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41 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Wenbing Li
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ed102e9d88
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Add iOS test pipeline and a sample app. (#5298)
* Add iOS test pipeline and a sample app. * clean up the unused code. * clean up. * revert the unknown change * disable the shared library for iOS. * add open source notice text. * ignore the skipped test. * extract the common ortenv setup |
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Guoyu Wang
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3a3f26f38e
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Move ort flatbuffers helper functions and value info r/w functions into separated lib (#5276)
* Move fbs include from header to cc * add initial cmake for flatbuffers * Move most flatbuffers util to ort_flatbuffers * move code around * fix * move test/perf runner to use flatbuffer directly instead of model * minor update * Fix build break * Clean up includes and foward decl * Fix traning CI build breaks * Addressed PR comment, replaced some include with forward decls * Remove ORT_MUST_USE_RESULT temporarily |
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Wenbing Li
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de6e3fb61d
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Reduce IOS shared library size by symbol file. (#5171) | ||
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Wenbing Li
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2a456d16c0
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Enable onnxruntime iOS shared library build. (#5148) | ||
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Scott McKay
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fae5915d76
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CMake fixes/tweaks for minimal builds and MinSizeRel builds (#5112)
* Fix places where MinSizeRel wasn't having relevant flags added in the same way as Release and RelWithDebInfo Enable LTO for minimal build. Cleanups onnx_minimal.cmake to remove some things handled when LTO is enabled in CMakeLists.txt * Only enable LTO for MSVC in a minimal build |
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Scott McKay
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80ada0291f
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Improve the minimal build size on android and linux (#5086)
Fix bug where linux build fails when python is enabled and rtti is disabled Update doco for new build settings |
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Ryan Hill
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ac725b53f6
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Convert TensorRT provider into a shared library (#4721)
Lots of changes to shared library interfaces, new lighter weight design. |
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Andrews548
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62b44527e5
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Add ArmNN Execution Provider (#3714)
* Add ArmNN Execution Provider Add a new execution provider targeting Arm architecture based on ArmNN. Validated on NXP i.MX8QM CPU with ResNet50, MobileNetv2 and VGG models. reviewed-by: mike.caraman@nxp.com * Minor fixes - renamed onnxruntime_ARMNN_RELU_USECPU to onnxruntime_ARMNN_RELU_USE_CPU - fixed acl typo * remove extra includes. added exception for ArmNN in test * fix indentation * Separated the activation implementation from the cpu and fixed the blockage from the endif Co-authored-by: Andrei-Alexandru <andrei-alexandru.avram@nxp.com> |
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Paul Fultz II
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7759136610
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Add amd migraphx execution provider to onnx runtime (#2929)
* Add amd migraphx execution provider to onnx runtime * rename MiGraphX to MIGraphX * remove unnecessary changes in migraphx_execution_provider.cc * add migraphx EP to tests * add input requests of the batchnorm operator * add to support an onnx operator PRelu * update migrapx dockerfile and removed one unused line * sync submodules with mater branch * fixed a small bug * fix various bugs to run msft real models correctly * some code cleanup * fix python file format * fixed a code style issue * add default provider for migraphx execution provider Co-authored-by: Shucai Xiao <Shucai.Xiao@amd.com> |
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edelaye
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64b5f7edf6
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Initial release of Vitis-AI Execution Provider (#3771)
* Initial release of Vitis-AI Execution Provider * Add documentation, fix for onnxruntime::Model changes and use stringstream instead of file dump for model passing * - Add Vitis-AI docker file - Add online quantization flow Vitis-AI execution provider - Fix remarks * - Add fatal error build message for Vitis-AI cmake build on Windows - Fix pep8 issue in build.py - Add Vitis-AI execution provider example in docs Co-authored-by: Elliott Delaye <elliott@xilinx.com> Co-authored-by: Jorn Tuyls <jornt@xilinx.com> Co-authored-by: Jorn Tuyls <jtuyls@users.noreply.github.com> |
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gwang-msft
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a75a83b41a
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Minor android build fix (#3980) | ||
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airockchip
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edaf8a542c
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Initial PR for RKNPU execution provider (#3609)
* Initial RKNPU execution provider
* Init
* Support Ops:
Conv, Relu, Clip, LeakyRelu,
MaxPool, AveragePool, GlobalAveragePool,
Concat, Softmax, BatchNormalization, Gemm,
Add, Mul, Sub,
Reshape, Squeeze, Unsqueeze,
Flatten, Transpose,
QLinearConv, DequantizeLinear
* Add rknpu unittest
* Update BUILD.md and Add RKNPU-ExecutionProvider.md
* misc code update
* fix CLIP accuracy issue.
* fix "Error: Duplicate definition of name".
* move rknpu_ddk out of onnxruntime submodule.
* remove temporary code.
* add rknpu namespace.
