* Add ability to generate configuration that includes required types for individual operators, to allow build size reduction based on that.
- Add python bindings for ORT format models
- Add script to update bindings and help info
- Add parsing of ORT format models
- Add ability to enable type reduction to config generation
- Update build.py to only allow operator/type reduction via config
- simpler to require config to be generated first
- can't mix a type aware (ORT format model only) and non-type aware config as that may result in insufficient types being enabled
- Add script to create reduced build config
- Update CIs
* Use readelf for minimal build binary size checks.
The on-disk size grows in 4KB chunks which makes it hard to see how much growth an individual checkin causes.
Only downside is that the sum of the sections is larger than the on-disk size (assumably things get packed smaller on disk and some of the section alignment constraints can be ignored)
* Remove unused function
* assert sequence tensor and remove skips
* update testdata json
* use ONNX 1.8 in cgmanifest.json
* use previous commit to workaround
* update ONNX commit ID in docker
* skip test_maxpool_2d_dilations test for now
* update function name
* Enabling fasterrcnn variant and vehicle detector
* changes for 2021_2 branch
* yolov3_pytorch commit
* fixed braces in basic_backend.cc
* ci information added
* faster rcnn variant and vehicle detector changes were made in 2021.1 and not in 2021.2
* some changes to support unit tests
* disable some tests which are failing
* fix myriad tests for vehicle detector
* Did some cleanup
*cleaned up comments
*Disabled Add_Broadcast_0x1 and Add_Broadcast_1x0
tests on MYRIAD_FP16 backend due to a bug
*cleaned up capability_2021_2.cc file
*Removed extra conditions which were added
for some validation in backend_utils
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* yolov3 pytorch workaround to ensure that the output names are matched
* gemmoptest fixed on myriad
* Fixed MYRIADX CPP Test Failures
*Expand,GatherND,Range,Round op's
are only supported in model
*where op with float input data
types are not supported and fixed
*Scatter and ScatterElements op's with
negative axis are fixed
*Reshape op with 0 dim value are not
supported and fixed
*Disabled InstanceNorm_2 test on MYRIADX
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* make changes to yolov3 pytorch
* Fixed python unit tests
*Fixed failing python tests on vpu,
GPU and CPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixes POW op failures on GPU_FP16
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Clean up capability_2021_2.cc
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Updated docx for MultiThreading option
*Added extra info on setting the num_of_threads
option using the API and it's actual usage
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* fixed slice and removed extra prints
* Disabled failing python tests
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Minor changes added in capabilty_2021_2
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* made changes to slice to avoid failures
* Disabling FP16 support for GPU_FP32
->Inferencing an FP16 model on GPU_FP32
leads to accuracy mismatches. so, we would
rather use GPU_FP16 to infer an FP16 model
on GPU Device
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Updated docx for Inferencing a FP16 Model
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* fix for mask rcnn
* Script for installing openvino from source
* Updated with openvino 2021.2 online installation
* code comment fixes
fixed accuracy mismatch for div
* Update OpenvinoEP-ExecutionProvider.md
updated for 2021.2 branch
* Update README.md
updated dockerfile documentation
* Update BUILD.md
build.md update documentation
* permissiong change of install_openvino.sh
* made changes to align with microsoft onnxruntime changes
* Updated with ov 2021.2.200
Co-authored-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
Co-authored-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: mohdansx <mohdx.ansari@intel.com>
Update training Python packaging build to use get_docker_image.py.
Remove BUILD_EXTR_PAR docker build argument.
Update get_docker_image.py to check again for the image in the cache after building and before pushing to reduce the chance of a redundant push.
Description: Add ORT minimal with NNAPI EP to Android CI
Motivation and Context
The added build/test to Android CI will only run UT, additional onnx_test_runner with customer .ort models will be added later
* Remove nGraph Execution Provider
Pursuant to nGraph deprecation notice: https://github.com/microsoft/onnxruntime/blob/master/docs/execution_providers/nGraph-ExecutionProvider.md#deprecation-notice
**Deprecation Notice**
| | |
| --- | --- |
| Deprecation Begins | June 1, 2020 |
| Removal Date | December 1, 2020 |
Starting with the OpenVINO™ toolkit 2020.2 release, all of the features
previously available through nGraph have been merged into the OpenVINO™
toolkit. As a result, all the features previously available through
ONNX RT Execution Provider for nGraph have been merged with ONNX RT
Execution Provider for OpenVINO™ toolkit.
Therefore, ONNX RT Execution Provider for **nGraph** will be deprecated
starting June 1, 2020 and will be completely removed on December 1,
2020. Users are recommended to migrate to the ONNX RT Execution Provider
for OpenVINO™ toolkit as the unified solution for all AI inferencing on
Intel® hardware.
* Remove nGraph Licence info from ThirdPartyNotices.txt
* Use simple Test.Run() for tests without EP exclusions
To be consistent with rest of test code.
* Remove nGraph EP functions from Java code
This PR adds infrastructure to automatically cache docker images used in CI builds in a container registry.
Currently, build images are pulled from a container registry for some builds and built every time for others. The container registry requires maintenance to keep the images up to date and building images every time wastes build agent resources.
With this change, a given build image can be looked up in a cache container registry and if present, pulled, and otherwise, built and pushed. The uniqueness of a build image is determined by a hash digest of the dockerfile, docker build context directory, and certain "docker build" options. This digest is part of the image tag in the cache container repository.
The cache container registry will need to be cleaned up periodically. This is not automated yet.
* Add validation of operator registrations to the reduction script
- the script has all the logic to process the registrations, and there's a CI that uses it
Fix some operator registrations
* Fix CUDA PRelu registration
* Refactor to split out kernel registration file parsing and use in the exclude ops script and an op registration validation script.
