* 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>
Adding code for symmetric quantized matrix multiplication. Used in quantized convolution, achieving significant perf gain.
TODO, use Symmetric Quantized GEMM in other operators!
TODO address activation buffer overread in custom allocators and tensors supplied by users.
DOT kernel perf test:
Pixel 5a:
Cartoongan 513.539 ms 471.786 ms
Efficient 57.5169 ms 56.4174 ms
Edgetpu 14.6673 ms 13.5959 ms
NEON kernel perf test
Pixel 3a
Cartoongan 1423.53 ms 1069.92 ms
Efficient 114.086 ms 107.968 ms
Edgetpu 39.2632 ms 36.9839 ms
Co-authored-by: Chen Fu <fuchen@microsoft.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.
* clearing map for eager mode backends
* clearing map for eager mode backends manager
* making OrtBackendsManager an extern variable and trying to delete it
* cleaning backends manager when the python interpret exits
* adding ifdef for eager mode code
* disabling warning for pybind state file
* disabling warning for python module file
* running clang auto format and reducing redundancy
* remove new line
* moving declaration to a new header file
* adding the header file for eager mode for python module
* removing source files for eager mode
* add source file for python module in eager mode
* Update orttraining/orttraining/python/orttraining_python_module_eager.h
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
Co-authored-by: Thiago Crepaldi <thiago.crepaldi@microsoft.com>
Although github works with both, this is more precise.
Having an extension also makes it easy to match with regex, when we want to inject code to reroute traffic to our own git mirror.
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.
* 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
Adding a symmetric quantized convolution kernel for ARM64
Note:
Indirect conv performs worse for shallow convs (input channels are small). This is much more so for low end pre-dot CPUs, where only 128 or deeper conv is faster with indirect conv. With DOT-CPUs, 32 deep conv is already faster
Co-authored-by: Chen Fu <fuchen@microsoft.com>
* Add QAttention to DNNL EP
Add QAttention to DNNL EP (limited support and disable for gpu)
update ONEDNN version to 2.4.4
bug fix in getcapability
add memory debug print
Signed-off-by: Wang <zhaoyang.wang@intel.com>
* Address Code Review + MatMulInteger Fix
clean up code and add comments
fix matmulinteger and add fusion rule to enable initialized vector weight zero
points of 0s
update DNNL_TAG to v2.5
Signed-off-by: Wang <zhaoyang.wang@intel.com>
* Linux Compile Fix + rollback ONEDNN to 2.4.4
Signed-off-by: Zhaoyang Wang <zhaoyang.wang@intel.com>
* Fix QAttention Debug build
Signed-off-by: Wang <zhaoyang.wang@intel.com>
* Fix QAttention build if USE_DNNL not specified
Signed-off-by: George Nash <george.nash@intel.com>
Co-authored-by: Wang <zhaoyang.wang@intel.com>
Co-authored-by: MTC <63478620+jeyblu@users.noreply.github.com>
* fix error C4996
* remove wd4996 and fix error C4966
* fix typo
* remove wd4996 for onnx-tensorrt
* remove more /wd for onnx-tensorrt
* gix bug for strncpy_s of (Buffer is too small && 0)
* fix code to remove warning 4244
* fix code to remove warning 4267
* remove /wd4267 /wd4244
* fix bug
* change int to size_t
* using size_t instead of int
* use float instead of double
* Use size_t instead of int
* use size_t instead of int
* use size_t instead of int. Also fix typo
* 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>
* POWER10: Add optimized dgemm kernel
This patch makes use of POWER10 matrix multiply assist feature and
adds new DGEMM kernel.
* Indentation update
Co-authored-by: Rajalakshmi Srinivasaraghavan <rajis@linux.ibm.com>
* Arm64 Depthwise Convolution 3x3.
* Add 5x5 intrinsic dwqconv for arm64
* rebase to master, remove no-need logic after arm64 convsym enabled.
* Some more adjustment on the instrunction pipeling.
* Add specific test cases.
* Fix test dimension too small.
* Fix build warning as error on some CI.
* better format, etc.
* 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.
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.
* explicit link with libtorch instead of use cmake var to avoid introduce mkl dependency
* use find_lib to get libtorch lib name
* temp fix
* add missing libraries
Co-authored-by: Cheng Tang <chenta@microsoft.com>