* update misc of node_attr_helper
* add const & comment for onnx_converter
* add const & comment for shaper
* unify variable name
Co-authored-by: dkm <dkm@rock-chips.com>
Co-authored-by: George Wu <jywu@microsoft.com>
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Jan Scholz
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ce9acf0c21
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iOS crosscompilation under linux (#3298)
* added support for ios crosscompilation under linux * reverted cmake generator change * if --ios is added protoc can be compiled for host system * accidently reverted change to compile protoc for host system for ios if protoc exe is not set * wdata is now used * accidentally pasted CMAKE_OSX_ARCHITECTURES into CmakeLists.txt, also made bad merge on build.py previously * removed print * fixed typeo, deleted commented statements for earlier debugging * reverted accidental delete * added asmmacro.h for aarch64 asm now MlasSgemmKernel**** gets underscore added if needed no need anymote to differentiate between iOS arm64 and normal amr64 build onnxruntime.cmake: added check if iOSCross is set to properly set RPATH * removed 2 spaces * fix: logcial error fixed, now protoc gets compiled if not supplied with --path_to_protoc_exe * removed unecessarily added spaces * removed some more spaces |
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Tiago Koji Castro Shibata
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3bdb0b620a
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Fix WCOS/Win32 linking bugs (#3126)
* Fix WCOS/Win32 linking bugs * Remove unused NODEFAULTLIB flags * Avoid plain target_link_libraries signature * Avoid plain target_link_libraries signature * Fix library list escaping * Use library list instead of string * Remove duplicate link to windowsapp.lib * Remove Win32 build workarounds * Specify CMake policies before initializing language * Expose Win32 header definitions during build * Force set API family * Enable Win32 APIs in featurizer * Use MT dynamic CRT * Expose Win32 specific functions * Disable app container globally * Disable default wide functions in featurizers * Add featurizers to test include path * Workaround https://gitlab.kitware.com/cmake/cmake/issues/19428 * Revert pipeline debugging hacks * Skip /FI in CUDA sources * Default to Win32 builds * Enable WCOS when using WinML * Use generator expression to apply CMAKE_MSVC_RUNTIME_LIBRARY to C++ only |
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Ori Levari
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5e0f7412cd
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Properly handle downlevel and WCOS scenarios (#3075) | ||
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Ori Levari
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0beb75ce77
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populate file metadata for onnxruntime.dll (#2978) | ||
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smk2007
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c32cedc6c9
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Merge windowsai (winml layering) into master (#2956)
* Initial Commit * Merged PR 3985217: add onecoreuap_apiset.lib in order to avoid linking against kernel32.lib etc (#2346) add onecoreuap_apiset.lib in order to avoid linking against kernel32.lib etc and violating our OS layering requirements. We linked against onecoreuap_apiset.lib in VB so we will continue doing this, but I am still unsure why not to link against onecore instead since that is where we ship. However, since Sheil is the owner of this code we will wait to discuss with him before changing anything. * Initial changes for layering * more snipping to get core into ort * update build instructions to include --build_shared_lib (#2358) * update build instructions to include --build_shared_lib * fix line breaks * Task 23998197: add winml_lib_core into onnnxruntime.dll (#2368) * Task 23998197: add winml_lib_core into onnnxruntime.dll * PR feedback build break on perf_test * return proper error when the model path isn't found (#2391) * LearningModelSession is cleaned up to use the adapter, and parts of b… (#2382) this is a big PR. we are going to move it up to layer_dev , which is still a L3 so we are still safe to do work there agile. we are going to move this into the L3 so that ryan can start doing intergration testing. we will pause for a full code review and integration test result prior to going into the L2. >>>> raw comments from previous commits >>> * LearningModelSession is cleaned up to use the adapter, and parts of binding are. * moved everything in the winmladapter made it all nano-com using, WRL to construct objects in the ORT side. base interfaces for everythign for winml to call cleaned up a bunch of winml to use the base interfaces. * more pieces * GetData across the abi. * renamed some namepsace cleaned up OrtValue cleaned up Tensor cleaned up custom ops. everything *but* learnignmodel should be clean * make sure it's building. winml.dll is still a monolith. * model moved over. everything builds clean. step ! * weak ref comment * Layer dev paulm (#2408) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * Layer dev paulm (#2414) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * User/xianz/win ml telemetry (#2410) * add option to enable winml telemetry * add option to enable winml telemetry * clean logs while developping * clean the log of GUID * compile onnxruntime_common with winml telemetry * use option for use_telemetry * rename option winml_use_telemetry to onnxruntime_use_telemetry * little change * fixed some lifetime management. fixed the debug build. squeezenet passes using winmlrunner for CPU and GPU * Layer dev paulm (#2423) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * fixed