* 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
* 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>
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
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.
* 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
* 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>
* 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>
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>
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.
Add Xamarin support to the ORT nuget packages.
- Update C# code to support Xamarin builds for iOS and Android
- refactor some things to split out common code
- include iOS and Android ORT native shared library in native nuget package
* make work for both rocm 4.2 and rocm 4.3.1
* fix rocm 4.3.1 docker image reference
* fix CUDA_VERSION to ROCM_VERSION
* fix ReduceConsts conflict def
* add ifdef to miopen_common.h as well
* trailing ws
* 2021.4.1 Docker and ci changes
* OV version change
* Removing Imagescaler op from the op's list
Reverting this change which was added in last
PR. Imagescaler is now deprecated. so removing
it from the supported list. Also this
op is causing regression in the performance
of the FP16 models.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Re-writing the help message for num_of_threads
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: Aravind Gunda <aravindx.gunda@intel.com>
* install protobuf from source
* fix rm command in Dockerfile
* fix options on rm command
* fix cd into protobuf source directory
* try again
* remove strip step
* debug list the files
* ls on /usr
* more debug
* more debug
* adjust LD_LIBRARY_PATH
* try remove protobuf before ORT build
* updates for picking pnnx commit
* add tests filter to c# tests
* plus test fixes
* fix versioning for contrib ops
* fix tests
* test filter for optional ops
* more versioning related updates
* fix test
* fix layernorm spec
* more updates
* update docs
* add more test filters
* more filters
* update binary size threshold
* update docs
* draft - enable model local function
* enable model local functions in ORT
* update to latest rel onnx commit
* plus tests
* plus more updates
* plus updates
* test updates
* Fix for nested functions + shape inference
* plus bug fix and updates per review
* plus fixes per review
* plus test updates
* plus updates per review
* plus fixes
* fix a test
* copy changes from trt_and_mem
* second edits
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml for Azure Pipelines
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml for Azure Pipelines
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml for Azure Pipelines
* change to cuda 11.4
* build with cuda 11.4
* Update Dockerfile.ubuntu_cuda11_1_tensorrt7_2
* add cmake extra defines
* cmake architectures
* fix cmake arch
* Delete ubuntu-18.04.Dockerfile
* Rename Dockerfile.ubuntu_cuda11_1_tensorrt7_2 to Dockerfile.ubuntu_cuda11_4_tensorrt7_2
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml for Azure Pipelines
* removing previous ort args
* rename to cuda 11.4
* remove cuda 10_2
* delete trt 7.1
* remove 7.1
* Passing in cuda architecture to reduce build time
* always add submodule sync due to recursive cloning
* fix run command
* add and
* take away unused arms and share python installation script
* Update linux-gpu-tensorrt-ci-perf-pipeline.yml
* Update Dockerfile.tensorrt
* cleanup file
* install python directly on dockerfile - move to scripts in future
* Update Dockerfile.custom-trt-perf
* adding cuda 11.1 for missing Libnvrtc.so.11.1
* Delete install_python.sh
* modify for test
* modify for test
* modify for test
* modify for test
* modify for test
* modify for test
* prepare for PR
* Rename cuda directory to gpu directory in tarball
* Fix gpu java package
* fix bug
* fix small bug
* Add onnxruntime_providers_shared.dll into gpu nuget package
* Modify for test
* Temporarily remove for test
* Modify for test
* Modify for test
* Test packging Windows combined GPU
* Test packging Windows combined GPU
* Test packging Windows combined GPU
* Test packging Windows combined GPU
* modify for test
* modify for test
* fix bug
* Modify for test
* Modify for test
* Modify for test
* Modify for test
* Modify for test
* Modify for test
* Modify for test
