* First attempt for half2 vectorized memory access in SkipLayerNorm
* Add some functions for debugging
* Clean up the code
* Clean up the code
* Generalize the vectorized kernels with aligned_vector and remove cudaDeviceProp
* Add a unit test for a larger input size
* Fix some Lint C++ warnings
* Use ILP = 4 for the vectorized kernels
* Rewrite the vectorized kernel and templatize ComputeSkipLayerNorm
* Use conditional operator for input_v
* Refactor LaunchSkipLayerNormKernel and replace the original SkipLayerNormKernelSmall with the vectorized kernel
* Clean some comments and rename the layernorm function
* Use ComputeSkipLayerNorm to replace LaunchSkipLayerNormKernel
* Resolve a Lint C++ warning
* Fix SkipLayerNormBatch1_Float16_vec output data
* Add hipified code of bert SkipLayerNorm for ROCmEP
* Resolve some Lint C++ warnings
* Resolve some Lint C++ warnings
* Resolve some Lint C++ warnings
* Resolve Python formatting issue
* Add net6 targets.
Remove maccatalyst as we don't have a native build targetting that.
* Set platform in macos targets
* Add targetFramework entries
* Move NativeLib.DllName definition and set using preprocessor values for simplicity. Couldn't get it to build with the preprocessor based setup when it was in a separate file.
Update the nuspec generation to set platform version for .net6 targets. TODO: Validate versions. I copied them from the managed nuget package the packaging pipeline generated prior to adding targets. Possibly w could/should lower some of the versions.
Hopefully the need to specify a version goes away when the release version of VS2022 supports .net6.
* Try android 31.1 as https://github.com/actions/virtual-environments/blob/main/images/win/Windows2022-Readme.md suggests that should be available on the CI machines
* Fix patch version mismatch
Add some extra debug info in case it helps
* Debug nuget location in CI
* Add workspace entry back in
* Add steps
* One more attempt with hardcoded nuget.exe path and original android31.0 version
* Better fix - found explicit nuget download and updated version there.
* flake8 fixes
* Fix black complaints.
* Exit Microsoft_ML_OnnxRuntime_CheckPrerequisites for net6 iOS.
* Removed outdated comment
* Using vectorized loads (float2) for fp16 to improve performance
* Fix a few warnings from cpplint
* Fix a few warnings from cpplint
* Use __float2half2_rn and fix some cpplint warnings
* Move some computaions to LaunchFastGeluKernel
* Fix some Lint C++ warning
* Using vectorized loads (float4) for fp16 to improve performance
* Switch whether to optimize FastGelu with float4 vectorization
* Switch to float4 memory access based on input_length in FastGelu
* Comment how to set the threshold of float2 and float4 vectorized kernels
* Add FastGelu fp16 unit tests for bias_length = 2 and 8
* Make vectorized kernels generic with aligned_vector
* Unify the vectorized kernels with/without bias
* Refactor the code to suppress cpplint warnings
* Solve formatting issues
* Remove cudaDeviceProp from FastGeluKernel and LaunchFastGeluKernel
* Move fast_gelu_impl.h to rocm/bert
* Fix some Lint C++ warnings and code alignment
* Add .net6 support to the C# nuget package.
Currently requires jumping through a lot of hoops due to .net 6 only being supported in the preview release of VS 2022.
Build existing targets using msbuild.
Add .net6 targets and build using dotnet.
Create nuget package with combined targets.
A few misc automated changes from VS to spacing and adding a couple of properties.
* Try manually installing trt8.4 in multi-gpu pipeline
* Remove stmts that clean up cmake, ctest. Update tensorrt repository name passed to get_docker_image.py
* Update trt and cudnn home
* Don't install trtexec cli tool.
* Increase job timeout
* Revert timeout change and use trt placeholder builder build option
* update trt 8.4ga
* trt 8.4 linux ci pipeline
* fix cmake
* placeholder_builder
* trt 8.4 windows pipeline
* gpu package pipeline
* trt 8.4.1.5 , packaging pipeline updates
* python packaging
* ctest timeout
* python packaging test
* bump timeout
* python format
* format
* revert
* newline
* enable trt python tests
* typo
* python format
* disable on windows
* Rework the EP factory creation setup so we're not cut-and-pasting function declarations in multiple places.
Convert append EP for SNPE to be generic, and also use for XNNPACK.