some lifetime management. fixed the debug build. squeezenet passes using winmlrunner for CPU and GPU * PR feedback. * Layer dev paulm (#2424) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * fixed some lifetime management. fixed the debug build. squeezenet passes using winmlrunner for CPU and GPU * PR feedback. * couple of fixes and coded getmutabledata() * Layer dev paulm (#2425) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * fixed some lifetime management. fixed the debug build. squeezenet passes using winmlrunner for CPU and GPU * PR feedback. * couple of fixes and coded getmutabledata() * fixed 2 more heap corruptions * Layer dev paulm (#2426) * model moved over. everything builds clean. step ! * weak ref comment * added a wrapper for RoGetActivationFactory to hook back into winml for creating winml objects. fixes model load. * fixed some lifetime management. fixed the debug build. squeezenet passes using winmlrunner for CPU and GPU * PR feedback. * couple of fixes and coded getmutabledata() * fixed 2 more heap corruptions * Add opset and IR check when loading model (#2413) * Add opset and IR check. * Add test case for future opsets. https://github.com/microsoft/onnxruntime/issues/2371 * fixed map and sequence when passing stl types across the ABI . found a leak in nvidia driver, but skipped it. all winmlapitests pass now * Moved SessionOptions over to the abi * WinML CI (#2412) * Pass flags to build/test WinML in CI * Add initial CMake config for unit tests in WinML * Set winml_unittests standard to C++17 * Add WinML API tests and port them to googletest * Install WinML test collateral * Add LearningModelSessionAPITests ported to googletest * Fix WinML test files encoding * Add GPU tests * Add parameterized test, skip GPU tests * Enable precompiled header * Remove unused code and collateral * Remove brand images * Add dllload.cpp * Remove images not used in API tests * Add LICENSE.md to image collaterals * Add models with licenses * Remove FNS Candy tests * Add API test models * Add ModelInSubdirectory * Install collaterals post-build with copy_if_different, split common lib * fix warnings * Link to gtest_main * Register WinML TraceLogging provider on Onnxruntime.dll (#2455) * Register WinML TraceLogging provider on Onnxruntime.dll * Add ifdef to make sure trace logging provider has telemetry option when LAYERING_DONE * No need for ifdef for TraceLoggingOptionMicrosoftTelemetry * PR feedback * Move etw registration into lotus environment constructor and deresgister in lotus environment destructor * Brianma/cpuwinml (#2466) * allow building winml cpu without dml. * Brianma/breaks (#2469) * fix some more breaks * learning model doesn't need lotusEnvironment and CPU shouldn't include dmlEP headers * move dml checks out of winml and into the adapter * better error handling * Brianma/fi (#2470) * learning model doesn't need lotusEnvironment and CPU shouldn't include dmlEP headers * User/xianz/win ml telemetry (#2410) * add option to enable winml telemetry * add option to enable winml telemetry * clean logs while developping * clean the log of GUID * compile onnxruntime_common with winml telemetry * use option for use_telemetry * rename option winml_use_telemetry to onnxruntime_use_telemetry * little change * Add opset and IR check when loading model (#2413) * Add opset and IR check. * Add test case for future opsets. https://github.com/microsoft/onnxruntime/issues/2371 * WinML CI (#2412) * Pass flags to build/test WinML in CI * Add initial CMake config for unit tests in WinML * Set winml_unittests standard to C++17 * Add WinML API tests and port them to googletest * Install WinML test collateral * Add LearningModelSessionAPITests ported to googletest * Fix WinML test files encoding * Add GPU tests * Add parameterized test, skip GPU tests * Enable precompiled header * Remove unused code and collateral * Remove brand images * Add dllload.cpp * Remove images not used in API tests * Add LICENSE.md to image collaterals * Add models with licenses * Remove FNS Candy tests * Add API test models * Add ModelInSubdirectory * Install collaterals post-build with copy_if_different, split common lib * fix warnings * Link to gtest_main * fix bad merge * Checking in a staging checkpoint point so that Ryan can work with me in parrallel * build break. * Brianma/testfails (#2473) * add missing ir version to dictvectorizer-string.onnx * add missing ir version to relu.onnx * add missing ir version to zipmap*onnx * add IR version to manually generated models * remove an unnecessary ifdef dml * Brianma/windowsai fi (#2475) * update dockerfiles/README (#2336) * Make elementwise op run 4 items per thread (#2335) Description: Describe your changes. Make elementwise op run 4 items per thread unroll for loop to leverage ILP remove unnessary N==0 check inside elementwise GPU kernel Motivation and Context Why is this change required? What problem does it solve? It can improve the performance of GPU elementwise ops. ~2% performance gain on popular NLP bert model. If it fixes an open issue, please link to the issue here. * Add CUDA GatherElements kernel (#2310) * Updates * Update test * Update * Updates * nits * PR feedback * Update * Update * PR feedback * PR comments * Update * Fix build * Fix build * Nits * Fix * Layer Normalization Fusion (#2319) basic layer normalization transform * Add FastGelu Cuda Op for Gelu and Add bias fusion (#2293) * Add FastGelu cuda op * Add AddBiasGelu for experiment * Revert "Add AddBiasGelu for experiment" This reverts commit 5c1ee019858c657e6bb75887265cb85675626e5b. * Add bias * Add unit tests * update comment * update script * fix build error * update coding style * update for CR feedback Enable half2 optimization only when cuda arch >= 7.0 * move _Tanh to