* create branch for debug
* move unit test
* more changes
* move relu to activations_grad*
* Fix ReluGrad Domain and opset version
* added unit test, CudaKernelTest.Relu_basic doesn't work yet
* remove CudaKernelTest.Relu_basic
* PR comment
* add unit test ReluGradTest_Basic
Co-authored-by: Jingyan Wang <jingywa@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* cancel night build on pyop
* add rewriter to rewrite cpu provider
* skip BuildKernelCreateInfo<void>
* refactor variable name and comment
* include ops from csv file
* process multiple eps
* add default function to cuda provider
* rename function and add license header
* fix import
* add doc
* fix typo
* deal with empty kernel entry in cuda
* rename the rewriter file
* add comment into provider file
* add comment and rename function
* log warnings
* refactor extracting logic
* add entry for script to run solo
* add better example
* avoid onnx importing
* fix flake8 alerts
* minor fixes to better comments and doc
* add entries for all domains
* add void entry into contrib providers
* format cuda_contrib_kernels.cc
* format cpu_contrib_kernels.cc
* add all providers
* add default entry to all providers
* include op_kernel header
* cancelling change in providers beyond cpu/cuda
* rename file and switch file format to domain;opset;op1,op2...
* update doc
* restore non-regular ending grammar in cuda_contrib_kernels.cc
* add ort_root as input argument of script
* enable test in ci
* update doc
* update doc
* revert change on linux gnu ci
* switch to set to host ops
* simplify trimming logic
* add domain map to track current model
* allow ort_root to take relative path
* correct some errors in the flatbuffers schema, move flatbuffers submodule to cmake/external
* update the ort flatbuffers schema to use less namespace
* minor update
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
* Initial set of changes to start disabling code in the minimal build. Breaking changes into multiple PRs so they're more easily reviewed. Focus on InferenceSession, Model and Graph here. SessionState will be next.
Needs to be integrated with de/serialization code before being testable so changes are all off by default.
Changes are limited to
- #ifdef'ing out code
- moving some things around so there are fewer #ifdef statements
- moving definition of some one-line methods into the header so we don't need to #ifdef out in a .cc as well
- exclude some things in the cmake setup
* Update session state and a few other places.
The core code builds if ORT_MINIMAL_BUILD is specified.
* update onnx to latest master
* implement per-channel for quantizelinear and dequantizelinear
* refine the unit test
* exclude sequence_insert tests
* refine onnx cmake
* add failure tests to broken_tests
* move qdq common code to a seperate function
* refine code
* Add Node::SinceVersion() so that the value is known when loading a graph from the ORT format (OpSchema is not available).
* Fix build warning from returning 'const int'
* add flatbuffers submodule
* test version of flat buffer schema
* test version of flat buffer schema
* minor updates
* add serialization of the value info, group defs in different namespace
* update comments
* update cgmanifest.json
* update namespace, changed typeinfovalue to use union, added root_type and file_identifier
* add new container type, add max_node_index to graph
* add serializing session state
* addressed review comments
* minor updates
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
The string concatenation of the cuda flags makes compiling impossible due to the missing space (Error: " nvcc fatal: redefinition of keyword 'code' ") .
* Removed building ngraph from source
* Disabled some tests temporarily
* Enabled softmax for all dims
* Added onnx importer to link libraries
* int64 changes
* fixed
* temp
* slice update start and end need to be initializer
* Disabled GatherND, ScatterND, ReverseSequence operators
* Added supported ops instead of unsupported ops
* Set precision only for CPU
* Removed some unecessary conditions
* Fixed segfault in slice
* Softmax restriction removed
* changes
* Setting precision for all plugins
* Changes added to include precision
and supported ops for gpu and vpu
* branch op support
* checking for disabled python test failure
* mapped input names and tensors directly rather than copying which was leading to mismatch
* last index is not supported
mkldnn does not support pow between integers
* included the code changes
* Rename inner-scoped variable to avoid MSVC warning
* applied changed to vadm as well and removed the utility function
getinputtensors() completely
* OpenVINO multi version support: CMake changes
* OpenVINO multi version support: C++ support
* removed commented code
* Remove redundant code lines
* Revert "Rename inner-scoped variable to avoid MSVC warning"
This reverts commit 2f650493162675bc6fb70730de9656ec400be332.
Merged separately in master.
* vadm changes disabled reduction op test
* putting test_gather_negative_indices in unsupported list for now
* Update MCR Dockerfile with 2020.4
Installs OpenVINO 2020.4 from deb packages via APT tool.