Add XNNPACK to C# API
* Don't need stub for MIGraphX as it's using provider bridge.
* Remove old 'create' functions that aren't applicable now that the EPs are built as separate libraries.
* Only use EPs that require the layout transform if the opset is supported by the layout transformer.
* Update wasm registration of xnnpack.
* aten op for inference
* fix build error
* more some code to training only
* remove domain from operator name
* move aten_op_executor ext out from ortmodule
* add pipeline
* add exec mode
* fix script
* fix ut script
* fix test pipeline
* failure test
* rollback
* bugfix
* resolve comments
* enable aten for python build only
* fix win build
* use target_compile_definitions
* support io binding
* turn off aten by default
* fix ut
Co-authored-by: Vincent Wang <weicwang@microsoft.com>
Co-authored-by: zhijxu <zhijxu@microsoft.com>
* update TVM
* get alignment constant from TVM
* update TVM_VM_SetInputs to upstream with TVM API
* fix CI issue: update TVM EP dependencies
* add sudo
* revert changes needed to install missing package
* add package for TVM EP CI
Co-authored-by: Valery Chernov <valery.chernov@deelvin.com>
Co-authored-by: KJlaccHoeUM9l <wotpricol@mail.ru>
* Initiate Ort SNPE EP
* fix snpe ep windows build which is caused by the utility method (ToUTF8String) name change on master
* correct the source path for libonnxruntime.so while building for andorid package
* add AdditionalDependencies for amr64
* On MS-Windows, the patchfile must be a text file, i.e. CR-LF must be used as line endings. A file with LF may give the error: "Assertion failed, hunk, file patch.c, line 343," unless the option '--binary' is given.
* fix build failure if snpe is not enabled
* update doc for contrib op
* separate out snpe ep settings to onnxruntime_snpe_provider.cmake
* renaming according review comments
* update according review comments
* Implement XNNPACK support via an EP.
* Layout transform uses the GraphPartitioner infrastructure.
* Node fusion is supported.
* Conv and MaxPool implementations were ported from Changming's PR.
* Added optional mutex in InferenceSession::Run as we only want to allow sequential calls if xnnpack is enabled
* [UPDATE] update amd ci pipeline 2 rocm5.1.1
* [FIX] json format error
* [ERROR] disable unit tests
* [FIX] ucx error
* [FIX] cmake version
* [FIX] units test
Description:
Add the extra param to match gelu in PyTorch in the contrib symbolic function
Motivation and Context
Why is this change required? What problem does it solve?
The symbolic function in /onnxruntime/python/tools/pytorch_export_contrib_ops.py is missing a recently added parameter approximate. We add this parameter and use the exporter defined gelu if approximate is "tanh".
* move all logic for ubuntu dockerfiles
* pass in trt version
* update trt 8.0 file
* downgrade protobuf
* uncomment
* and
* change to 8.0
* update dockerfiles
* checkout protobuf based on version
* adding last dockerfile:
:
* checkout 3.10 protobuf
* fix checkout version
* update to 8.2
* keep only one submodule sync
* cleanup
* Delete Dockerfile.custom-trt-perf
* create checkout submodules script
* properly compare decimals in bin/sh
* combine build ort paths
* deprecate TRT 7.2
* only checkout protobuf if we checkout older onnx-tensorrt
* only pull nvidia container if true, update image
* downgrade protobuf only if we checkout onnx-trt
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* Add quotes to avoid path splitting
* address shellcheck
* use shellcheck suggestions
* Create new pipeline to sign ov ep binaries
* make codesign available
* make codesign available
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* add codesign task
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* windows
* reduce timeout to 15 minutes
Description: Set black's target version to be py37 - py310
Motivation and Context
Black by default targets its format for py3.10. Since our project supports python 3.7, we need to target version to all the python versions supported.
Re-ran black. 13 files reformatted.
Description: Format all python files under onnxruntime with black and isort.
After checking in, we can use .git-blame-ignore-revs to ignore the formatting PR in git blame.
#11315, #11316
* increase timeout
* show mac agent info
* Revert "show mac agent info"
This reverts commit a646ebefff8940a3044f1984107856db33319eb8.
* increase timeout in PR test
TODO: Someone should investigate why the AARCH64 build takes 3+ hours and reduce it if possible. Assuming it's using an emulator given the x64 build with the same arguments takes 13 minutes.