common.cuh * implement CPU contrib OP Attention (#2333) * Remove unused initializer from GraphProto as well as name_to_initial_tensor_ in CleanUnusedInitializers. (#2320) * Remove unused initializer from GraphProto as well as name_to_initial_tensor_ in CleanupUnusedInitializers. This means initializers that have been replaced during graph optimizations are not left in the GraphProto when we save an optimized model. * Handle edge case where a model has an unused initializer with matching graph input by also removing the graph input. * Use non-const iterators in std::find_if calls to make centos build happy. * Nuget pipeline changes (#2305) 1. refactor the pipeline, remove some duplicated code 2. Move Windows_py_GPU_Wheels job to Win-GPU-CUDA10. We'll deprecated the "Win-GPU" pool 3. Delete cpu-nocontribops-esrp-pipeline.yml and cpu-nocontribops-pipeline.yml 4. In Linux nuget jobs, run "make install" before creating the package. So that extra RPAH info will be removed * Cuda Reverse Sequence Op, maping types of same size using same template function. (#2281) * Set ElementType to String type of node metadata, instead of byte[] (#2348) * Set ElementType to String type of node metadata, instead of byte[] * Fix spacing * Introduce PrimitiveType into a Type System along with an integer constant (#2307) Improve perf by avoiding GetType<T>() calls. Introduce MLTypeCallDispatcher to switch on Input Type. Add Tensor IsType<T>() fast method. * Fix/test dim value of 0 handling in a couple of places (#2337) * Update the CUDA Where implementation broadcasting logic to handle a dim with value of 0. Add unit test Also add unit test for unary op with dim value of 0 * Exclude ngraph from Where test with 0 dim. * Openvino EP R3.1 onnxrt server (#2357) * onnxrt server with OVEP * onnxrt server with OVEP * Update Dockerfile.server.openvino * onnxrt server OVEP fix reviews * onnxrt server OVEP fix reviews * Implement cuda nonzero op. (#2056) Implement cuda nonzero op. * Direct use python numpy array's memory if already contiguous. (#2355) * Direct use python numpy array's memory if already contiguous. This could greatly improve performance for session with large input, like big image 1920x1080 fastrcnn, 30~40% speed up could be achieved. * Add test case enforce contiguous/non-contiguos numpy array as inputs. * Add helper to create output to minimize binary size. (#2365) Add ConstEigenTensorMap typedef so we don't unnecessarily const_cast the const input Tensor. * fix builds enabling onnxruntime_DEBUG_NODE_INPUTS_OUTPUTS (#2369) * fix builds enabling onnxruntime_DEBUG_NODE_INPUTS_OUTPUTS * update * Add Tracelogging for profiling (#1639) Enabled only if onnxruntime_ENABLE_INSTRUMENT is ON * test bidaf with nuphar for avx target (#2370) increase nuphar test coverage a bit * Fix a bug in TLS refcount that may destabilized CUDA CI (#2374) * update output size calculation for resize (#2366) * change how output size is calculated for resize op * add tests for ver 10 resize * Extend OneHot CPU kernel to support more types (#2311) * Extend OneHot CPU kernel to support input int64_t, depth int32_t, output float * Skip BERT before the test data fix is picked up * Fix bug with Slice. Need to pass in flattened input dimensions so the initial offset into the input is calculated correctly. (#2372) * Add opset 11 version of Split to CUDA ops (#2376) Organize the CUDA ops definitions so all the opset 10 and 11 parts are together (same setup used for CPU ops) * Layer Norm Fusion Fix (#2379) * layer norm fusion fix * Add input shape check in code and unit tests * Fuse Add + Gelu (#2360) Implement the transformer to fuse add + gelu Implement the accurate kernel * Skip layer norm transform (#2350) * skip layer normalization transformer * Another try to stabilize CUDA CI (#2383) The root cause seems to be failure in CUDA dealloc when tear down. cudaFree return code was ignored before, so should the debug check. * fix BUILD.md typo (#2375) build.py: error: argument --config: invalid choice: 'RelWithDebugInfo' (choose from 'Debug', 'MinSizeRel', 'Release', 'RelWithDebInfo') * Fixed compilation with ngraph (#2388) * Fix reuse logic in allocation planner. (#2393) * Fix reuse logic in allocation planner. * PR comments * Add helpful comments * Don't allow reuse across string tensors. * [NupharEP] Multiple optimizations (#2380) Fuse transpose into MatMul Implement Pow and constant scalar simplification Vectorize ReduceMean Improve symbolic shape inference Minor updates for better debugging in fused function name * Avoid using the default logger in the graph lib and optimizers (#2361) 1. Use the session logger if it is available. 2. Don't disable warning 4100 globally. We should fix the warnings instead of disabling it. * Change CUDA implementation of Transpose to support all fixed size tensor types (#2387) * Change CUDA implementation of Transpose to not use a typed kernel so we can support more types with minimum binary size. Add support for 8, 16, 32 and 64 bit types. Add unit tests. Add method so the implementation can be called directly (will be used by CUDA Scan very soon). * Disable TensorRT for MLFloat16 and int8 unit tests. * Address PR comment and add support for calling cublas implementation if type is mlfloat16. * Add opset 11 versions of the existing CUDA operators that had negative axis support explicitly added. (#2398) * Add opset 11 versions of the existing CUDA operators that had negative axis support explicitly added. * [NupharEP] force some low/zero cost ops to be inlined (#2409) * fix cross compile bug (#2415) * Minor optimization: if a node has already been placed, there's no need to find a kernel for it. (#2417) * Add Reshape Fusion (#2395) * Add reshape fusion * Add some comments * update comments * update comment format * update according