Run op validation in minimal build CI
* Fix PEP8 error and some comments
* Add copy sparse model in minimal CI
* Add squeeze 13 support
* fix small typo
* Add ut for squeeze in NNAPI
* Fix some issue in the UT and code
* Modify based on the master change
* Fix build break
replace number matching with relaxed comparison in frontend tests
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Cmake changes for 2021.1
* added new ov version 2020.1 for faster rcnn
* Added missing defs
* equal op modified
* changes to incoroporate faster rcnn
* backend util.cc
* hddl_plugin_config.hpp is depreceated . instead use hddl_config.hpp
* changing myriad precision bool to i32
* gather is not enabled for gpu
* conv2D and pooltest auto_pad attribute should not be null
* negative indices are not valid for scatter op in myriad
* non max suppression op only supported in faster rcnn mode
* maxpool indices output is not supported
* Cleaned redundant code in backends
* Added ifdefs for HDDL config
* cast output dimensions check
topk operator k input it seems only resolved for myriad as it is
throwing issues for ask rcnn . need to verify
* we are limiting the subgraph size to 3 here
* taking care of review comments
* Fixed minor bugs
* Modified Slice op checks
* Added NonZero, Upsample
* Removed TopK if it's in the middle of a subgraph
* incorporated upsample conditions too
* Dockerfile changes for 2021.1 release
* dockerfile aptkey update
* Minor fixes
* ceil condition added again
* Fixed few gpu models
* Disabled LSTM and yolov3 in ModelTests
* python softmax cross entropy tests and negative log likelihood
* Update Build.md
Updated for openvino 2021.1
* Update OpenVINO-ExecutionProvider.md
update openvino execution provider for 2021.1
* Update READMe.md
updated new openvino version
* Update Dockerfile.openvino
added environment variable for DEBIAN Frontend
* Fixed myriad models
* Fixed gather condition
* Fixed mask rcnn model on myriad
* Modified Gather condition
* set default target of MCR dockerfile to MYRIAD_FP16
* Fixed tinyolov3 on CPU
* Update OpenVINO-ExecutionProvider.md
update openvino execution provider documentation
* Update Dockerfile.openvino
Removed environment variable
* Update OpenVINO-ExecutionProvider.md
update image manipulation networks supported
* Update onnx_backend_test_series_filters.jsonc
removed test_upsample_nearest from cpu test cases
* New InternalCI changes for 2021.1
* Full protobuf removed for OpenVINO
* Protobuf added
* Updated with apt installation for openvino
* Revert the testing changes
* Reverted testing changes
* File permessions are changed to original
* Deleted openvino installation and cmake change
* Optimized Dockerfile
Removed unnecessary cmake installation, numpy
* Added missing ifdefs
* delete array fix
* backend_utils.cc output_shape
* Revert "set default target of MCR dockerfile to MYRIAD_FP16"
This reverts commit 928d3e2b71e2f589cf51dacd3a133951cf9ca18d.
Co-authored-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
Co-authored-by: suryasidd <48925384+suryasidd@users.noreply.github.com>
Co-authored-by: S. Manohar Karlapalem <manohar.karlapalem@intel.com>
Co-authored-by: Aravind <aravindx.gunda@intel.com>
Co-authored-by: Aravind Gunda <38353114+gundaarx@users.noreply.github.com>
* add tensor board, remove torch.distributed.lanuch because ort nccl depends on MPI. Use MPI to launch parallel training.
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* cancel night build on pyop
* setup win cuda11 pipeline
* add debug build
* test base gpu settings
* setup pipelines to test cuda 10.2 and 11
* rename linux docker images
* rename docker image tag and add clean up job
* fix typo in cuda 11 config
* set cuda11 env
* update linux cuda 11 pipeline
* reset docker image name
* disable uninitialized warning from linux build
* change the way to silence uninitialized warning
* add flags to linux gpu pipeline
* switch docker image for linux cuda 10.2
* switch linuc cuda 10.2 image
* test cuda11 with devtool8
* try latest built images
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
* enable rejecting models based on onnx opset
* enable unreleased opsets in linux and mac CI
* test fixes and more updates
* enable unreleased opsets in CI builds
* enable released opsets in linux cis
* try fix windows ci yml
* yml fixes
* update yml
* yml updates post master merge
* review comments
* bug fix
* Copy samples to build folder and load models from there. Fix CI
* This PR also includes a fix to path validation for save_as_onnx API
* Add torchtext to CI for GPU training
* Remove new frontend tests from CI
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
* 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>
* 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.
1. Avoid building ONNX of every history ONNX versions in our CI, it is costly and easy to fail.
2. Run docker command without sudo. Previously the user is not in docker group, now Azure DevOps Service have added it in.
1. Increase job timeout, while we are investigating why the tests take much longer
2. Upgrade the linux docker image to manylinux2010, by request from Tianlei. (We had an offline discussion with Pranav and Tracy)
3. Remove the installation of "devtoolset-7" in the CUDA image. It was added for CUDA 10.0, it is not needed for CUDA 10.1. We have moved to CUDA 10.1.
Modify gradle build so artifactID has _gpu for GPU builds.
Pass USE_CUDA flag on CUDA build
Adjust publishing pipelines to extract POM from a correct path.
Co-Authored-By: @Craigacp
Add transformer glue test example to show how to use ORTTrainer to fine-tune a transformer model
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Remove 'model_.' prefix for onnx model initializers in training
* fix test case remove redundant device test
* rename
* Fix state_dict/load_state_dict with frozen_weight
* nit
* Add monkey patch for pt opset 10
* remove pt patch in CI
* nit: newline
Change training perf test build to use "docker" instead of "sudo docker". The training perf test build runs in an environment that supports calling "docker" and not "sudo docker".
Update install_deps.sh to use relative path from script directory to symbolic_opset10.py. This allows install_deps.sh to be called from different working directories.
* Enable running PEP8 checks via flake8 as part of the build if flake8 is installed.
Update scripts in \tools and \onnxruntime\python. Excluding \onnxruntime\python\tools which needs a lot more work to be PEP8 compliant. Also excluding orttraining\tools for the same reason.
Install flake8 as part of the static_analysis build task in the Win-CPU CI so the checks are run in one CI build.
Update coding standards doc.
* initial change to transformer.py
* prepare e2e transformer tests
* refactor transformer tests
* put test python files in a flat folder
* fix typo pip install transform(s)
* python 3.6
* python version to 3.6 in install_ubuntu.sh
* remove argparser
* to use opset ver 12
* workaround loss_scale naming patch in case of loss_fn_
* assign self.loss_fn_ so it can be checked
* skip a few un-needed post-process steps
* fix loss_scale_input_name, clean up post process steps
* skip non-frontend tests
* move cpu/cuda related files to coresponding cpu/cuda folder (#3668)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* type cast for ratio is not necessary for dropout (#3682)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* thrustallocator is not needed since cub is used directly for gather now. (#3683)
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* GatherND-12 Implementation (#3645)
* Renamed, UT passing
* Move GatherND CUDA Kerenl into onnxruntime
* Merge GatherNDOpTest
* Refactor Test code
* Merge CPU Kernel Impl
* Handle Negative Indice, Fix UT
* Improve CUDA kernel to handle negative index
* Minor Fixes
* Preserve GatherND-1 Cuda kernel
* Fix Mac build
* fix UT
* Fix Build
* fix GatherNDOpTest.double > CUDA error cudaErrorInvalidDeviceFunction:invalid device function
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Peng Wang (pengwa) <pengwa@microsoft.com>
* update with reviewers' comments
* testBertTrainingGradientAccumulation was not using rtol and may fail occasionally with small (e-06) difference
* fix merge mistakes
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Weixing Zhang <weixingzhang@users.noreply.github.com>
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
Co-authored-by: Sherlock <baihan.huang@gmail.com>
Co-authored-by: Sherlock Huang <bahuang@OrtTrainingDev3.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Peng Wang (pengwa) <pengwa@microsoft.com>
* Added FP16 transformations
* Revert "Added CMAKE_BUILD_TYPE to make building dynamic"
This reverts commit d3e17af1af655cfdc4d2fec33f52055caa525e85.
