* Update to flatbuffers v2.0.0 (#10866)
* Fix Reduced ops pipeline (#10861)
* Fix a couple of issues with the python package tools (#10858)
* 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
* Fix wrong percentile values returned during calibration (#10847)
* Use numpy.percentile to get the lookup value.
* Use 1.0 as float value rather than integer.
* Add missing cdf parameter for `np.percentile`.
* Use 100. instead of 1.0
* Remove print.
* Update from @yufenglee
* Add support for opset 16 to transpose optimizer. (#10841)
* Add support for opset 16 to transpose optimizer.
Only change required is for GridSample to be added to the layout sensitive ops. The existing handling for layout transpose works with that as the first input and first output are layout sensitive.
Update the optimize to be able to return an error message if it fails.
* Use separate build directories for full and mobile iOS packages. (#10835)
* Address performance issue with abseil flat_hash_table. (#10819)
When returning by value in a cross DLL call, the hash table
even though containing all the entries that are originally there
can not find at least some of them. Reverting to std::unordered_set
pending further investigation.
* Mark end of version 11 C API. (#10803)
* Mark end of version 11 C API
* Add static_assert
* avoid using LocalFree on FormatMessageW buffer (#10796)
* remove local free
* Remove local free from onnxruntime
* don't allocate
* Change to use constexpr to satisfy CPU build warning
* Integrate C-API tests into Pipelines for release packages (#10794)
* 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
* Detect runtime CUDA JIT and warn the user (#10781)
* Use cudaMalloc vs cudaDeviceSynchronize and show the total time
* Update convert_onnx_models_to_ort.py to support runtime optimizations. (#10765)
Add runtime optimization support to ONNX -> ORT format conversion script.
Replace `--optimization_level`, `--use_nnapi`, and `--use_coreml` with a new `--optimization_style` option.
* Add multithreading test and put a lock on nvinfer1::createInferRuntime() for TRT EP (#10714)
* Add multithread unit test and put lock on library call
* update code
* remove debug code
* add comment
* add one session multi-threads inference
* Put lock for build engine all the time
* Update naming and comment
* remove unnecessary lock
* Revert "remove unnecessary lock"
This reverts commit 9c2317b1d2273dec0ebdeb52160bc757839e5edc.
* Fix handling of nodes inserted by NHWC transformer. (#10904) (#10925)
* Revert "Upsample support NHWC (#10554)" (#10917)
This reverts commit bd08f11a58.
Co-authored-by: Yufeng Li <liyufeng1987@gmail.com>
* [python API] Change raise import error when `C:\Windows\System32\vcruntime140_1.dll` is not found to warning (#10927)
* remove throw if C:\\Windows\\System32\\vcruntime140_1.dll cannot be found
* Add comments and update warning message
* adding back accidentally removed line
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
* [js] Create npm packaging pipeline (#10886)
* 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
* Follow up update for python API checking if `vcruntime140_1.dll` is available (#10927) (#10933)
Co-authored-by: Hariharan Seshadri <hasesh@microsoft.com>
Co-authored-by: Scott McKay <skottmckay@gmail.com>
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com>
Co-authored-by: Pranav Sharma <prs@microsoft.com>
Co-authored-by: Ryan Lai <rylai@microsoft.com>
Co-authored-by: Ryan Hill <38674843+RyanUnderhill@users.noreply.github.com>
Co-authored-by: Yi-Hong Lyu <yilyu@microsoft.com>
Co-authored-by: Yufeng Li <liyufeng1987@gmail.com>
Co-authored-by: Guoyu Wang <62914304+gwang-msft@users.noreply.github.com>
Co-authored-by: gwang0000 <62914304+gwang0000@users.noreply.github.com>
Co-authored-by: Sunghoon <35605090+hanbitmyths@users.noreply.github.com>
Current training optimizer kernels include CPU headers
that affects changes that we can make in the CPU code with C++14 compiler and
other refactoring efforts. Rearrange the kernel according to the established patterns
and do not include headers that are not needed.
ARM a55 micro-architecture (with dot product instructions), similar to a53, is widely used as little cores in big.Little configurations. A55 has a narrower memory load/store hardware, where a 128b load instruction would block the pipeline for 2 whole cycles, during which no other instructions can be executed. On the other hand, a 64b load instruction can be duo issued with many other instructions.
This change adds a Symmetric QGEMM kernel for a55 micro-architecture, where we replace
ldr q4,[x1],#16
with
ldr d4,[x1],#8
ldr x11,[x1],#8
ins v4.d[1],x11
so that we can try to hide the memory load cycles behind computing cycles in the kernel.
Co-authored-by: Chen Fu <fuchen@microsoft.com>
* change BeamSearch op to support encoder decoder model
* check model_type and decoder attribute
* fix
* update comments
* warn shape inference issue with onnx v1.11 or T5
* skip parity test when tempature != 1.0
* fix build
* Update dnnl Add, Mul, Sub, Div ops to handle scalar values
Signed-off-by: George Nash <george.nash@intel.com>
* Add additional scalar support for dnnl execution provider
This will add scalar support for:
Eltwise operators: Abs, Elu, Exp, LeakyRelu, Log, Relu, Round,
Sigmoid, Softplus, Sqrt, and Tanh
Gelu operators: BiasGelu, FastGelu, and Gelu
Softmax operator
Signed-off-by: George Nash <george.nash@intel.com>
This code is valid only when -mcpu is set to utilize POWER9 technology
or above. A compatible code for POWER8 was created as well, but it
was not tuned for performance.
* 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
* Add micro-benchmark for FastGelu
* Delete the bert-base case, as it is very similar to the bert-large one.
* Add argument parsing and more user-friendly provider type assertion.
* 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.