to feedback * update for recent logger change * fix build error * (1) Support both input and output edges in find path in graphutils (2) Add a test case of only one constant initializer of Concat input. (3) Refactor ReshapeFusion class to allow add more subgraph fusion in the future. * fix error * (1) loose constraint on initializer: non constant is allowed for reshape fusion. (2) Change versions type to vector. (3) Add logging. (4) Return false when multiple output edges matched in FindPath. Add comments. * only allow one direction (input or output) in FindPath * [NupharEP] Update notebook and docker image (#2416) Add BERT squad in Nuphar tutorial Enhance speed comparsion readability * Fix the issue in matmul_add_fusion (#2407) Fix the issue in matmul_add_fusion If Muatmul + Add has shape [K] * [K, N], reset it to [1, K] * [K, N] will make the output shape to [1, N] will also requires a reshape on the output. Fix: just remove the shape reset to not fuse it. Add a negative test case for matmul+add fusion * feat(treeregressor): Update TreeEnsembleRegressor for type support (#2389) Updates the `TreeEnsembleRegressor` to allow for `double`, `float`, `int64`, and `int32` inputs to match the upstream specification. Signed-off-by: Nick Groszewski <nicholas.groszewski@capitalone.com> * onnxrt server documentation update (#2396) * Added support for Pad-2 operator in OpenVINO-EP (#2405) * Add CUDA If operator. (#2377) * Add CUDA If operator. Uses CPU operator for implementation. By adding a CUDA version the inputs/outputs (with the exception of the 'cond' input) stay on GPU, and no other logic is required to avoid a copy to CPU across the control flow node. * Improved documentation for onnxruntime::utils::SwapByteOrderCopy(), added precondition check. * Fix the type constraints on CUDA If operator to exclude strings. (#2431) * add Im2col<uint8_t> (#2438) * Adjust codegen vectorization width from target (#2439) * Adjust codegen vectorization width from target * Add CUDA Scan operator. (#2403) * Add Scan CUDA op. Uses CPU implementation for logic. Added some device specific functors for handling when data needs to be manipulated on a different device. Added ability to override the materialization logic in the OrtValue slicer so DML can plugin their handling. * Fix Windows GPU C API packaging pipeline failure (#2440) Fix Windows GPU C API packaging pipeline failure (#2440) * Correctly handle implicit inputs for fused nodes (#2390) * Correctly handle implicit inputs for fused nodes Previously, nuphar's partitioning function didn't include node's implicit inputs into the inputs list of MetaDef, and hence a crash was triggered in the onnx graph checker. This commit fixed the issue. Furthermore, it also fixed a related issue where we didn't add implicit inputs into graph_inputs_excluding_initializers_ in Graph::SetGraphInputsOutputs. the issue was that graph_inputs_including_initializers_ populated by SetInputs (e.g. called by FunctionImpl::FunctionImpl) may contain implicit inputs which were not of any node's initializers in the graph. Because they were not part of any initializers, these implicit inputs couldn't be visited by going through all nodes' inputs. Consequently, they would *not* be added into graph_inputs_excluding_initializers_. We fixed the issue by first copying the populated graph_inputs_including_initializers_ into graph_inputs_excluding_initalizers_, which then had both initializers and non-initializers as its initial content. Later, we erase initializers from the list. In this way, we can ensure all implicit inputs to remain in graph_inputs_excluding_initializers_. * refined comments and fixed duplicates Address CR by revisiting comments in terms of implicit inputs Also fixed an issue by skipping duplicates while copying inputs from graph_inputs_including_initializers_. * address CR explain why we need to collect nodes' implicit inputs * don't rely on pointer values for iterating std::set Previously, openvino relied on iterating a set of NodeArg pointers to construct inputs and outputs for a fused graph. It could cause non-determinism. The reason was that although iterating std::set by itself is stable, pointer values of NodeArgs may vary. Consequently, we could end up visiting the set's elements in different orders for different runs for the same test, which resulted in constructing inputs (and outputs) with different orders to the fused graph. For example, for the same test, we may have inputs [A, B] in some runs but inputs[B, A] in others. Let's use std::string as the key type to avoid such nondeterminism. This commit also added implicit inputs into meta->inputs while returning the capability from the openvino provider. * Fixed another latent issue in openvino's GetCapability function The issue was that we couldn't simply erase fused_inputs and fused_outputs while iterating the nodes. For example, an output NodeArg may have multiple uses, and it's wrong if we erase it from fused_outputs when we encounter only one of its uses as input. * Remove DeviceAllocatorRegistry class (#2451) Remove DeviceAllocatorRegistry class * CSharp api and test for loading custom op shared library (#2420) - Added C-API test for loading custom op shared lib. - Made some changes in C++ api header and C-api implementation to get it working. - Added C# API and corresponding test for loading custom op shared library. * Parallel Gelu with ParallelFor (#2399) Parallel Gelu to get better performance for Gelu * Clean up build.py (#2446) * Pull the latest image before running docker build * Fuse SkipLayerNorm with Bias (#2453) Fuse SkipLayerNorm with Bias * Allow more than one invocation of CreateEnv in the same process. (#2467) * Allow more than one invocation of CreateEnv in the same process. * Fix centos build * Symbolic