* Modify for test
* Prepare for PR
* Prepare for PR
* Code refactor
* Rename proper Artifact name
* Rename intermediate Artifact names
* Revert Artifact Names
* Rename Artifact Names
* Modify Artifact name
* Modify Artifact name
* Modify Artifact name
* Update Java package
* Update Java package
* fix bug to change artifact name
* Fix bug for the wrong file path
* Fix no fetching correct artifact and test
* temporarily modify for test
* undo the change for test
* fix build - python.h not found
* disable --build_shared_lib for ortmodule tests
* fix
* fix the build flag
* disable --build_shared_lib for training path (not only for ortmodule)
* fix missing test model files
* disable test CApiTest.test_custom_op_library when ENABLE_TRAINING_TORCH_INTEROP is ON
* enable custom_op_library build
* fix build
* fix
* merge master and fix build failure
* build onnx_test_runner when onnxruntime_ENABLE_TRAINING_TORCH_INTEROP is ON
* resolve comments
* use --enable_training_torch_interop to replace "onnxruntime_ENABLE_TRAINING_TORCH_INTEROP=ON"
* initial update from 11.1 to 11.4
* change 11.4.1 to 11.4.0
* adjusting to match nvidia/cuda image tags
* adjusting to match nvidia/cuda image tags centos7
* correction to 11.4.0
* correction to 11.4.0
* update to cuda 11.4
* change training back to 11.1
* change training back to 11.1
* point to correct nvcr.io/nvidia/cuda 11.4.1 image
* change centos8 to centos7
* correct cudnn path
* Update linux-gpu-ci-pipeline.yml for Azure Pipelines
* Update c-api-noopenmp-packaging-pipelines.yml
* need to resolve centos images but remove space and change to 11.4
* Update linux-gpu-ci-pipeline.yml
* add cudnn to docker image
* bump devtoolset to 10
* revert cuda 11.4 change to setup_env_trt
* orttraining back to 11.1
* use nvcr.io
* Fix previous change back to cuda 11.1
* update cudnn path
* use cudnn image (revert if failure)
Add IsSparseTensor
Add CreateSparseTensor
Add utilities and test fully sparse instantiation
Fully sparse blocksparse
Add test and docs for fully sparse tensor instantiation
Rework creation API
Use API
Non string API
Retrofit of existing String API
Add tests
Add documentation
Address build issues (Winml pending)
Add inference test
Bump binary size
Add ifdef DISABLE CONTRIB
* updates for picking pnnx commit
* add tests filter to c# tests
* plus test fixes
* fix versioning for contrib ops
* fix tests
* test filter for optional ops
* more versioning related updates
* fix test
* fix layernorm spec
* more updates
* update docs
* add more test filters
* more filters
* update binary size threshold
* update docs
* plus more fixes
* updates per review
* update to release commit
* add filters for optional type tests
* plus updates
* update onnx-tensorrt parser to master
* disable unsupported tests
* add cuda sm 75 for T4
* update tensorrt pipeline
* update trt pipelines
* update trt pipelines
* Update linux-gpu-tensorrt-ci-pipeline.yml
* update trt cid pipeline
* Update linux-gpu-tensorrt-ci-pipeline.yml
* Update Tensorrt Windows build pool and TensorRT/CUDA/CuDNN version
* update to cuda11.4 in trt ci pipeline
* update base image to cuda11.4
* update packaging pipeline to cuda11.4
* clean up
* remove cuda11.1 and cuda11.3 docker file
* disable unsupported tensorrt tests at runtime
* Update linux-multi-gpu-tensorrt-ci-pipeline.yml
1. Update SDLNativeRules from v2 to v3. The new one allows us setting excluded paths.
2. Update TSAUpload from v1 to v2. And add a config file ".gdn/.gdntsa" for it.
3. Fix some parentheses warnings
4. Update cmake to the latest.
5. Remove "--x86" build option from pipeline yaml files. Now we can auto-detect cpu architecture from python. So we don't need to ask user to specify it.
SparseTensor support
Implement Builder pattern
Fix support for 1-D and 2-D COO indices
Implement and test CSR support.
Handle shape inference for SparseTensors
Implement conversion for COO, CSR and tests.
Address the case where constant sparse initializer is the output.
Implement test infra for SparseTensors
Implement SparseDenseMatMul for Csr and COO and tested it.
Add hash for SparseToDenseMatMul
Finish shared provider refactor
Refactor GetOrCreate to Create
Working on py interface
Expose OrtDevice and use it in allocate_numpy
Adjust Sparse interfaces, add support for string SparseTensor. Add tests.