In #11114 , I changed the script to use azcopy instead of azure blob storage's python APIs. However, it doesn't work for the AMD rocm pipeline, because:
1. The machines do not have azcopy installed
2. The machines are not in Azure, so they don't have Azure managed identity. So they still need to use SAS.
Therefore in this PR I get the old python file back, but only use it in the AMD pipeline.
* delete unused files
* only use one dockerfile, otherwise install
* Update pipeline file
* get other changes
* minimal packages
* update pull nightly variable
* try logical boolean
* test boolean
* have build ort as boolean
* case senstive
* use the current head not the previous commit
* add helpful note
* update layernorm to reflect the fix in ROCm 4.3.1
* fix UT
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
Co-authored-by: Ethan Tao <ettao@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* remove rocm42 CI
* update torch to v1.11.0
Co-authored-by: Ethan Tao <ettao@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* Enabling ov-ep for 2022.1 Release
->Added ov-ep 2022.1 flow
->Validated CPU Unit tests with OV
Master using onnxruntime_test_all unit
tests.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix for output mismatch b/w OpenVINO and ONNX
Refer:
https://jira.devtools.intel.com/browse/CVS-60310
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enabling Adobe ops
->Enable Resize op for iGPU
->Enable Add op for iGPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing irrelevant conditions
->Removing some conditions from
GetCapability() which are now not
required. (Removed conditions for
OV version support less than 2021.2)
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable upsample op
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable Adobe proxy-e model
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing any extra conditions for Opset13 ops
* Opset13 changes
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Exception handling for devices
* Added comments
* Implement GPU Throttling feature
*Added GPU Throttling feature for iGPU's.
when user enables it as a runtime option,
it helps in reducing overall CPU usage
of the application
*Added changes to exercise this option
using onnxruntime_perf_test application.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Renaming the runtime config option
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added the user to video and users group
* Handling_GPU.0_GPU.1
* Handling special conditions
->Handling corner cases for
device_type checks
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Modification to include new api 2.0 changes in the code
* Added opset13 changes
->Enabled Few ops
->Added Debug info for case 3b in getcapability()
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enabling ov-ep for 2022.1 Release
->Added ov-ep 2022.1 flow
->Validated CPU Unit tests with OV
Master using onnxruntime_test_all unit
tests.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix for output mismatch b/w OpenVINO and ONNX
Refer:
https://jira.devtools.intel.com/browse/CVS-60310
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enabling Adobe ops
->Enable Resize op for iGPU
->Enable Add op for iGPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing irrelevant conditions
->Removing some conditions from
GetCapability() which are now not
required. (Removed conditions for
OV version support less than 2021.2)
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable upsample op
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable Adobe proxy-e model
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing any extra conditions for Opset13 ops
* Opset13 changes
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Exception handling for devices
* Added comments
* Implement GPU Throttling feature
*Added GPU Throttling feature for iGPU's.
when user enables it as a runtime option,
it helps in reducing overall CPU usage
of the application
*Added changes to exercise this option
using onnxruntime_perf_test application.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Renaming the runtime config option
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added the user to video and users group
* Handling_GPU.0_GPU.1
* Handling special conditions
->Handling corner cases for
device_type checks
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added opset13 changes
->Enabled Few ops
->Added Debug info for case 3b in getcapability()
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Log comments updated
* Changes to enable 2.0 api
* Enabling ov-ep for 2022.1 Release
->Added ov-ep 2022.1 flow
->Validated CPU Unit tests with OV
Master using onnxruntime_test_all unit
tests.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix for output mismatch b/w OpenVINO and ONNX
Refer:
https://jira.devtools.intel.com/browse/CVS-60310
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enabling Adobe ops
->Enable Resize op for iGPU
->Enable Add op for iGPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing irrelevant conditions
->Removing some conditions from
GetCapability() which are now not
required. (Removed conditions for
OV version support less than 2021.2)
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable upsample op
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Enable Adobe proxy-e model
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Removing any extra conditions for Opset13 ops
* Opset13 changes
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Exception handling for devices
* Added comments
* Implement GPU Throttling feature
*Added GPU Throttling feature for iGPU's.
when user enables it as a runtime option,
it helps in reducing overall CPU usage
of the application
*Added changes to exercise this option
using onnxruntime_perf_test application.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Renaming the runtime config option
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added the user to video and users group
* Handling_GPU.0_GPU.1
* Handling special conditions
->Handling corner cases for
device_type checks
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added opset13 changes
->Enabled Few ops
->Added Debug info for case 3b in getcapability()
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix build issue
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixes issues
*Fixes compiler warnings c4458 on windows.