shape inference improvements: (#2460) * Symbolic shape inference improvements: - add a mode to guess unknown ops' output rank - add support for GatherND - add support for If - fix a bug in get_int_values when then tensor rank > 1D, by treating it as no sympy data - add symbol to literal merge when ONNX silently merges dims - fix a bug in Concat when input dim is 0 - fix a bug in ConstantOfShape that computed dim is not updated - add support for dynamic shape in ConstantOfShape - fix a bug in Loop output shape that loop iterator dim is not inserted at dim 0 - add support for dynamic padding in Pad - add support for dynamic shape in Reshape - add support for Resize with opset > 10, by treating output dims as dynamic - fix a bug in Slice when starts/ends are dynamic - restrict input model to opset 7 and above - make output model optional to avoid disk write when testing Run model tests for symbolic shape inference Reduce 2GB docker image size of nuphar * add additional test data set for nuget pipeline (#2448) * add SAS token to download internal test data for nuget pipeline * update azure endpoint * fix keyvault download step * fix variable declaration for secret group * fix indentation * fix yaml syntax for variables * fix setting secrets for script * fix env synctax * Fix macos pipeline * attempt to add secrets to windows download data * fix mac and win data download * fix windows data download * update test data set url and location * Revert "Brianma/windowsai fi (#2475)" This reverts commit |
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Changming Sun
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7ff5c0e5a3
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CMake changes (#2961)
1. Add support for vstest. 2. Add support for vcpkg. To use it: ```bat vcpkg install zlib:x64-windows benchmark:x64-windows gtest:x64-windows protobuf:x64-windows pybind11:x64-windows re2:x64-windows mkdir build cmake ..\cmake -DCMAKE_BUILD_TYPE=Debug -A x64 -T host=x64 -DCMAKE_TOOLCHAIN_FILE=C:\vcpkg\scripts\buildsystems\vcpkg.cmake -DVCPKG_TARGET_TRIPLET=x64-windows -Donnxruntime_PREFER_SYSTEM_LIB=ON ``` 3. New cmake option: onnxruntime_PREFER_SYSTEM_LIB, which allows user using the preinstall libs instead of the things in onnxruntime submodule. 4. New cmake option: onnxruntime_ENABLE_MEMLEAK_CHECKER, which allows user turn on/off the memory leak checker by @RyanUnderhill in Windows Debug Build. The checker doesn't work with vstest. 4. Fix the post merge pipeline(Mainly for test coverage report). 5. Ignore the compile warning from the Featurizer library code 6. Apply "/utf-8" VC compile flag to our code. Without this, you can't build onnxruntime on Chinese Windows. 7. Remove the SingleUnitTestProject cmake option because it's deprecated more than one year and nobody is using it. 8. Move opaque api tests to onnxruntime_test_all 9. Enable "/W4" on CUDA ep's C++ code(Not the *.cu files), and fix some warnings, add some extra checks. 10. Delete the onnxruntime::test::TestEnvironment class. 11. Add a DLLmain for onnxruntime.dll. 12. Allow dynamic link to libprotobuf |
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James Yuzawa
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49ce4891bc | Add noexecstack linker flag | ||
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Sreekanth Yalachigere
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31ea11a696 |
Renaming MKL-DNN as DNNL (#2515)
* DNNL: Moving Files to rename file names * DNNL name change * azure pipeline updated * disable ceil/dialation and enable Opset10 * disable ceil/dialation tests in Python * mlperf_ssd_resnet34_1200 disabled |
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mikecaraman
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358b517d49 |
[v2] Add ACL (Arm Compute Library) execution provider (#2258)
* Guard unused parameter Guard unused parameter for Linux Arm and other cases. * Add ACL (Arm Compute Library) execution provider Add a new execution provider targeting Arm architecture based on Arm Compute Library. Validated on NXP i.MX8QM CPU with ResNet50, MobileNetv2 and VGG models. All unit tests are passing. Comparative performance improvements for ResNet50v1 model obtained with onnxruntime_perf_test: A72 2xA72 A53 4xA53 ACL vs CPU 16% 9% 21% 13% Usage documentation available in ACL-ExecutionProvider. * Fix eigen unused parameter Fix eigen unused parameter error for Arm cross-compilation. |
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Adrian Tsai
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4090d0d0de
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Add DirectML Execution Provider (#2057)
This change adds a new execution provider powered by [DirectML](https://aka.ms/DirectML). DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning on Windows. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers. The DirectML execution provider is capable of greatly improving evaluation time of models using commodity GPU hardware, without sacrificing broad hardware support or requiring vendor-specific extensions to be installed. **Note** that the DML EP code was moved verbatim from the existing WindowsAI project, which is why it doesn't yet conform to the onnxruntime coding style. This is something that can be fixed later; we would like to keep formatting/whitespace changes to a minimum for the time being to make it easier to port fixes from WindowsAI to ORT during this transition. Summary of changes: * Initial commit of DML EP files under onnxruntime/core/providers/dml * Add cmake entries for building the DML EP and for pulling down the DirectML redist using nuget * Add a submodule dependency on the Windows Implementation Library (WIL) * Add docs under docs/execution_providers/DirectML-ExecutionProvider.md * Add support for DML EP to provider tests and perf tests * Add support for DML EP to fns_candy_style_transfer sample * Add entries to the C ABI for instantiating the DML EP |
