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* 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
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