*Fixes the bug in device_type check logic
*Adds print info for enable_opencl_throttling
option in onnxruntime_perf_test
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* commit to make openvino_2021.4 compatible
* Fixed IO Buffer Optimization
* Fix output names issue
* Fix 2021.3 branch
* Bug Fix for Multiple inputs/outputs
- Assigns the right output_name and
input_name for the graph when
returned by CompiledModel::inputs()
OV function.
- Also takex care of output mismatch
issue b/w openvino output and onnx
output
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Add comments for the changes made
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* IO Buffer Changes
* Commit for Disabling GPU Throttling for 2021.4
* Updated branch
* Fix windows build
->Fixed windows build in debug mode
->Disabled scatternd3_tensor_int64
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed CPP Unit tests for CPU
-Fixed shrink, MVN, ReduceL2, Maxpool,
upsample, scatter, slice, reshape,
unsqueeze.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed first set of GPU Tests
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed additional failing tests on GPU
->Added conditions to disable certain ops
under certain conditions
->Disabled certain tests
->Added some op supports for no_dimension
supported
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added Expand op support for CPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added condition for squeeze op
->Shape can't have empty axes attribute
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Add support for LessOrEqual op function
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* OV Interface wait for replaced by indefinite wait call
* use names from ONNX model to access OV tensors
This chnage is to use the input/output names
retrieved from original onnx model to access
OV tensors and to check if there's any input
or output names mismatch b/w ONNX naming
and OV naming.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixes Myriad unit tests and other issues
->Fixes Myriad CPP unit tests
->Fixes output mismatch issue with models with
sub graph partitioning
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix segfault issue
->Fixed case 3b condition in get_capability()
which was causing the segfault issue
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed build isuse with ov 2021.4 with I/O buffer
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Disables performance counters for I/O Buffer
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed inputs/outputs mismatch for HDDL with 2022.1
Signed-off-by: Mohammad Amir Aqeel <mohammadx.amir.aqeel@intel.com>
* Fix to enable GPU FP16
* Enabled mlperf_ssd_mobilenet_300 model fully on CPU
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added ov version specific dll packaging for nuget
* Fixed conditions for few ops
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Dockerfile updates
* Updated License Info
-Updated the copyrights License Info
-modified FP16 transformations with OV 2022.1
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Disabling mlperf_ssd_mobilenet_300 model
->Disabled this model for openvino. The
test is failing in Internal_CI pipelines.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Disabling failing python CPU Tests
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed flake8 python errors
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: hdgx <harinix.d.g@intel.com>
Co-authored-by: mayavijx <mayax.vijayan@intel.com>
Co-authored-by: sfatimar <sahar.fatima@intel.com>
Co-authored-by: mohsinmx <mohsinx.mohammad@intel.com>
Co-authored-by: Mohammad Amir Aqeel <mohammadx.amir.aqeel@intel.com>
* Update orttraining release pipelines to use torch 1.11.0
* Change requirements_torch...txt to requirements.txt
* Update cuda cmake architectures and clean up old files
Follow up to #10904.
- Move node EP assignment for ORT format into SessionState::FinalizeSessionState().
- Add unit test for #10904.
- Make convert_onnx_models_to_ort.py optimization level configurable via environment variable.
* get inputs independently for trtexec
* track one process only
* remove engine and profile files
* change time to commit time
* add runtime option for io binding
* move to commit date
* fixes
* add option for graph optimization
* cleanup docker script
* note second time creation
* allow for parameters to be configured from pipeline at runtime
* uncomment
* include optional arguments at runtime
* post second session creation
* update cmake version
* Revert "update cmake version"
This reverts commit 09a1364eae68610724c8e90eeea777b7ee03f74b.