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Dmitri Smirnov
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d1b1cdc5c4
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Replace GSL with GSL-LITE submodule and fix up refs (#1920)
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 |
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KeDengMS
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c9240f4e93
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Implementation of Nuphar execution provider (#881)
* Implement Nuphar execution provider Nuphar execution provider is a TVM-based compilation provider. It has shown great speedups for RNN models using Scan. This PR is mainly for a preview of the shared codegen library for other TVM-based providers. * Fix submodules * Fix TVM submodule * Update Nuphar to latest and resolve confliction * Remove stale files caused by merge -X theirs * Revert heap buffer change to not introduce onnxruntime_framework into onnxruntime_perf_test * Fix bad merge * Merge from Nuphar * Fix warning treated as error, revert some unnecessary changes * Revert some more test changes * Some more test revert or comments to make review easier New tests could be added later * One more revert of unnecessary changes * More change revert. Test could be added back later. |
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Changming Sun
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7be5695fad
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Remove --whole-archive (#1655) | ||
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Ke Zhang
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3bf0e364e2
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Move CopyTensor out of IExecutionProvider interface. (#1268)
* add ortdevice class * add data transfer manager for copying tensors. * update * add data trasnfer for gpu * fix constexpr build break. * update * remove unnecessary header files. * remove unnecessary header files. * add dependency * add dependency * add dependency * add dependency * fix linux build break. * update * fix build break * fix build break * fix build break * update * update * update c api. * update to not use OrtCreateAllocatorInfo * change to all eps . * fix linux build break * remove useless codes. * update * move datatransfermanager in session state * update * fix cuda build break. * fix comments * fix windows GPU build. * fix comments * fix build break * fix comments * fix test failure * update * fix comments * fix onnx runtime server. * update * fix test failure. * fix comments * fix comment |
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daquexian
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c65489a47f |
Initial PR for NNAPI execution provider (#1220)
* init * Update DNNLibrary * Update DNNLibrary, set compiler flags, it compiles now * Add more missing flags, add test * Update DNNLibrary * Update Compile method, fix allocator and some other bugs * Update DNNLibrary * Implement CopyTensor * Not delete state explicitly since it is managed by unique_ptr * Add the missing files when SingleUnitTestProjct is ON * misc changes * Fix wrong name in provider factory * Add my own test * Update the code of add node into graph, and add the missing initializer into graph * Fix the bug that re-build the graph produces extra output * Update DNNLibrary * Transpose nchw (ONNX) -> nhwc (NNAPI) * Add license * Add GetSupportedNodes method (implement it later) * Rename onnxruntime_nnapi_test->onnxruntime_nnapi_squeezenet_test * Update squeezenet_test.cpp after rebase master * Remove squeezenet_test.cpp since it is almost same with the c++ sample * Update DNNLibrary for GetSupportedNodes * Update GetSupportedNodes * Revert "Remove squeezenet_test.cpp since it is almost same with the c++ sample" This reverts commit a97575fd9ff49e50ba1dc8d8154790d8cd86c48d. * Update DNNLibrary * Fix multiple outputs bug * Remove GetKernelRegistry * Revert "Revert "Remove squeezenet_test.cpp since it is almost same with the c++ sample"" This reverts commit 2a0670e9cbf10ea654111ce39e198a4be0ddd838. * Set default memory type of NNAPI EP * Add CPUOutput allocator * Update DNNLibrary for multiple outputs * Fix bug of nhwc->nchw * Remove GetExecutionHandle() |
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Changming Sun
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766c6b6163
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Add an API for retrieve ORT version (#1263)
* Add an API for retrieve ORT version |
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S. Manohar Karlapalem
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8d15ffd8f5 |
Initial commit for OpenVINO Execution Provider (#935)
* 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> |
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RandySheriffH
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cdb27de090
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implement python opeartor (#1045)
* implement python opeartor * format code * remove dup * limit type * format code * cancel default logging func * add comment * fix compile err * fix comments * switch to c++ style cast * implement interop framework * fix format * move includes * cancel needless linking * fix comment * add UT * exclude def |
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Changming Sun
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7bce377113
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Fix LTO build failure on ubuntu (#1048)
* Fix LTO build failure on ubuntu |
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nivas-x86