* Added FP16 transformations for FP16 builds
* Backend logic cleanup
Cleans the backend(intel_graph.*) code in the following ways:-
1. Minimize global usage: Since all the IR graphs need to be
re-generated on every Infer, it is bad practice to rely on globals
for their saving and usage as there would be multiple readers and
writers to the same global variable leading to incorrect usages or
contentions. This change replaces globals with locals where possible.
This change also fixes an existing bug with due to
incorrect global usage.
2. Remove all unused functions.
3. Remove all unused headers and prepocessor directives.
* removed commented out code
* Disabled default optimization for Intel EP
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fix missed plugins.xml for python bindings
* Fixed the build after latest master changes
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled unsupported ops for accelerators
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added some more disabled ops
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added environment variable to enable debugging
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added more debug statements
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed unsupported ops list for GPU and VPU
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed unsqueeze unit tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added error message to the status
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Overwrite Model proto with shape info from data
Overwrites the shape info of Model proto with the shape from
actual input data. Needed for inferring models with Dynamic
shapes.
* Removed print statement and disabled where op
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Reshape with Empty initializer
* Added more debug statements for 1P
* Don't allow 1D inputs with symbol for dimension
* Disabled some 3rd phase ops
* Disabled split and added zero dimension check for OutputDefs
* Cleanup zero dimensionality check
* Added different data type check for inputs and initializers
* Added conditions for Mod, Cast and Pad
* Removed unused variable
* Disabled scan and added conditions for squeeze
* Added changes for fixing all C++ unit tests
* Implements Backend Manager class for caching
Backend Manager provides a layer of indirection between EP interface
and OV backend that provides caching services for models with
symbolic dims in input shapes.
* clean up commented blocks
* clang-formatting
* Read I/O type info from ModleProto
Read the tensor element type information from ModelProto object,
as FusedNode is no longer available.
* code cleanup
* clang-formatting
* Added print statement for jenkins
* Disabled some python tests
* Changed the path of convert fp32 to fp16 hpp
* Added conditions for BatchNorm in GetCapability
* Fixed failed tests
* Revert "Added conditions for BatchNorm in GetCapability"
This reverts commit c3c28c3b00d27892c42546b35dacdd807a48ee90.
* Added Intel to onnxruntime backends
* pick up vars set by OV package setupvars.sh
* Added conditions for Identity
* remove a few cout prints
* Added conditions for GPU_FP32 unit tests
* Revert "pick up vars set by OV package setupvars.sh"
This reverts commit 8199e029c03eae21a1a7ef6bfdc93d00e5d0198b.
* Commented out fatal message for protobuf
* Might need to be removed
* Add interface class for current backend
* moved common logic to base class
* simplified cpu backend
* Removed unused headers
* use vectors to save i/o tensors for windows compatibility
* move utils fxns to backend_utils namespace
* rename ov_backend to ibackend
* Factory pattern for backend creation
* rename CPU backend to Basic backend
* renamed to vad-M and added to factory list
* Added conditions for VPU
* Added print statements
* Changed the logic for checking for symbolic shapes
* Modified logic for zero dimension check
* Removed VPU single dimension condition
* Removed comments
* Modified logic in DimensionCheck method
* Remove legacy OpenVINO EP
Remove all the legacy code for OpenVINO EP. UEP code will take its
place going forward.
This change does NOT remove OVEP files in the following areas asa
they will be reused by UEP:-
1. Documentation: All .md files
2. Docker releated files
3. Python bindings
4. Java bindings
5. C# bindings
6. ORT Server
7. CI pipeline setup files
* Rename Intel EP to OpenVINO EP
* Added unique names to the subgraphs
* Removed subgraphs with only constant inputs
* Modified subgraph partitioning algorithm to remove const input subgraphs
* Apply suggestion to onnxruntime/core/providers/openvino/openvino_execution_provider.cc
* Tracking output names to fix the output order bug
* Changed output names to a unordered map
* Modified logic to check for symbolic input shapes
* Fixed a bug in Reshape check
* Added empty model path to Model constructor
* Made necessary changes to cmake to build from the binary package
* Changed INTEL_CVSDK_DIR to INTEL_OPENVINO_DIR
* Enable dyn device selection with C++ API
* Added Round operator to unsupported list
* Modified subgraph partition logic for MYRIAD
* Removed supported ops from the list
* Enable dyn dev selection in Py API's
* Add documentation for dynamic device selection
* Use MYRIAD || HDDL instead of VPU
* Removed temporary cast of Int64 to FP32
* Disabled unit Tests for CPU_FP32 and GPU_FP32
* Removed default "CPU" from unit tests to allow overriding
* Removed ops Concat, Squeeze, Unsqueeze from unsupported list
* Get the device id from info
* Removed overwriting device_id and precision
* Enabled ConvTranspose and EyeLike
* Reordered unsupported ops in alphabetical order
* Fixed syntax error
* Fixed syntax error
* Code clean-up: Handle exceptions, logs and formatting
Code formatted according to ORT coding guidelines.
* remove debug print from pybind code
* updated docs with ops and models
* formatting prints
* Added default values for c and j for openvino
* Overriding the values set for c and j to be 1
* BACKEND_OPENVINO should be empty if openvino is not in build
* Overriding c value with default for perftest
* fix VAD-M device string bug
* Add IE error details to exceptions
* Use IE specific device names in EP
* Add VAD-F (FPGA) device support
* Removed unecessary libraries from whl package
* Code changes for Windows compatibility
* Add VAD-F option to python API
* [revert before merge] cmake changes for RC
* Enable Windows build in CMake
* Unset macro OPTIONAL for windows builds
inference_engine.hpp's include chain defines a macro 'OPTIONAL'
which conflicts with onnx project's headers when using MSVC. So
would need to explictly unset it for MSVC.