* Move data format import
* create npm packaging pipeline
* fix indentations
* Update npm-packaging-pipeline.yml for Azure Pipelines
* Update npm-packaging-pipeline.yml for Azure Pipelines
* Update npm-packaging-pipeline.yml for Azure Pipelines
* react-native-ci as a template
* fix typos
* fix template paths
* add a depencendy
* change a stage name
* set different artifact name for each package
* fix typo
* Update npm-packaging-pipeline.yml for Azure Pipelines
Set a build Id for node npm package as a parameter
* Update npm-packaging-pipeline.yml for Azure Pipelines
Set a build Id for node npm package as a parameter
* Update npm-packaging-pipeline.yml for Azure Pipelines
* add c-api test for package
* fix bug for running c-api test for package
* refine run application script
* remove redundant code
* include CUDA test
* Remove testing CUDA EP temporarily
* fix bug
* Code refactor
* try to fix YAML bug
* try to fix YAML bug
* try to fix YAML bug
* fix bug for multiple directories in Pipelines
* fix bug
* add comments and fix bug
* Update c-api-noopenmp-packaging-pipelines.yml
* Remove failOnStandardError flag in Pipelines
* Tweaks to the model utils
* Add handling for a dim_value of -1 when replacing the entire input shape. This occurs in models exported from PaddlePaddle
* make pytorch helpers accessible in package
* make QDQ helpers accessible in package
Add runtime optimization support to ONNX -> ORT format conversion script.
Replace `--optimization_level`, `--use_nnapi`, and `--use_coreml` with a new `--optimization_style` option.
* get inputs independently for trtexec
* track one process only
* remove engine and profile files
* change time to commit time
* add runtime option for io binding
* move to commit date
* fixes
* add option for graph optimization
* cleanup docker script
* include remaining changes
* choose graph optimization option
* add space in option
* Change storage container, simplify build definition parameters.
* Remove explicit version from Objective-C docs.
* Increase timeout.
* Use real storage account.
* Get static website URL with az cli.
* Add android package build settings for full build
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
Co-authored-by: Scott McKay <skottmckay@gmail.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
* skip browserstack test at release pipeline
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* pool name as a parameter to run at lotus
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* Update web-ci-pipeline.yml for Azure Pipelines
* create a packaging pipeline for web
* Update web-packaging-pipeline.yml for Azure Pipelines
* make web-ci-pipeline as a template
* make web-ci-pipeline as a template
* make web-ci-pipeline as a template
* make web-ci-pipeline as a template
* change a paramter name checking a pipeline
* make a pool name changable for react native pipeline
* disable code sign validation for react native
* fix react native package.json publish
* fix indentation
* remove unnecessary comment
* test onnxruntime-common package publish
* ts and js files use lf as eol for windows
* use Linux style of ending line break
* change newLine at only tsconfig.json
* restore a commented code
* fix git restore directory for npm packaging
* fix a typo
* force eol to lf on windows for js directory in CI
Work on minimizing memory management calls by
reducing number of allocations and copies.
Replace std::unordered_set to InlinedHashSet
and add usage of InlinedVector.
Employ std::move() to minimize copying and memory allocations.
Remove copying of the const shared data into each of the
PropagateCast transformer instances.
Move inlined_containers.h header to include/common
Adjust AsSpan imlementation for C++ < 17
* add support for bool type
* add TVM EP support for tests
* include TVM EP in python test pool
* fix pylint
* moved technical imports to a separate file
* clean up post build actions & move _ld_preload.py extension to CMake level
* add files for include TVM EP into CI
* implement custom logger for TVM
* replace TVM logging with ONNX RT logging
* update link for TVM EP tutorial
* clean up TVM EP cmake
* add pybind auto enabling for TVM EP
* fix blank spaces
* code review fixes
* replace print with comment
* add list of EP without TVM EP
* enable onnx tests
* disable contrib ops and ml ops
* reuse Dockerfile.ubuntu
* Move install_tvm_test_dependencies.sh out of Docker context dir, update build definition.
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
* Add initial helper for optimizing a QDQ format model for usage with ORT.
If a DQ node has multiple consumers it will end up in multiple QDQ node units. This is complicated to handle as each qdq unit could end up being handled by different execution providers. By duplicating the DQ node we simplify this logic.
Generally the duplicate nodes will disappear when the qdq node unit is converted to a single node with a quantized operator. If there are qdq node units that are not able to be converted to use a quantized operator the ORT cleanup (pending) to drop remaining Q->DQ pairs between fp32 nodes can remove any remaining DQ nodes.
