dl for tensorflow to 1.2 * updated pip command * Greg gan work (#3) GAN support for DIGITS * Tensorflow Work * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * bAbI data plug-in Add utils Add inference form to bAbI dataset Allow inference without answer Allow unknown words in BaBI data plug-in Fix bAbI plugin Lint errors * Tensorflow integration updates Use TFRecords for TF inference TF: Don't rescale inputs Fix some TF classification tests Remove unnecessary print Fix TF imports when uninstalled Fix mean image scale Fix generic model tests Fix Torch single image inference Fix inference TMP TF Lint Revert changes in digits-lint script Lint: ignore tensorflow standard examples More Lint fixes * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * Add gradient hook * Add memn2n model * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Update memn2n with gradient hooks * Remove the selenium walkthrough * GAN example * Make batch size variable * Training/inference paths * Small update to TF 0.12 * Snapshot names, float inference, restore all vars * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Do not restore global_step or optimizer variables * Add TB link * Update GAN network * Dynamically select inference form * TF inference: convert images to float * Update GAN z-gen network * Small Update model view layout * Add GAN plug-ins * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Update GAN plug-in to create CelebA dataset * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Add ability to show input in ImageOutput extension * Add all data to raw data view extension * Add model for CelebA dataset * Update GAN data plug-in * Update all losses in one session * Remove conversion to .png in GAN data plug-in * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * TF Slim Lenet example Divide input by 255 * Update GAN data plug-in * Fix TF model snapshot * Reduce scheduler delays to speed up inference * Update GAN plugins * Fix TF tests * Add API to LmdbReader (used by gan_features.py) * Save animated gif * Add GAN walk-through * Update GAN walkthrough with embeddings video * Fix GAN view for list encoding * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Add animation task to GAN plugins * Fix shellcheck-related bug in PPA upload script * Add view task to see image attributes * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Add comments to GAN models * Update README * Fix GAN features script * Fix a bug introduced when fixing shellcheck lint * GAN app * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Fix DIGITS inference * Adjust GAN window size automatically * Add attributes to GAN app * Move gandisplay.py * Remove wxpython 3.0 selection * Fix call to model * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * Adding disclaimer * Display the filename of the image that caused the exception while loading. * Ported DIGITS to using tensorflow 1.1.0. * Ported DIGITS to using tensorflow 1.1.0. Got master branch working * Fix softmax visualization by scaling to image range * added the official store image and updated the documentation * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * updated gitignore * first cherrypick for installation scripts * Tf install experimental (#2) * Fix visualization when palette is None (NVIDIA#1177) The palette may be `None`when working with grayscale labels. Fix NVIDIA#1147 * Bugfix for customizing previous models (NVIDIA#1202) * [Packaging] Disable tests (NVIDIA#1227) * [Tests] Skip if extension not installed (NVIDIA#1263) * [Docs] Fix spelling errors in comments * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Docs] Add note about torch pkg and cusparse (NVIDIA#1303) * [Caffe] Fix batch accumulation bug (NVIDIA#1307) * Use official NVIDIA model store by default (NVIDIA#1308) * Mark v5.0.0 * [Packaging] Pull latest docker image before build * Add .pgm to list of supported image file formats * Restrict usage of cmap to labels DB in generic dataset exploration fix NVIDIA#1322 * Update Object Detection example doc (NVIDIA#1323) * Update Object Detection example doc (NVIDIA#1323) * [TravisCI] Cache local OpenBLAS build This fixes a Torch bug we've been having on Travis for a while now. We had only been building OpenBLAS from source when there was no cached torch build present on the build machine. That meant you could get a cached build of Torch which was built against one version of OpenBLAS, but the system actually installed an older version. This led to memory corruption and segmentation faults. * [Tests] Skip if extension not installed (part 2) (NVIDIA#1337) * [TravisCI] Install all plugins by default Also test no plugins * [Tests] Skip if extension not installed (NVIDIA#1337) * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * [Docs] Update model store documentation (NVIDIA#1346) TODO: add a screenshot of the official model store once approved * Add steps to specify the Python layer file (NVIDIA#1347) * Add steps to specify the Python layer file (NVIDIA#1347) * [Docs] Install minimal boost libs for caffe * Remove the selenium walkthrough * Update copyright year for 2017 * Add a few missing copyright notices * Fix Siamese example Broadcast -1 into all elements that equal 0 in original label. * Fix Siamese example (NVIDIA#1405) Broadcast -1 into all elements that equal 0 in original label. * [Packaging] Make nginx site easier to customize * Fix documentation typo. train.txt and test.txt was swapped and shown in the wrong folders for mnist and cifar10 data sets. * Document a cuDNN workaround for text example (NVIDIA#1422) * Document a cuDNN workaround for text example (NVIDIA#1422) * Correct shebang for prepare_pascal_voc_data.sh (NVIDIA#1450) * [Docs] Document workaround for torch+hdf5 error * Fix typo in ModelStore.md * Fix typo in medical-imaging/README.md * Fix bash lint with shellcheck * Fix bugs when visiting nested image folder * Fix shellcheck-related bug in PPA upload script * Copy labels.txt inside the dataset Move import to the top * Fix Distribution Graph Move backwards-compatibility to setstate * Fix typo in Sunnybrook plug-in * Fix a bug introduced when fixing shellcheck lint * Fix another shellcheck-related bug * Fix table formatting in README.md Fix table formatting * Clamp distance values from segementation boundaries before begin converted to uint8. That was causing banding in the image because of wrapping at V % 256 * lint * [Docs] 5.0 debs and Ubuntu 16.04 support * WIP lint fix * Linted most of what I can lint prior to asking for context * updated the model store urls in the readme * added debugs in build scripts to understand the point of failure * added travis wait to install openblas * removed tensorflow to the build process to see if affects openblas * removed