* Use a single copy of plugin/IE::Core
Defined as a static member in Backend manager
* Remove restriction of single subgraphs for myriad
* Passed subgraph name to Backend to enhance log statements
* Disabled zero dimension conditions
* Disabled concat to remove zero dims
* Enabled building ngraph as part of ORT
* Removed serializing and added versioning
* Fix CPU_FP32 unit tests
* Removed unecessary condition
* add ngraph.so.0.0 to .whl
* Check for zero dimensions only for inputs and outputs
* Restrict loading only 10 subgraphs on myriad
* Build ngraph.dll within UEP. Doesn't link yet
* Rename Linux included libngraph.so to libovep_ngraph.so
Renames locally built libngraph.so containing ONNX importer to
libovep_ngraph.so in order to avoid linkage conflicts with
libngraph.so supplied by OpenVINO binary installer.
Applies only for Linux builds.
* use output_name cmake properties for lib name
* fix .so name format in lib_name.patch
* CMake code cleanup
* Rename WIN32 included ngraph.dll to ovep_ngraph.dll
To avoid conflict with ngraph.dll distributed by openvino.
* Added myriad config for networks without 4 dimensions
* Loading the 10 max clusters for inference on myriad
* Refactor code and add Batching support
Encapsulate subgraph settings into context structs.
Add batching support for completely supported models.
* Disabled some broken tests
* use input_indexes to avoid batch-checking initializers
* Avoid static initialization order error on WOS
* Added candy to broken tests
* InternalCI changes for 2020.2
* Updated DLDT instructions
* Unsaved changed in install_openvino.sh
* Changes after manual check
* Remove custom ngraph onnx_import build for WOS
ONNX Importer on WOS does not have protobuf issue.
* Remove FP32ToFP16 ngraph pass
This conversion is performed implicitly within IE.
* Surround debug logic by #ifndef NDEBUG
* remove invalid TODO comments
* removed references to ngrpah-ep
* clang-formatting
* remove commented code
* comment edits
* updating copyright year to that of first OpenVINO-EP release
* remove redundant log msg
* Modified operator and topology support
* Update build instructions
* doc formatting
* Fixed clip unit tests
* Revert "Remove FP32ToFP16 ngraph pass"
This reverts commit ec962ca5f315a5658ad980e740196f19de2639c1.
* Applying FP16 transformation only for GPU FP16
* Fixed GPU FP32 python tests
* automatically use full protobuf
* disable onnxrt server for now
* Disabled upsample
* update dockerfile instructions
* Removed MO paths and added ngraph path
* Remove OVEP from ORT Server docs
Will put it back in after validation
* Updated path to Ngraph lib
* Disabled Resize and some other python tests
* Removed unnecesary header files
* Use commit SHA to fetch ngraph repo
* Avoid un-needed file changes due to version update
* Fixed clip tests
* Fixed Pow, max and min onnx tests
* build.md doc typo
* Update cmake patch command for ngraph src
* remove dead cmake code for onnxruntime_USE_OPENVINO_BINARY
* use spaces instead of tab
* remove commented code
* Add info about protobuf version
* edit debug env var and enable for WIN32
* specify only version tag of 2020.2 for dockerbuilds
* remove unnecessary file changes
* Pass empty string as default argument to C# tests
* Use ${OPENVINO_VERSION} to name openvino install directory in CI builds
* Enabled unnecessarily disabled tests
* Fixed ngraph protobuf patch
* Fixed error in protobuf patch
* Revert "Use ${OPENVINO_VERSION} to name openvino install directory in CI builds"
This reverts commit 89e72adb8bf3b9712f5c81c5e13fe68c6c0df002.
* Remove unsetting OPTIONAL macro
This is no longer used in recent ONNX update onnx/onnx@da13be2,
so this unset workaround is no longer necessary.
* Use a null string default argument for C# API
* Set OpenVINO version yml files and pass to CI Docker builds
Git Tag info for DLDT as well as install directory are set
using this value.
This reverts commit 9fa9c20348ed72ae360a95c98e9b074d2f9fafc5.
* Documentation: recommendation and instructions for disabling ORT graph optimizations
* more doc updates
* Reduced the number of models according to CI time constraints
Co-authored-by: ynimmaga <yamini.nimmagadda@intel.com>
Co-authored-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
Co-authored-by: Mikhail Treskin <mikhail.treskin@intel.com>
Co-authored-by: mbencer <mateusz.bencer@intel.com>
Co-authored-by: Aravind <aravindx.gunda@intel.com>
Co-authored-by: suryasidd <48925384+suryasidd@users.noreply.github.com>
* add frontend minst test
* to use torch nightly with torchvision
* remove incorrect comment per reviewer's comment
* experiment torchvision import failure
* experiment install_deps.sh
* more experiment install_deps.sh
* experiment install_deps.sh with --upgrade
* Experiment with install_deps.sh.
* Experiment with install_ubuntu.sh.
* Use Ubuntu 18.04 and Python 3.6 for CI.
* Update cmake version for CI.
* Install MPI on Ubuntu 18.04 for CI.
* Increase tolerance for MNIST test.
* Go back to Ubuntu 16.04 for CI, fix installing from deadsnakes ppa.
* Clean-up.
* Update ort_trainer.py from ort_training.
* Get default Ubuntu Python ver back to 3.5.
* Add underscore to opset_version parameter name in ORTTrainer constructor.
* Move loss/model wrap before the call for sample output.
* Update expected values for MNIST test.
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Sergii Dymchenko <sedymche@microsoft.com>
1. Fix onnxruntime server docker file build failure. Tested with the notebook in ONNX tutorial, it works well.
2. Delete the docker files for the other EPs, because currently they don't work and I don't have enough time to update them.
We want to implement SoftmaxCrossentropy and NegativeLossLikelihoodLoss forward training ops for opset-12 but that requires ONNX submodule to point to the latest commit to have the latest and greatest ONNX spec!
- Reverse integrate changes from *.in.proto files in github ONNX repo.
- Regenerate csharp/test/Microsoft.ML.OnnxRuntime.Tests/OnnxMl.cs
- Disable ONNX tests that don't have op implementation for the latest opset.
Use CUDA 10.1 for Linux build
(Windows change is already in)
Please note, cublas 10.2.1.243 is for CUDA SDK 10.1.243, not CUDA 10.2.x. CUDA 10.2.89 need cublas 10.2.2.89. They match on the last part of the digits.
libcublas10-10.1.0.105 won't work!!!
The cuda docker image by viswamy is already using 10.1, no need to change.