* Fix pep8 warning
Co-authored-by: Guoyu Wang <wanggy@outlook.com>
* apply the same policy for onnxruntime-common as web and node
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* remove old comment
* Enable Attention op for ROCM EP.
As a note, potential hipify improvements: (1) handle math
contants (attention_softmax.h), (2) correctly generate transpose
options for the GEMM helpers, consider counterpart/dummy API for
CublasMathModeSetter (attention_impl.cu, attention_impl.cu). After
these improvements, we don't need to manually keep copies of the
above mentioned files any more.
* Clean up debugging code.
* Pipeline for ONNX Runtime react native
* Fix a test failure
* test with custom built binaries
* add onnxruntime-common package back
* don't bob build when bootstrap
* revise Android test
* rename example to e2e
* remove onnxruntime packages from package.json
* remove release-it package
* upgrade gradle version to the same as CI
* add a pipeline for react native
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* android and ios mobile build for react native e2e
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* use android aar package template
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* use android aar package template
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* publish ios test results
* add e2e tests and publish a npm package
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* remove aar from npm package
* wait for view displayed
* change a waiting logic
* increase wait time for app launching
* give more time to launch an app
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* disable metro server on testing
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* test ios simulator launching
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* fix iOS e2e test
* use a publishing version of npm packages
* make pretty
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* make only one onnxruntime-common package after packaging
* make a powershell script of packaging universal
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Add a warning for file changes during a test
* clean up
* fix lint errors
* fix js npm packaging
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* Update mac-react-native-ci-pipeline.yml for Azure Pipelines
* resolve comments
* fix a typo
* move table names to one location
* remove session metadata
* reload trt inputs
* fix posting names
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* remove comments
* Split up anubis job and perf run
* add trt environ variables
* No embedded links
* add qdqgroup as input for NodeUnit
* minor update
* hookup nnapi_ep
* minor update
* update compiler setting
* Add a simple UT
* Pipeline change to add build minimal extended with NNAPI for Android
* move GetAllNodeUnits to node_unit.h, add UT for NodeUnits, minor updates
* minor updates
* address CR comments
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
Add abseil and inlined containers typedefs
Introduce TensorShapeVector for shape building.
Use gsl::span<const T> to make interfaces accept different types of vector like args.
Introduce InineShapeVectorT for shape capacity typed instantiations
Refactor cuda slice along with provider shared interfaces
Refactor Concat, Conv, Pad
Build with Conv Einsum and ConvTranspose refactored.
Remove TesnorShape::GetDimsAsVector()
Refactor SliceIterator and SliceIteratorBase
Refactor broadcast
Refactor Pads for twice as long
Remove memory planner intermediate shapes vector
Refactor orttraining
Fix passing TenshroShapeVector to tests
Remove abseil copy and submodule, use FetchContent_Declare/Fetch
Path with separate command
Make RocmAsyncBuffer accept anything convertible to span. Adjust Linux GPU pipeline.
* add back previous changes lost in merge
* post session to dashboard
* post session creation time to dashboard
* fix trt 8 functionality:
* add component governance
* Remove hardcoded values
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* cleanup errors
* post results only once
* checkout 8.0 GA
* try build 8.0 without building shared lib
* add back build_shared_lib, not the problem
* add upload_time to table
* use identifier to post
* Shorten to TRT x.x
* shorten commit hash using rev_parse
* use shortened commit hash
* use nvidia's default TRT_VERSION
Move binary size check(s) to a separate pipeline. In the future, other binary size-related builds can go here.
Add publishing of build artifacts for easier analysis.
Add optional build with debug info.
* migrate to 1ES Hosted Pool
* migrate to Kusto database
* refactor and organize ep names with ORT prefix
* standardize TRT benchmarking with save/load engine, input binding, and workspace
* Add TRT 8.2 to ep perf pipeline
* update model_list.json with full onnx zoo
* add anubis credentials
* add anubis credentials
* clarify trt variables
* get system info from docker image
* remove unwanted commenting
* [ROCm] update hipify-perl location
Depending on the ROCm version installed, hipify-perl might not always
live in the hard-coded path of /opt/rocm/bin. Use python 3.3's
shutil.which to locate the script.
* provide alternative locations for hipify-perl if not in PATH
* implement hipify-perl search as a function
This avoids running the logic during module import since all builds
import the amd_hipify module.