Add and test to_cuda()
Add accessors to format specific indices
Test values and indices views, read-only flag, after GC access
Add sparse related methods to OrtValue
Re-work SparseTensor wrapper, add OrtValue methods
Rework numpy_array_to_cuda/to_cpu
Add run_with_ort_values
Add models and test sparse_mat_mul with run_with_ort_values
Refactor sparse tensor to use a single buffer
Ifdef x86 Eigen CSR sparse matmul implementation
Exclude broken test, check for string type when copying cross device
Split pybind schema, regenerate docs, add exclusion
Conditionally exclude schema module
Update docs fix cuda build
Add test to a filter and renerate JS docs
Add conversion and test string support for sparse tensors
Exclude conversion utils from minimal build
Add CUDA Memcpy and adjust provider interfaces
* Changes to ensure the openvino-ep-2021.4 branch is created
* Fix failing cpp and python unit tests
* Fixed Myriad Tests for Ov_2021.4
* Disabled failing python tests for myriad
* Fixes models which were breaking w.r.t 2021.4
* Added fixes to Fix tinyyolov3 working on Myriad
and MaskRcnn, FasterRcnn using GPU_FP32
* Added FP16 output data type support for ngraph
* Implemented ReadNetwork() method
->Using Core::ReadNetwork() method for reading and creating a CNNNework
->Since OpenVINO™ 2020.4 version, Inference Engine enables reading ONNX models
via the Inference Engine Core API and there is no need to use directly the low-level
ONNX* Importer API anymore. To read ONNX* models, it's recommended to use the
Core::ReadNetwork() method that provide a uniform way to read models from ONNX format.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed ngraph f16 supported output type
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Added comments in data_ops.cc
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fixed broken windows build
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Disable failing CPP tests on CPU
Some of the convtranspose tests are failing on
OpenVINO-EP CPU due to accuracy mismatch w.r.t
default CPU. so currently we are disbaling
these tests.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Updated for ov version 2021.4
* Changes to include qdq ops in code
* Disabled failing python tests on GPU
Disabled two maxpool python tests on
GPU as they were passing but throwing
segfault
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix the backward compatibility issue
ReadNetwork() API has a bug and will only work
starting from OpenVINO 2021.4 version.
The previous versions will still have to use
onnx importer route
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
* Fix CMakeLists.txt for OpenVINO EP
If a directory with OpenVINO is sourced,
the latest OpenVINO settings have to
be imported.
Signed-off-by: MaajidKhan <n.maajidkhan@gmail.com>
Co-authored-by: sfatimar <sahar.fatima@intel/com>
Co-authored-by: sfatimar <64512376+sfatimar@users.noreply.github.com>
Co-authored-by: Aravind Gunda <aravindx.gunda@intel.com>
* Add ability to generate ios static framework
* Fix typos
* Add pod cache clean, update some comments of previous commit
* Fix CI failure with newly added cpuinfo library
* Update test model (CoreML requires node has a name)
* Addressed CR comments
Pytorch cpuinfo library allows us to query current cpu features, micro-architecture and cache size, etc. These information is needed for targeted performance optimizations.
Unfortunately it does not work under Windows/ARM. We need to develop our own later
* Add metadata_props to ORT model
* Minor update
* Update python binding, and increase the minimal pipeline size threshold
* Fixed a small bug in serializing ir_version
* Remove temp ort.py.fbs and add it to .gitignore
* first attempt share docker image across python and torch versons
* set dependency between jobs
* fix yaml grammer
* remove python version from first stage
* clean deepspeed directroy
* split into two images according torch version
* fix yaml syntax
* invalidate cache
* remove DS to prevent torch 1.9.0 upgrade
ORTModule requires two PyTorch CPP extensions that are currently JIT compiled. The runtime compilation can cause issues in some environments without all build requirements or in environments with multiple instances of ORTModule running in parallel
This PR creates a custom command to compile such extensions that must be manually executed before ORTModule is executed for the first time. When users try to use ORTModule before the extensions are compiled, an error with instructions are raised
PyTorch CPP Extensions for ORTModule can be compiled by running:
python -m onnxruntime.training.ortmodule.torch_cpp_extensions.install
Full build environment is needed for this
1. Remove some unused code and simplify tools/ci_build/github/linux/run_dockerbuild.sh.
2. Enable Nuget CUDA tests. The original design was we could leverage Directory.Build.props and let cmake generate the required properties(USE_CUDA/...) there. However, in nuget packaging pipeline we test the package on a different host that doesn't run cmake command and doesn't have the auto-generated Directory.Build.props file.