* update onnx-tensorrt submodule to trt7 branch
* add fp16 option for TRT7
* switch to master branch of onnx tensorrt
* update submodule
* update to TensorRT7.0.0.11
* update to onnx-tensorrt for TensorRT7.0
* switch to private branch due to issues in master branch
* remove trt_onnxify
* disable warnings c4804 for TensorRT parser
* disable warnings c4702 for TensorRT parser
* add back sanity check of shape tensort input in the parser
* disable some warnings for TensorRT7
* change fp16 threshold for TensorRT
* update onn-tensorrt parser
* fix cycle issue in faster-rcnn and add cycle detection in GetCapability
* Update TensorRT container to v20.01
* Update TensorRT image name
* Update linux-multi-gpu-tensorrt-ci-pipeline.yml
* Update linux-gpu-tensorrt-ci-pipeline.yml
* disable rnn tests for TensorRT
* disable rnn tests for TensorRT
* disabled some unit test for TensorRT
* update onnx-tensorrt submodule
* update build scripts for TensorRT
* formating the code
* Update TensorRT-ExecutionProvider.md
* Update BUILD.md
* Update tensorrt_execution_provider.h
* Update tensorrt_execution_provider.cc
* Update win-gpu-tensorrt-ci-pipeline.yml
* use GetEnvironmentVar function to get env virables and switch to Win-GPU-2019 agent pool for win CI build
* change tensorrt path
* change tensorrt path
* fix win ci build issue
* update code based on the reviews
* fix build issue
* roll back to cuda10.0
* add RemoveCycleTest for TensorRT
* fix windows ci build issues
* fix ci build issues
* fix file permission
* fix out of range issue for max_workspace_size_env
1. Pipeline changes for python 3.8
2. Fix a regression in setup.py which was just introduced in the previous commit.
Please notice, we still haven't made python 3.8 + Windows + CUDA work.
1. temporarily exclude vgg19 test which comsumes too much memory, run out of memory on Upsquared device. Single test pass for vgg19, need furture investigation (#2588)
2. Update docker file to decrease the docker image size
* change c++14 to c++11
* add ld lib path for centos
* enable csharp tests on macos
* fix C API test on MacOS + fix manylinux dotnet install
* fix manylinux dotnet install
* fix lib link
* add centos tests to linux cpu ci pipeline
* Disable failing test
* use centos6 instead of centos7
* change back to centos7
* add dotnet runtime dependency
* fix dotnet runtime dependencies
* install dotnet sdk instead of runtimes
* add more dotnet dependencies
* temporary skip failing test
* ix lib path
* reenable failing test
Remove gsl subodule and replace with a local copy of gsl-lite
Refactor for onnxruntime::make_unique
gsl::span size and index are now size_t
Remove lambda auto argument type detection.
Remove constexpr from fail_fast in gsl due to Linux not being happy.
Comment out std::stream support due to MacOS std lib broken.
Move make_unique into include/core/common so it is accessible for server builds.
Relax requirements for onnxruntime/test/providers/cpu/ml/write_scores_test.cc
due to x86 build.
Add ONNXRUNTIME_ROOT to Server Lib includes so gsl is recognized
1. remove sudo from the cleanup step for Linux so that we don't need the sudo access for vstsagent build user
2. a minor fix in the install_ubuntu.sh to make the image smaller for openvino
* Bump onnx to latest
Update onnx.in.proto with changes for SparseTensor.
* add temp skip tests
* remove passed tests from skip list
* skip more tests for new ops in opset 11
* skip crashing tests
* update handling of new attribute types sparse tensor and sparse tensors
* advance onnx commit and remove skip cpu_flaky_tests
* temporarily skip yolo3 model test due to resize opset10 shape inference regression
* update proto for onnxruntime server
* advance onnx commit further
1. Add openvino GPU nightly build pipeline, this test is running on Intel Up square Edge device. The device are host locally not from Azure VM. We persist a smaller model test data on Edge device.
2. Update the build condition for openvino GPU so it works for GPU_FP32, GPU_FP16
3. add option to install_ubuntu.sh to exclude the package used for nuphar, so that we can save some disk space as the Edge device usually have limited disk space.
Enable Nuphar EP docker build
Revert back to LLVM 6.0.1
Reinstate disabled Softmax tests caused by LLVM 8.0.1
Reinstate Nuphar Python test due to stale sympy version
Increase build timeout of Linux CI
* remove memory copy between CUDA and TRT
* add info to RegisterExecutionProvider input
* use new IDeviceAllocator for trt allocator
* remove SetDefaultInputsMemoryType from TRT EP
* remove onnx-tensorrt 5.0
* add submodule onnx-tensorrt branch 5.1
* remove redundancy
* Update transformer_memcpy.cc
* Update tensorrt_execution_provider.cc
* switch to TensorRT 5.1.5.0
* update python binding
* disable failed test case on TensorRT
* Update activation_op_test.cc
* upgrade to TensorRT container 19.06
* update according to feedback
* add comments
* remove tensorrt allocator and use cuda(gpu) allocator
* update onnx-tensorrt submodule
* change ci build cuda directory name
* Add MacOS leg of Python packaging job
* Update copy files source directory for Mac OS leg
* Add a task to display the binaries directories contents after build wheel creation
* Revert some changes
* Add task to log
* Update
* Remove unnecessary logs
* Update DNNLibrary
* Allow fp16 by default
* Add nnapi build in ci
* Fix nnapi ep after #1268
* Remove unused variables
* Support nnapi in onnx_test_runner
* Update DNNLibrary to fix tests
* Update build.py for android build support, solve conflict of
tools/ci_build/build.py
* Support non-ARM Android build, solve conflict of tools/ci_build/build.py
* Enable android test by x86_64 android emulator
* Add dnnlibrary/NNAPI support in build.py
* suppress the verbose adb output
* Remove debug logs
* Install cmake by pip
* Fix undefined host_protoc_path
* cmake==3.13.2 in pypi is actually 3.12.2, so install 3.13.2.post1 instead
* Fix Android ARM64 build
* Use android ndk r20 instead of r19c, fix conflicts in install_deps_android.sh
* sync onnx to get equal op with float support
* doc update
* fix test failure because of updated shape inference logic for roialign.
* filter consum test cases since it's not implemented yet.
* replace log sinks
* limit headers to include dir
* first changes to do dynamic linking
* wip for using cxx api
* remove weird dangling dependency
* building with tests failing
* finish updating converters
* fix const
* intital introduction of typedef
* change logging to use spdlog
* get tests passing
* clang format
* map logging levels better
* clean up unused imports
* trent cr comments
* clang-format
* code review comments
* changing buffer use to reserve
* Dynamically link
* revert tvm
* update binary uploading
* catch exceptions by const-ref
* Revert "revert tvm"
This reverts commit 387676dd1018134d15eb71fa126f7caf94380800.