* fix flake8 errors
In a reduced ops build, some source files get updated. This change moves the updated files into the build directory. This way, it is easier to simultaneously manage different build directories (with possibly different reduced ops configurations) based on a single source directory.
* Include onnxruntime binary when not using pacakge referene or uap app.
* Remove the lib\uap10.0 build from the nuget package - causing conflicts
* Add UWP test
* remove build files
* remove local change
* reset mimalloc and onnx-tensorrt
* change username to Microsoft
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* squashed commit for standalone tvm execution provider
* critical fix for correct python build with stvm ep
* get tuning log file from ep options. It has priority over AUTOTVM_TUNING_LOG
* updates and fixes
* update parsing of stvm provider options
* add support of external data for onnx model
* add conditional dump of subgraphs
* remove unused code
* get input tensor shapes through provider options. get output shapes for fixed input ones by TVM API
* support AUTO_TVM tuning log file inside ORT. Selector for Ansor and Auto_TVM is provider option (tuning_type)
* add fp16
* add functionality of conversion of model layout to NHWC if need. Necessary parameter was added to STVM provider options
* fix license text in header. fix log format
* small fixes
* fix issues from flake8
* remove model proto construction from GetCapability
* reserve memory for vector of DLTensors
* add simple tutorial for STVM EP
* STVM docs
* jroesch/tvm -> apache/tvm
* remove dead code, unneccessary logs and comments
* fix in readme
* improve tutorial notebook
* tvm update
* update STVM_EP.md
* fix default value
* update STVM_EP.md
* some TODOs for the future development
* shorten long lines
* add hyperlink to STVM_EP.md
* fix Linux CI error
* fix error in csharp test
Co-authored-by: Jared Roesch <jroesch@octoml.ai>
Co-authored-by: Valery Chernov <valery.chernov@deelvin.com>
Co-authored-by: KJlaccHoeUM9l <wotpricol@mail.ru>
* update base image from 11.4.0 to 11.4.2
* update Linux TRT GPU pipeline to TRT 8.2
* update onnx-tensorrt to 8.2-GA
* disable failing TensorRT 8.2 tests.
* update pad test.
* fix
* update win trt ci pipeline to trt 8.2
* test run with cuda 11.4 and cudnn 8.2
* increase timeout
* revert
* revert
* update packaging pipelines to use trt 8.2
* fix typo
* update trt gpu perf pipeline to trt 8.2
* increase timeout
* delete deprecated ci-perf-pipeline.yml
* bump timeout
* adjust timeout packaging
* update to torch 1.10
* update torchvision version
* update torchtext version
* remove deprecated option enable_onnx_checker
* add unit test to test gradient of GatherElements
* add ORTMODULE_ONNX_OPSET_VERSION in a docker file
The memleak checker used by default in Debug configuration does not
play nice with embedding static lib of ONNXRuntime into binaries,
because other code will not be using the same debug heap, leading
to trouble.
This makes it easier for outside builders to disable it for their
build.
* add ortmodule and eager mode test
* add ortmodule dependency
* convert between aten ort tensor and ortvalue
* register the EP to ortmodule using ort device information
* remove duplicated test
* remove useless dependency
* handle half precision type for ortmodule outputs
* adjust the tensor conversion python code
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* Changes
*Fixed merge conflicts
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* C# Nuget fix for windows
-> OpenVINO Libs included in Nuget package
-> Updated nuget.exe path for openvino ep build in Windows
-> Include mvcmd file along with openvino dlls
* Fixing PEP Style comments
* Comment Removed
Co-authored-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: saharfraza <sfatima.3001@gmail.com>
* add ortmodule and eager mode test
* add ortmodule dependency
* fix eager pipeline
* skip tthe ortmodule test for windows due to win ci issue
* remove useless win ci change
* add torch
Co-authored-by: Abhishek Jindal <abjindal@microsoft.com>
* Add 2 builds to validate the cmake defines for excluding optional components work in both full and minimal builds.
* Create empty config for no-ops build
* Create empty config for no-ops build - attempt #2
* Create empty config for no-ops build - attempt #3
* Update python binding code to work when sparse tensors are disabled.
