Commit d0fbac3
committed
Merge branch 'release-v0.100.0'
============================== Release Notes: v0.100 ==============================
Support for new network structures:
- 3D molecular generation models for Metal Organic Frameworks from the CoRE MOF Database.
- 3D CosmoFlow Model
- DenseNet
- ATOM LSTM model
- RAS state classifier
- node2vec
- Transformer and other attention-based models
- ExaGAN (formerly CosmoGAN)
- MaCC ICF surrogate model
Applications:
- Created a directory of example applications, deprecating the "model zoo" directory
Support for new layers:
- Embedding layer
- Distributed embedding layer
- Channel-wise scale/bias layer
- Entry-wise scale/bias layer
- Gated-Recurrent Units (GRU)
- Entry-wise batchnorm
- Argmax, Argmin, and one-hot layers
- Layer norm
- Deconvolution layer (transposed convolution)
- Layers for channel-wise operations (channel-wise fully-connected, channel-wise softmax, channel-wise scale/bias, instance norm)
- Matrix multiply layer
Python front-end:
- Can now configure contrib launcher with environment variables
- Added NERSC compute center
- Per-layer specification of compute device (CPU or GPU)
- Option to write custom batch scripts with Python front-end
Performance optimizations:
- Parallelized Python data reader with "multiprocessing" module
- Fuse batchnorm stats allreduces in FP/BP.
- Tuned concatenate and slice layer
- Dynamically allocate and free memory for layer error signals (halves LBANN's memory footprint)
Model portability & usability:
- Bamboo tests for individual layers
Internal features:
- Added support for DistConv features (distributed, generalized,
parallel convolution)
- Added support for NVSHMEM 1.0 API (used in distributed embedding
layer and DistConv halo exchange)
- Support for multiple data types per model (per-layer)
- Support for per-layer mixed-precision weight training and inference,
includes per-weight object and objective function mixed-precision.
- Improved how and when the RNGs are initialized
- Callback to dump images to TensorBoard
- Callback to save model weights (useful to export to PyTorch)
- Callback to save top K models (LTFB)
- Improved run-to-run reproducibility by initializing weights in alphabetical order
- Moved models from model_zoo directory to applications directory
- Cleanup and refactoring of callbacks and layer instantiation
- Grouped batchnorm statistics
- Callback to print model description
- Refactored trainer and training-state out of the model class
- Support for transposing data in matrix multiply layers
- Added DiHydrogen tensor and DistConv library
- Added parallel strategy to layer class to support DistConv
- LBANN inference mode supports loading models from multiple directories
- Cleanup of checkpoint and restart logic
I/O & data readers:
- Added in-memory data store that caches samples in CPU memory. It can be loaded
during the first epoch or preloaded
- Added new "transform" data preprocessing ingestion pipeline
- Added sample list format for specifying data sets
- Introduced data coordinator that manages data readers and extracts them from
the input layers
- Data store is able to checkpoint / spill it's contents to local disk
- Data reader for SMILE strings
Build system:
- Hydrogen 1.3.4
- Aluminum 0.3.3
- Improved documentation on read the docs (RTD)
- Robust support for using Spack as a build system around CMake
- Identified compute centers for specifying build and run dependencies
- Added Catch2-based tests
Bug fixes:
- Fixed path resolution for dump weights, save model, and checkpoint callbacks
- Added mutexes for preloading the data store
- Fixed the LTFB exchange to include all ADAM optimizer state
- Fixed the mapping of I/O RNGs to I/O processing threads to ensure
consistent and correct multi-threaded performance
Retired features:
- moving MNIST data reader is replaced by python data reader
- ASCII data reader is deprecatedFile tree
1,308 files changed
+106623
-78559
lines changed- applications
- ATOM
- data
- utils
- CANDLE/pilot2
- data
- tools
- MOF
- data
- test
- graph
- data
- test
- utils
- nlp
- data
- experiments
- rnn
- transformer
- utils
- physics
- ICF
- cosmology/ExaGAN
- data
- selfsupervised
- patch_generator
- vision
- data
- cifar10
- imagenet
- mnist
- summarizing_images
- bamboo
- common_python
- data
- imagenet
- mnist
- compiler_tests
- builds
- error
- output
- integration_tests
- error
- expected_values
- catalyst
- clang4
- gcc7
- pascal/gcc7
- experiments
- output
- unit_tests
- error
- experiments
- output
- prototext
- cmake
- configure_files
- modules
- docs
- external/TBinf
- include/lbann
- callbacks
- data_coordinator
- data_readers
- patchworks
- data_store
- execution_contexts
- io
- data_buffers
- layers
- activations
- image
- io
- input
- learning
- loss
- math
- misc
- regularizers
- transform
- macros
- metrics
- models
- objective_functions
- weight_regularization
- optimizers
- proto
- trainers
- training_algorithms
- transforms
- vision
- utils
- impl
- threads
- weights
- model_zoo
- cosmoflow
- data_readers
- jag_utils
- python
- models
- alexnet
- autoencoder_candle_pilot1
- autoencoder_cifar10
- autoencoder_imagenet
- autoencoder_mnist
- candle/pilot1
- cosmoflow
- gan
- jags/cycle_gan
- mnist
- jag
- ae_cycle_gan
- 3models
- cycle_gan
- gan
- cyclic
- vanilla
- wae_cycle_gan
- lenet_mnist
- molecular_autoencoder_candle_pilot2
- python/keras
- resnet50
- siamese
- finetune-cub
- siamese_alexnet
- triplet
- simple_mnist
- vram
- tests
- data_reader_tests
- layer_tests
- vision
- python
- lbann
- contrib
- lc
- models
- nersc
- core
- launcher
- models
- modules
- util
- scripts
- spack_recipes
- spack_environments
- llnl_lc
- nersc
- osx
- users/llnl_lc
- ppc64le_cuda
- x86_64_cuda
- src
- callbacks
- data_coordinator
- data_readers
- patchworks
- data_store
- execution_contexts
- io
- data_buffers
- layers
- activations
- image
- io/input
- learning
- loss
- math
- misc
- regularizers
- transform
- metrics
- models
- objective_functions
- weight_regularization
- optimizers
- proto
- factories
- unit_test
- trainers
- training_algorithms
- transforms
- unit_test
- vision
- unit_test
- utils
- threads
- unit_test
- stubs
- weights
- unit_test
- superbuild
- aluminum
- catch2
- cereal
- clara
- cnpy
- conduit
- cub
- dihydrogen
- hdf5
- hydrogen
- jpeg-turbo
- lbann
- openblas
- opencv
- protobuf
- tests
- test_img_pipeline
- test_patchworks
- test_stack_tracing
- tools/siamese_patch_list
- unit_test
- example
- utilities
- unit_test
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