* fix typo
* update versioning of lib
* Update cuda for python wheels
* Update cuda for python wheels
* Update cuda for python wheels
* Update azure-pipelines-py-packaging.yml
* Update to cuda 10
* Only test win gpu
* Update cuda for python wheels
* Use manylinux2010 image to build linux python wheels
Allow wheels built to truly be compliant with a manylinux policy
* call install_onnx with relative path
* use caller path
* get abs path of current script
* process unicode char
* replace script name
* add suffix as part of match
* match only the end of path
* Initial commit for OpenVINO Execution Provider
OpenVINO Execution Provider provides the interface for ONNX Runtime
applications to access Intel's hardware accelerators using Intel's
OpenVINO Toolkit.
* Fixed bug in GetCapability to disable custom ops
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added OPENVINO ci pipeline
Added new pipeline for openvino provider,
made changes to support the docker build and
onnxruntime build with openvino.
Signed-off-by: Luis Daniel Castellanos <luis.daniel.castellanos@intel.com>
* Enabled all unit tests for OpenVINO EP
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed syntax issue in run_docker_build.sh file
* Added missing default OPENVINO_VERSION
Default value for OPENVINO_VERSION env was
missing causing the build to fail
* Added install Model Optimizer deps step
* Fixed python unit tests and some tests from onnx_backend_test_series
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Fixed indentation bug
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled some of the python backend tests for OpenVINO
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled some model tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Remove Duplicate checks for openvino in build.py
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Modified GetCapability for FP16
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled GPU FP32 tests that are not supported
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Convert modelProto to string and use it in compile
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Pass byte-array input args to MO
* Serialized ModelProto passed in-memory to MO
ModelOptimizer python module receives the serialized ModelProto
in-memory.
Uses appropriate ONNX function to load the serialized bytes.
* Make Py_Finalize compatible with older python versions
Also, remove pFunc unassigned variable possibility.
* Fallback if input dims of Matmul is greater than 2
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* fixup: Device #define syntax
* Updated the documentation
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Enable dynamic dim value
* removed commented out code
* Added Dockerfile for openvino EP
Updated instructions on dockerfiles/README.md file
Signed-off-by: Luis Daniel Castellanos <luis.daniel.castellanos@intel.com>
* Disabled fp16_inception_v1 test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Code formatting with clang-format
Uses style from the .clang-format file in root directory.
* fixup: docker tag and build error fixes
* Heuristics to automatically detect batching
Distributes slices from batch into parallel infer-request objects.
* Handle disabled tests in GetCapability
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled average pool and max pool if ceil_mode is 1
Also dilations are not supported if they are greater than 1
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Unsqueeze int32 test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* changes to fix output results bug
* Disabled a few C++ unit tests for MYRIAD FP16
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Manually revert '9fe162bb Enable dynamic dim value'
Reverts compile time setting of dynamic shape
Reverting manually due to significantly huge auto-revert conflicts.
* Fixed unused variable warning
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Mul test for GPU_FP16 due to accuracy issue
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* VPU documentation update
* Disabled inception_v1 for MYRIAD and HDDL
*Also disabled few C++ accuracy tests for HDDL
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* updates from upstream
* use the new CustomOpApis for I/O interfacing
* Pass initializers as subgraph meta-def inputs in GetCapability()
Requirement due to API changes introduced with PR# 1019.
* Remove obsolete functions
* Save indexes of graph inputs from fused_node info
Both inputs and initializers are passed as data inputs to the
infer function. To identify only inputs among them, save thier
index info from fused_node in Compile function.
* Documentation changes to enable VPU
* Fix VPU related changes in documentation
* Fix minor changes in documentation
* Fix VPU related changes in documentation
* Use Node.In/OutputDefs() to track graph inputs and outputs.
Don't use graph_viewer's GetInputs() or
GetInputsIncludingInitializers().
* Permit "SAME_UPPER" auto_pad attribute from MaxPool
* Disabled fp16_tiny_yolov2 in onnx model tests
* Updated documentation to include configuration guides for myriad and hddl
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Use 8 Infer requests only for VAD-R
* disable debug prints
* Clang-format source files
* Updated BUILD.md with OpenVINO R5 links
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled same upper python tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Update test exclusion syntax
* Change path of install_onnx.sh
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disable tiny_yolov2 in broken tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Revert "Change path of install_onnx.sh"
This reverts commit ba9db165f3be430f2aff1ef413299ed04637196a.
This change is only required for Intel internal CI pipeline until
the settings are matched with the upstream's CI pipeline.
* Added debug statements for debugging CI error
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Add --build_wheel to linux openvino pipeline
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added -v option to onnx_test_runner for debugging
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed path change patch
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Added -c 1 to onnx_test_runner
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Refactor MO python invocation in separate function
Cleans up Model Optimizer python invocation check and conversion
logic. Invokes MO only once in GetCapability() and passes the
IR strings (xml and bin) to the Compiler as meta-def attributes.
* Add comments
* code cleanup and comments
* Code cleanup for GetCapability
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed unnecessary files
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Revert "Added -v option to onnx_test_runner for debugging"
This reverts commit d1dd70938a94d648df1a1dbbc2e48d0b97e49ec8.
* Revert "Added debug statements for debugging CI error"
This reverts commit b86d41afed2aa29c3508155d6f9c8d3a7263cc60.
* incorporate Status Code changes
* ComputeFunc returns Status::OK() on success
* Use test names to disable tests for MYRIAD and VAD-R
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Rename local identifiers from CNNNetwork to OpenVINO network
CNNNetwork is an OpenVINO's API class that represents more than
just convolutional neural networks (CNNs). Renaming helps to avoid
confusion that the API's only support CNN type models.
* Added error message if building on windows
* Removed duplicate option in Cmake
* Removed unnecessary parameters in activation_opt_test
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Refactor Map search and access logic for efficiently and cleanliness.
* use C++ style casts
* Use os.path.join for python directory path operations
* use C++ style casts
* EP classes should use onnxruntime namespace
* Clean up fixes from PR comments
* Don't explicitly shutdown Py interpreter
* Remove debug print statements
Prints will be re-enabled later with a logging mechanism with
debug/verbose printing options.