* Changes to ensure openvino build go through in Windows
* Modified Hetero plugin Logic
*Modified Hetero Feature logic. In Hetero,
if the operator to be marked true in getcapability(),
it should be supported by either of the devices
specified with HETERO in the device_type.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* OV updated to 2021.4.2 version
* OV updated to 2021.4.2 version
* Updated OV to 2021.4.2 version, mono download link and dotnet version
* Copying Managed nugets in openvino c# docker file
*Copying Managed nuget to nugets artifacts
directory
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: saharfraza <sfatima.3001@gmail.com>
Co-authored-by: mayavijx <mayax.vijayan@intel.com>
Co-authored-by: Aravind Gunda <aravindx.gunda@intel.com>
- Only set them as targets for the ORT nuget package
- Use OrtPackageId as the condition for inclusion, if installed
- need to do the nuget restore via msbuild so that this property is set correctly
- Add desktop-only version of the C# sln as there is no way to exclude the mobile specific csproj's from an sln
- use this when applicable if someone is running build.py with the `--build_nuget` flag
Other
- remove attempt to include symbols in the nuget package as nuget doesn't support symbols in native packages
- update build.py to use `nuget` and not a windows specific path and filename for a linux build with `--build_nuget`
* add use_tensorrt build option
* Add use_tensorrt to running tests
* add use_tensorrt for Windows
* make trt ep to skip backend test
* make trt ep to skip backend test
* Fix bug
* Add/Modify description
* modify for debug
* swtich pool to test
* modify to debug
* modify to debug
* add vobersity
* refine the code
* refine the code
* refine the code
* fix flake8 warning
* refine the code
* add pre_load check for trt as well as add cupti lib to cuda depedencies
* modify script to make trt build path the same as cuda
* show error message when user wants to run TensorRT but TensorRT is not installed in the env
* fix bug
* fix bug
* add trt lib for manylinux
* include cuda_dependencies for trt
* rewrite the condition to throw exception
* make code more compact
* Update required operators for prebuilt package to add opsets 14 and 15.
Add helper script to check if the prebuilt package will support the model and if not why not.
* Add support for multiple opsets being specified on a single line in the required operators config. This makes it easier to update the pre-built package config.
It's also required for validation tools to work as they only have a single opset from the model and not per-operator opsets. If we only list the incremental ops we could merge in the ops from the previous opset, but that wouldn't give a way to drop an operator from being supported.
Left the info on which ops changed though so we have a better feel for the cost of supporting each opset.
* Added checks for Hetero/Multi
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Remote Context Plugin
* changes for IO Buffer plugin
* erronous couts added
* erronous entry rectified
* Set the Openvino OP Buffer also as output
* Enable AUTO plugin in OpenVINO EP
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Remote Context Plugin
* changes for IO Buffer plugin
* erronous couts added
* erronous entry rectified
* Added checks for Hetero/Multi
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Set the Openvino OP Buffer also as output
* Enable AUTO plugin in OpenVINO EP
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Please commit error message and rectification of param.context
* Alignment fixed
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Changed the string to OpenVINO_GPU
* hanged OpenVINO to to OpenVINO_CPU
* Onnxruntime updated API for memory location
* Removing Duplicate LOG Error
* Tensor.h removed DeviceType function. Updated comment
* API Comments updated
* Removing changes to Provider Indo
* Erronous commit
* Removing Extra logs
* Merge CMAKE
* Not copy from a local location
* Duplicate Entry
* Remove extra line
Co-authored-by: MaajidKhan <n.maajidkhan@gmail.com>
Adding ARM64 depthwise convolution kernel for symmetric quantization
Motivation and Context
Two improvements against current kernel code :
1. Signed int8 based instructions, no need to extend from 8b to 16b before multiplication.
2. Unrolled loop with manual software pipelining
Co-authored-by: Chen Fu <fuchen@microsoft.com>
* Only serialize runtime optimization records container if non-empty.
* Remove runtime optimizations from onnxruntime/core/flatbuffers/schema/README.md as it's not completely implemented yet.
* Disable partial runtime optimization implementation by default.
* schema change
* cc channges
* remove temp debug code
* Adding fbs namespace to session_state_flatbuffers_utils.h
* Add fbs namepsace to all ort format utils
ORT format model runtime optimization implementation is in progress.
This change adds a build.py option to disable the partial runtime optimization implementation, adds CI builds to test it, and disables runtime optimizations in mobile package builds.