* Update build docs with 2020.4 info
* Update dockerfile with OV 2020.4 info
Instructions for building OpenVINO based docker image no longer require
downloading installer package as it is installed by the dockerfile
using OpenVINO 2020.4 APT package for Ubuntu 18.04
* Added constant folding bypass logic
* Added cout statements for ci
* Added NDEBUG flag for debug symbols
* Update Ops info in docs
* fixes multiple unit tests
* mathoptest.ceil disabled for gpu and myriad
* activation test temp disabled
* Fix models for CPU
* Fixed a syntax error
* local cmmit
* fixing unit tests for myriad
* Fixed Variadic Split, Topk issues
* fix_model commit
* Fix models in myriad
* Added ifdefs for OpenVINO 2020.4
* temp
* made some changes to not operator
* Added unused parameter
* relu enabled
* Fixed bug in Conv output
* Consolidated GPU failing tests into one category
* Made it compatible to InternalCI 2020.4
* Made changes for ngraph
* Disabled test for mask,fastercnn,tinyyolov3
* Removed proxy for ci
* run_dockerbuild.sh restored to same version
* run_dockerbuild.sh restored to same version
* run_dockerbuild.sh restored to same version
* Updated documentation for 2020.4
* Removed FP32 to FP16 transformation for GPU
* Disabled Coreml-FNS-Candy model test
* Added FP16 transformations
Co-authored-by: sfatimar <sahar.fatima@intel.com>
Co-authored-by: Manohar Karlapalem <manohar.karlapalem@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
Co-authored-by: sfatimar <64512376+sfatimar@users.noreply.github.com>
Co-authored-by: intel <you@example.com>
Co-authored-by: gundaarx <aravindx.gunda@intel.com>
* Refactor SessionState to support coming de/serialization changes
- move more parts into SessionState to simplify usage
- do the kernel lookup once instead of multiple times from different places
- rename finalize_session_state.* to session_state_utils.* as the finalization logic is now inside SessionState
* Fix some build issues
* Move subgraph session state creation into SessionState. It's not needed by GraphPartitioner any more so we can delay the creation until later. Fixes issue where EP may have removed the subgraph during partitioning when taking a control flow node, and SessionState thought the subgraph was still valid.
* Address PR comments
* Clarify a comment
This PR also includes:
* Remove defaults from named tuples to support python 3.6
* Allows model which takes dicts as input
* Adapts BERT finetuning example to run on the new frontend
* Match numbers for BERT fine tuning model
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* Port legacy checkpoint API into new front-end
This PR also fixes:
* Warnings on ORTTrainer for improper tensor copies
* Inaccurate LRScheduler tests using wrong LR
* Stale DeepSpeed documentation
* Minor code refactoring for Toy BERT tests
* Move experimental state_dict() and load_state_dict() into checkpoint ns
* adding generic configurations for session options
* fix a build break on linux
* fix training ci build break
* fix training ci build break
* addressed CR comments
* fix traning ci build break
* move config_key from enum to string
* add c# api
* add python api
* fix build break
* move prepacking from 2 new api entries to session options configs
* fix traning ci build break
* add python test, update some comments, move const key definition to avoid build break
* addressed comments
* move definitions of keys to common.h
* move api to version 5
* remove accidental change in build.py
* remove pragma to avoid build break
* addressed CR comments
* fix the python build break, and move location of config keys definition
* small typo changes
`LossScaler.update()` was not being properly called due to the incorrect TrainStepInfo.all_finite assignment.
Additionally to this fix, _ORTTrainerModelDesc.is_finite was renamed to _ORTTrainerModelDesc.all_finite to make it more uniform with TrainStepInfo
* Sahar/csharp support openvino (#4703)
* Temp changes and include openvino to ensure nuget package is created with linux till we configure azure ci pipeline
* string id change
* native nuget indentation changes
* documentation changes
* Update Openvino_execution_provider.md
Documentation includes openvino execution provider
* Update OpenVino-ExecutionProvider.md
update details to build csharp api for openvino execution provider .
* vadm backend revert
* Update Openvino-Execution-Provider.md
updated for review comments
* Update OpenVino-Execution-Provider.md
* Update OpenVINO-ExecutionProvider.md
* nuget package custome support for openvino
change in native nuget spec python script for including linux runtime
* change to make path to boolean flag
* removed the tab
* Update OpenVINO-ExecutionProvider.md
updated for review comments
* chnages to include pep8 warnings
modification to documentation
Co-authored-by: saharfraza <sfatima.3001@gmail.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
* Changes to include csharp support for openvino
* Fix flake error
* Fix
Co-authored-by: sfatimar <64512376+sfatimar@users.noreply.github.com>
Co-authored-by: saharfraza <sfatima.3001@gmail.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
* replace strncpy with strlcpy
* keep strncpy to linux
* cancel reseting of string ending for strlcpy
Co-authored-by: Randy <Randy@randysmac.attlocal.net>
Co-authored-by: RandySheriffH <rashuai@microsoft.com>
* Check status of BinaryElementwise::Prepare().