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a4d7052aeb |
Add nGraph Execution Provider (#832)
* Add nGraph Execution Provider * feedback changes 1 * feedback2 * Feedback and upgrade nGraph * Feedback 4 * Fix CI * Disable new ops |
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Pranav Sharma
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780aad8fd0 | Eliminate unused code and data from Linux binaries. (#849) | ||
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Changming Sun
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43521c0de7 | update | ||
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stevenlix
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e8b0ae8923
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Trt execution provider (#382)
* updated cmake files for trt * added trt execution provider * added trt basic test * removed trt_path action attribute * Add files via upload * Update build.py * Update trt_allocator.h * fixed issues found by reviewers * changed cast operator * added comment for custom kernel implementation * changed auto to auto& * changed to function compile APIs for TRT execution provider * changed to function compile APIs for TRT execution provider * added new DType DInt64 * adapted to the changes of onnxruntime_c_api * removed trt kernel (use function compile instead) * updated onnx-tensorrt submodule * set default memory type to TRT fused kernel * resolve merge conflict * fixed the issue that USE_CUDA conflicts with USE_TRT * construct graph by adding nodes in topological order * made changes for Windows * change buffers type * bypass HasImplementationOf check for TRT XP because TRT kernel is not registered * added domain to version info in rebuilt model proto * added trt to test option list * added DomainToVersionMap() to GraphViewer * removed Copy() * fixed broken code * format the code to clang format * used local reference to the frequently used values * fixed a couple of issues according to reviewers feedback * fixed a couple of issues according to reviewers feedback * added python binding for TRT and enable use_cuda when use_trt is on * fixed a redefinition issue * changed shared_ptr to unique_ptr on trt engines, and made a few changes required by reviewers * enabled trtexecution provider for unit tests * renamed trt to tensorrt * added tesorrt to python binding * update submodule onnx and onnx-tensorrt * made a couple of minor changes based on reviewer's feedback * added CUDA_CHECK * removed test code * fixed broken code after merge * updated onnx-tensorrt submodule * added post processing to align trt inputs/outputs with graph inputs/outputs * updated onnx submodule * added CUDA fallback for TensorRT and fixed TensorRT cmake issue * added ci pipeline for tensorrt and removed some redundent code from trt xp * fixed syntax issue * updated onnx-tensorrt submodule * fix trt build problem by: (#602) 1. Add additional /wd for debug build 2. Add io.h for additional targets 3. Bring back mb version of getopt * Update install_ubuntu.sh * Update linux-gpu-tensorrt-ci-pipeline.yml * Update linux-gpu-tensorrt-ci-pipeline.yml * Update run_build.sh * Update run_build.sh * Update run_build.sh * Update run_build.sh * fixed the issue that GetKernelRegistry returns nullptr * merged master to this branch * moved some data types to private * fixed tensorrt CI pipeline issue * customized test data for TensorRT pipeline * added onnx-tensorrt in json file and fixed an issue in ci script * added comments |
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shahasad
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8a8d1b0cea
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Fix MacOS shared library build (#447)
* try removing the --version-script * remove --no-undefined flag * remove the -rpath linker flag * remove the -rpath linker flag, including the -Wl * remove the --whole-archive flags * added -all_load -noall_load flags in place of --whole-archive and --no-whole-archive * spell correct all-load * set the MacOS specific cmake configs with if(APPLE) condition * added --build_shared_lib to mac CI |
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Weixing Zhang
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696ab8a194
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Create a separate component for graph optimization. (#421)
* Create a project for graph optimizer. Move optimizer related code to the folder optimizer. * Fix build failures. * rebase and fix build failures. * fix build failure. * fix build failure with cuda path. * fix python build failure. * Move two transformers(memcpy and insert_cast) from framework to optimizer. * rebase. * SessionState should not depend on optimizer. |
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jignparm
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ccca1e9402
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Update property file for Nuget Linux package (#369)
* Copy mkldnn to output folder for linux. Nuget doesn't resolve dll dependency correctly within a package * Modify to copy all dlls to output folder * update rpath for shared library * Simplified linker flags for RPATH * Removing copying of dlls to output folder, since setting RPATH works fine now |
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Changming Sun
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5e113661a9 |
Build system upgrades (#281)
* update * runas normal user |
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Pranav Sharma
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7aef8a1cca | Sync with internal master. | ||
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Pranav Sharma
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89618e8f1e | Initial bootstrap commit. |