* Decrement ref counts for used pyObjects
* Restore build instructions for other compilers
Content under the "Using other compilers" section has been
accidentally deleted by a previous commit. Restoring back that
content from the latest upstream repo.
* CMake code cleanup
Code clean up, commenting and formatting of CMake code.
* Don't pass the unused device_info parameter to OpenVINOGraph ctor.
* Add support for multiple I/O data types
Adds support for the following tensor data types for graph inputs
and outputs:
1) float
2) float16
3) int32
4) int16
5) int8
6) uint16
7) uint8
* cleanup setup.py module list definition
* Deduce index of input using tracked input index map
Ignores initializers in case they are ordered before inputs.
* Removed debug statement in MO code
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* PR feedback
* Removed per_sample_tolerance for openvino
* Removed unnecessary disabled tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed debug function
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled tiny_yolo_v2 due to accuracy issues
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Changed the disabled reason for broken tests
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Disabled Reshape with no input
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Python formatting with Autopep8
* Minor fix for MYRIAD devices
* Added zero dimension check
*Removed setting batch size for the network
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Set the threshold to larger value for MNIST
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Removed setting higher threshold in provider_test_utils
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
* Check for --use_openvino in python wheel setup.py
Add openvino modules to the setup script for building the wheel
package only for --use_openvino a build option.
* Removed nullptr checks for GetNode()
Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
Advance ONNX submodule to 5c51f0dbbe88ee1536f17ee7bd462b2ab3772c52
This commit in ONNX contains a fix to ConstantOfShape test data.
Uncomment ConstantOfShape.
Update test script, make sure exclusions are uniform.
* add version filter to failed tests
* exclude test from backend
* exclude shrink from opset 9
* fix compile err
* exclude certain version of constant shape
* enable flatten test
* fix compile err
* comment mvn test
* disable constantofshape test in x86
* disable x86 test
* get model version from imported opset
* test linux x86 case
* disable nonzero opset 10
* make mutex const
* test filter by commit id
* adjust substr offset
* Limit test platform
* remove change impacting TFModleInfo.h
* refactoring
* refactoring
* test x86 pipeline with filter
* add comment
* restrict version extraction on non-win
* restrict version extraction on non-win
* add tag
* exclude case from backend test
* remove dup
* remove dup
* make script runnable
* hard code adsolute path
* refactor log
* fix x86 compile err
* fix x86 compile err
* fix x86 compile err
* sync with latest tensorrt
* switch to regex
* fix cpu pipeline err
* test filter
* disable nonzero from all versions
* Refactor C# to handle x86
* update run script
* Add Native win x86 tests
* Add native x86 tests for Linux
* Update linux tests scripts to control which tests are run
* update linux image name for x86 to prevent using cached image
* update to not run unit python unit tests unless pybind is specified
* remove --build_wheel as a core common arg. Python cannot run on x86 build
* update OrtGetNumOfDimensions to OrtGetDimensionsCount in rest of C#
* Finer control over when Python tests are run
* add --build_wheel to linux pipeline, instead of run_build.sh
* add --build_wheel to all ci configurations
* update per review comments
* Update the ORT-SRV ci pipeline setup
* Update pip package installation for server tests
* Install requests package in build setup
* Check if python dependencies exists before install
* Accomodate missing optional 'axes' when 'steps' is present in Slice op (#946)
* Accomodate missing optional axes when steps is present in Slice implementation
* PR feedback
* Update package links (#937)
* Update package links
* Minor fix
* Update README.md
* Minor edit
* Update onnx commit (#949)
* Update onnx commit
* disable failing tests which don't have to be fixed for this release
* dummy change to fix file permission
* fix file permission
* Simple integration into CMake build system
* Adds vcpkg as a submodule and updates build.py to install hosting dependencies
* Don't create vcpkg executable if already created
* Fixes how CMake finds toolchain file and quick changes to build.py
* Removes setting the CMAKE_TOOLCHAIN_FILE in build.py
* Adds Boost Beast echo server and Boost program_options
* Fixes spacing problem with program_options
* Adds Microsoft headers to all the beast server headers
* Removes CXX 14 from CMake file
* Adds TODO to create configuration class
* Run clang-format on main
* Better exception handling of program_options
* Remove vckpg submodule via ssh
* Add vcpkg as https
* Adds onnxruntime namespace to call classes
* Fixed places where namespaces were anonymous
* Adds a TODO to use the logger
* Moves all setting namespace shortnames outside of onnxruntime namespace
* Add onnxruntime session options to force app to link with it
* Set CMAKE_TOOLCHAIN_FILE in build.py
* Remove whitespace
* Adds initial ONNX Hosting tests (#5)
* Add initial test which is failing linking with no main
* Adds test_main to get hosting tests working
* Deletes useless add_executable line
* Merge changes from upstream
* Enable CI build in Vienna environment
* make hosting_run*.sh executable
* Add boost path in unittest
* Add boost to TEST_INC_DIR
* Add component detection task in ci yaml
* Get tests and hosting to compile with re2 (#7)
* Add finding boost packages before using it in unit tests
* Add predict.proto and build
* Ignore unused parameters in generated code
* Removes std::regex in favor of re2 (#8)
* Removes std::regex in favor of re2
* Adds back find_package in unit tests and fixes regexes
* Adds more negative test cases
* Adding more protos
* Fix google protobuf file path in the cmake file
* Ignore unused parameters for pb generated code
* Updates onnx submodule (#10)
* Remove duplicated lib in link
* Follow Google style guide (#11)
* Google style names
* Adds more
* Adds an additional namespace
* Fixes header guards to match filepaths
* Consume protobuf
* Unit Test setup
* Json deserialization simple test cases
* Split hosting app to lib and exe for testability
* Add more cases
* Clean up
* Add more comments
* Update namespace and format the cmake files
* Update cmake/external/onnx to checkout 1ec81bc6d49ccae23cd7801515feaadd13082903
* Separate h and cc in http folder
* Clean up hosting application cmake file
* Enable logging and proper initialize the session
* Update const position for GetSession()
* Take latest onnx and onnx-tensorrt
* Creates configuration header file for program_options (#15)
* Sets up PredictRequest callback (#16)
* Init version, porting from prototype, e2e works
* More executor implementation
* Adds function on application startup (#17)
* Attempts to pass HostingEnvironment as a shared_ptr
* Removes logging and environment from all http classes