suppressing log contents * added set -x * fixed control * re-enabling tensorflow to see if travis builds * updated the version of numpy to ensure a stable build for travis wrt to open issue 8653 on numpy github * forcing numpy to v 1.8.1 * added the official store image and updated the documentation (NVIDIA#1650) * [TravisCI] Add `git fetch --unshallow` for DIST Useful for TravisCI builds in forks. * Got travis script to work for tensorflow installation * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * reodered the installation order to see if it builds due to TF using numpy 1.13 now * Cleaning installation to work with Numpy 1.3 upgrade removed the open blas stuff that somehow made it into here embarassing merge residue force install specific numpy version because 1.13 was being installed asdf trying changing the tensorflow install reodered the installation order to see if it builds due to TF using numpy 1.13 now * Tf example (#3) * inital work on autoencoder TF example * Moved the example files to its proper location * atempting to get autoencoder to work * autoencoder work * validated tensorflow autoencoder example * updated gitignore * disabled comments in the segmentation-model.lua script to prevent crashing * commiting the changes made to binary segmentation tf * adding work to do something else * I am seriously wayy too tired to write this commit message, it's just random bits of stuff * got binary seg and siamese working * started to work on the regression network * milestone * got regression for TF working * Got fine tuning to work in TF * changed the code to the format that is wanted by tim and greg * Finished all the work for examples inital work on autoencoder TF example Moved the example files to its proper location atempting to get autoencoder to work autoencoder work validated tensorflow autoencoder example updated gitignore disabled comments in the segmentation-model.lua script to prevent crashing commiting the changes made to binary segmentation tf adding work to do something else I am seriously wayy too tired to write this commit message, it's just random bits of stuff got binary seg and siamese working rebase rebase started to work on the regression network milestone got regression for TF working Got fine tuning to work in TF changed the code to the format that is wanted by tim and greg got fine tuning working * Some small fixes * changes WRT PR trying renaming the weights tested renaming variables * fixed api problem for multi gpus * changes to example documentation * git removed installing tests * updated most of linting * Removed unused block of code as per suggestion by Greg * Removing spaces... * Tf documentation (#4) * Worked on Tensorflow docs * milestone * changed some typos * added into the documentation for how to specify which weights to train * removed the open blas stuff that somehow made it into here * embarassing merge residue * force install specific numpy version because 1.13 was being installed * asdf * trying changing the tensorflow install * changed docs for freezing variables * added more to the documentation * capitalized some letters * fixed api problem for multi gpus * fixes to docs WRT to PR * changes WRT to PR comments * added the cudnn versioning problem with tf * added images for tensorflow image * updated dl for tensorflow to 1.2 * updated pip command fixed linting removed debug lines in scripts * cleaning up residues from the travis script * fixed a broken link * cleaned up more residue * somehow openblas made it through merge * lint fix * updated documentation for using tensorboard * added warnings for using tensorboard not on chrome * changed to using bootbox.alert() * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * updated googlenet with the best working model and add a note about the auxillary branches * lint * initial prototype fix * lint * removed debug prints * lint * Tf gans review (NVIDIA#9) * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * a typo made through * edited the gan examples to be compatable with TF 1.2 * lint * added to test optimizers other than sgd * pointed the celeba dataset to its main page * removed a tf-events file * Googlenet implementation initial commit for googlenet implementation mile stone on inception module finished googlenet inference finished googlenet and refactored a bit of other networks commiting to test this at the office fixed googlenet to get it working somehow a bad version went through switching to documentation removed softmax before loss in googlenet initial prototype fix updated gitignore updated googlenet with the best working model and add a note about the auxillary branches * Updated tensorboard documentation updated documentation for using tensorboard added warnings for using tensorboard not on chrome changed to using bootbox.alert() * Fixed linting lint initial prototype fix lint removed debug prints lint * Tf gans review (NVIDIA#9) * initial commit for googlenet implementation * mile stone on inception module * finished googlenet inference * finished googlenet and refactored a bit of other networks * commiting to test this at the office * fixed googlenet to get it working * somehow a bad version went through * switching to documentation * removed softmax before loss in googlenet * initial prototype fix * updated gitignore * a typo made through * edited the gan examples to be compatable with TF 1.2 * lint * added to test optimizers other than sgd * pointed the celeba dataset to its main page * merged rebase changes from development repo * removing ADAM tests for caffe and torch due to incompatability * readded adam tests but commented out torch due to tuning issues * set version to 6.0 fixed linting and version number reverting back to 5.1-dev for version

AltenLi closed this as completed Mar 21, 2015

This was referenced Mar 27, 2015

Loss graph did not show #31

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Use a different js graphing library #34

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lukeyeager mentioned this issue Apr 8, 2015

[ERROR] ValueError: math domain error #50

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Alqazzaz mentioned this issue Apr 30, 2017

segmentation PNG labels #1605

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TypeError: google.visualization is undefined #9

TypeError: google.visualization is undefined #9

AltenLi commented Mar 20, 2015

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AltenLi commented Mar 21, 2015

TypeError: google.visualization is undefined #9

TypeError: google.visualization is undefined #9

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AltenLi commented Mar 20, 2015

lukeyeager commented Mar 20, 2015

AltenLi commented Mar 21, 2015