* Add additional status checks for BinaryElementwise::Prepare() and UnaryElementwise::Prepare().
* Add status checks for BinaryElementwisePreparation::BinaryElementwiseBroadcastPrepareHelper().
* Add ORTTrainerOptions class for the new pytorch frontend (#4382)
Add ORTTrainerOptions class and some placeholders
* Add _ORTTrainerModelDesc to perform validation for model description (#4416)
* Add Loss Scaler classes to the new frontend (#4306)
* Add TrainStepInfo used on the new frontend API (#4256)
* Add Optimizer classes to the new frontend (#4280)
* Add LRScheduler implementation (#4357)
* Add basic ORTTrainer API (#4435)
This PR presents the public API for ORTTrainer for the short term
development.
It also validates and saves input parameters, which will be used in the
next stages, such as building ONNX model, post processing the model and
configuring the training session
* Add opset_version into ORTTrainerOptions and change type of ORTTrainer.loss_fn (#4592)
* Update ModelDescription and minor fix on ORTTrainer ctor (#4605)
* Update ModelDescription and minor fix on ORTTrainer/ORTTrainerOptions
This PR keeps the public API intact, but changes how model description is stored on the backend
Currently, users creates a dict with two lists of tuples.
One list called 'inputs' and each tuple has the following format tuple(name, shape).
The second list is called 'outputs' and each tuple can be either tuple(name, shape) or tuple(name, shape, is_loss).
With this PR, when this dict is passed in to ORTTrainer, it is fully validated as usual.
However, tuples are internally replaced by namedtuples and all output tuples will have
tuple(name, shape, is_loss) format instead of is_loss being optionally present.
Additionally to that normalization in the internal representation (which eases coding),
two internal methods were created to replace a namedtuple(name, shape) to namedtuple(name, shape, dtype)
or namedtuple(name, shape, is_loss, dtype) dependeing whether the tuple is an input or output.
This is necessary as ORTTRainer finds out data types of each input/output during model export to onnx.
Finally, a minor fix was done on ORTTrainer. It could initialize ORTTrainerOptions incorrectly when options=None
* Rename input name for test
* Add ONNX Model Export to New Frontend (#4612)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* Create training session + minor improvements (#4668)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Save ONNX model in file (#4671)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Add eval step (#4674)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Add train_step (#4677)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Add LR Scheduler (#4694)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* Add deterministic compute tests (#4716)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* Add legacy vs experimental ORTTrainer accuracy comparison (#4727)
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* Add Mixed precision/LossScaler + several fixes (#4739)
Additionally to the mixed precision/loss scaler code, this PR includes:
* Fix CUDA training
* Add optimization_step into TrainStepInfo class
* Refactor LRSCheduler to use optimization_step instead of step
* Updated several default values at ORTTrainerOptions
* Add initial Gradient Accumulation supported. Untested
* Fix ONNX model post processing
* Refactor unit tests
* Add ONNX BERT example + minor fixes (#4757)
* Fix training issue when passing ONNX file into ORTTrainer
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Add Dynamic Shape support (#4758)
* Update DeepSpeed Zero Stage option to a separate option group (#4772)
* Add support to fetches (#4777)
* Add Gradient Accumulation Steps support (#4793)
* Fix Dynamic Axes feature and add unit test (#4795)
* Add frozen weights test (#4807)
* Move new pytorch front-end to 'experimental' namespace (#4814)
* Fix build
Co-authored-by: Rayan-Krishnan <rayankrishnan@live.com>
Co-authored-by: Rayan Krishnan <t-rakr@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
1. Publish the image ACR, instead of building it every time for every PR
2. Make USE_MKLML and USE_OPENMP be able to co-exist. Currently both of them are enabled in our Linux CI build but indeed only one of them is taking effect.
3. Split nuphar and DNNL to separated pipelines.
4. Fix two warnings in onnxruntime/core/optimizer/matmul_scale_fusion.cc and onnxruntime/test/tvm/tvm_basic_test.cc.
5. Update the manylinux2010_x86_64 image to the latest.