* Passes http details to OnStart function
* Using full protobuf for hosting app build
* MLValue2TensorProto
* Revert back changes in inference_session.cc
* Refactor logger access and predict handler
* Create an error handling callback (#19)
* Creates error callback
* Logs error and returns back as JSON
* Catches exceptions in user functions
* Refactor executor and add some test cases
* Fix build warning
* Add onnx as a dependency and in includes to hosting app (#20)
* Converter for specific types and more UTs
* More unit tests
* Update onnx submodule
* Fix string data test
* Clean up code
* Cleanup code
* Refactor logging to use unique id per request and take logging level from user (#21)
* Removes capturing env by reference in main
* Uses uuid for logging ids
* Take logging_level as a program argument
* Pass logging_level to default_logging_manager
* Change name of logger to HostingApp
* Log if request id is null
* Update GetHttpStatusCode signature
* Fix random result issue and camel-case names
* Rollback accidentally changed pybin_state.cc
* Rollback pybind_state.cc
* Generate protobuf status from onnxruntime status
* Fix function name in error message
* Clean up comments
* Support protobuf byte array as input
* Refactor predict handler and add unit tests
* Add one more test
* update cmake/external/onnx
* Accept more protobuf MIME types
* Update onnx-tensorrt
* Add build instruction and usage doc
* Address PR comments
* Install g++-7 in the Ubuntu 16.04 build image for vcpkg
* Fix onnx-tensorrt version
* Check return value during initialization
* Fix infinite loop when http port is in use (#29)
* Simplify Executor.cc by breaking up Run method (#27)
* Move request id to Executor constructor
* Refactor the logger to respect user verbosity level
* Use Arena allocator instead of device
* Creates initial executor tests
* Merge upstream master (#31)
* Remove all possible shared_ptrs (#30)
* Changes GetLogger to unique_ptr
* Reserve BFloat raw data vector size
* Change HostingEnvironment to being passed by lvalue and rvalue references
* Change routes to getting passed by const references
* Enable full protobuf if building hosting (#32)
* Building hosting application no longer needs use_full_protobuf flag
* Improve hosting application docs
* Move server core into separate folder (#34)
* Turn hosting project off by default (#38)
* Remove vcpkg as a submodule and download/install Boost from source (#39)
* Remove vcpkg
* Use CMake script to download and build Boost as part of the project
* Remove std::move for const references
* Remove error_code.proto
* Change wording of executable help description
* Better GenerateProtobufStatus description
* Remove error_code protobuf from CMake files
* Use all outputs if no filter is given
* Pass MLValue by const reference in MLValueToTensorProto
* Rename variables to argc and argv
* Revert "Use all outputs if no filter is given"
This reverts commit 7554190ab8e50ba6947648c2f3e2a3d4d9606ce0.
* Remove all header guards in favor of #pragma once
* Reserve size for output vector and optimize for-loop
* Use static libs by default for Boost
* Improves documentation for GenerateResponseInJson function
* Start Result enum at 0 instead of 1
* Remove g++ from Ubuntu's install.sh
* Update cmake files
* Give explanation for Result enum type
* Remove all program options shortcuts except for -h
* Add comments for predict.proto
* Fix JSON for error codes
* Add notice on hosting application docs that it's in beta
* Change HostingEnvironment back to a shared_ptr
* Handle empty output_filter field
* Fix build break
* Refactor unit tests location and groups
* First end-to-end test
* Add missing log
* Missing req id and client req id in error response
* Add one test case to validate failed resp header
* Add build flag for hosting app end to end tests
* Update pipeline setup to run e2e test for CI build
* Model Zoo data preparation and tests
* Add protobuf tests
* Remove mention of needing g++-7 in BUILD.md
* Make GetAppLogger const
* Make using_raw_data_ match the styling of other fields
* Avoid copy of strings when initializing model
* Escape JSON strings correctly for error messages (#44)
* Escape JSON strings correctly
* Add test examples with lots of carriage returns
* Add result validation
* Remove temporary path
* Optimize model zoo test execution
* Improve reliability of test cases
* Generate _pb2.py during the build time
* README for integration tests
* Pass environment by pointer instead of shared_ptr to executor (#49)
* More Integration tests
* Remove generated files
* Make session private and use a getter instead (#53)
* logging_level to log_level for CLI
* Single model prediction shortcut
* Health endpoint
* Integration tests
* Rename to onnxruntime server
* Build ONNX Server application on Windows (#57)
* Gets Boost compiling on Windows
* Fix integer conversion and comparison problems
* Use size_t in converter_tests instead of int
* Fix hosting integration tests on Windows
* Removes checks for port because it's an unsigned short
* Fixes comparison between signed and unsigned data types
* Pip install protobuf and numpy
* Missing test data from the rename change
* Fix server app path (#58)
* Pass shared_ptr by const reference to avoid ref count increase (#59)
* Download test model during test setup
* Make download into test_util
* Rename ci pipeline for onnx runtime server
* Support up to 10MiB http request (#61)
* Changes minimum request size to 10MB to support all models in ONNX Model Zoo
* Adding versioned dlls to tar/zip packages
* fix syntax error
* fix version name of dylib
* minor fix in the target
* update pattern for versioned dylib files
* move files
* move files
* Remove NonMaxSuppression from Contrib op, move it to Onnx domain, opset 10
* move NMS out of namespace contrib
* update data type in UT
* update to latest onnx
* white list the node test for Mod which is not implemented yet
* enable android build
* Add 'log' to onnxruntime_EXTERNAL_LIBRARIES
* Remove cmake about header_files_test.cc
* Add Android CI pipeline
* Remove some ms-specific(?) ci
* Fix bash error
* Add execute flag for install_deps_android.sh
* Add install_ubuntu_for_android.sh
* Remove python in deps for android
* Add comment for BUILD_ARCH
* Set BUILD_SERVICE to cpu
* Set BUILD_OS in run_build.sh
* Fix -o bug in run_build.sh
* Android -> android
* Correct the android ndk location
* Checkout submodules in my own azure pipelines
* Revert "Remove some ms-specific(?) ci"
This reverts commit 302463213480487d8944c3127a3b311c591d55c0.
* Revert "Checkout submodules in my own azure pipelines"
This reverts commit 1acfb6755f933e532b8312ca35bb4900a833903f.
* Exclude unreferenced global data and op doc strings in the opschema object. The first causes a decrease in the binary size by at least 85k. The latter reduces resident memory size.
* Update onnx to incorporate my PR that fixes SetDoc compiler warnings
* Ensure Linux binaries are built with debug info. Extract debug info out of the main binaries. Strip the main binaries.
* add binutils
* add uname
* add binutils
* remove linux portion
* Update onnx
* Support updated function schema in ORT
* Update onnx related commit hash
* Check out an older commit in ONNX
* Add support for subgraph attribute
* Add comments
