Add transformer glue test example to show how to use ORTTrainer to fine-tune a transformer model
Co-authored-by: liqun <liqun@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
* Pad: Add support for all datatypes in opset-11 spec
Pad opset-11 implementation supports:
int32, int64, float & double
Per specification, Pad opset-11 also supports:
uint8, uint16, uint32, uint64, int8, int16 & float16
This commit add support for those types to get full coverage of Pad opset-11 operator.
* Pad: Remove 16-bit datatypes support
These types are unused at the moment and binary size is impacted. Remove support for those type to lower binary size.
Clean up a CUDAExecutionProvider's associated PerThreadContext instances when that CUDAExecutionProvider is destroyed.
Revert workaround (introduced in #3767) to lazily initialize CUDA handles to avoid segmentation fault. For that case, the CUDA handle cleanup was happening quite a bit later than the CUDAExecutionProvider destructor. This should be a cleaner way to fix that.
* online partition
* fix when multiple consumer nodes is in cut info
* fix windows build
* address feedback
* adding test
* feedback
* address feedback
* add parser for cut edge
* windows build
* 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>
* Optimize for OneHot with zero off value.
* Add test cases for indices out of range.
Co-authored-by: Vincent Wang <weicwang@microsoft.com>
Co-authored-by: Vincent Wang <weicwang@OrtDevTest2v100.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
In this PR, we
1. create some APIs for creating NVTX objects
2. apply those APIs in pipeline-related operators and sequential executor.
As a result, we can explicitly see how a pipeline schedule is run by GPUs in
Nvidia's visual profiler. Note that these APIs are Linux only due to Nvidia's
limited support.
* Remove 'model_.' prefix for onnx model initializers in training
* fix test case remove redundant device test
* rename
* Fix state_dict/load_state_dict with frozen_weight
* nit
* Add monkey patch for pt opset 10
* remove pt patch in CI
* nit: newline
onnxruntime init failure due to wrong path of reading native libraries. In OS X 64 system, the arch name is detected as x86 which generates invalid path to read native libraries.
Exception java.lang.UnsatisfiedLinkError: no onnxruntime in java.library.path
at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1867)
at java.lang.Runtime.loadLibrary0(Runtime.java:870)
at java.lang.System.loadLibrary(System.java:1122)
at ai.onnxruntime.OnnxRuntime.load(OnnxRuntime.java:174)
at ai.onnxruntime.OnnxRuntime.init(OnnxRuntime.java:81)
at ai.onnxruntime.OrtEnvironment.<clinit>(OrtEnvironment.java:24)
Change training perf test build to use "docker" instead of "sudo docker". The training perf test build runs in an environment that supports calling "docker" and not "sudo docker".
* gpt2 training perf
* gpt2 training perf
* debug
* debug
* debug
* fix bug
* minor
* on comments
* dynamic sql
* fix build
* minor
* linked hash
* on comments
* minor
* mem
* minor
Co-authored-by: Ethan Tao <ettao@microsoft.com>
* Initial update of readme
* Readme updates
* Review of consolidated README (#3930)
* Proposed updates for readme (#3953)
I found some of the information was duplicated within the doc, so attempted to streamline
* Fix links
* More updates
- fix build instructions
- nodejs doc reorganization
- roadmap update
- version fixes
* Update ORT Server build instructions
* More doc cleanup
* fix python dev notes name
* Update nodejs and some links
* sync eigen version back to master
* Minor fixes
* add nodsjs to sample table of content
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* Update README.md
* address PR feedback
* address PR feedback
* nodejs build instruction
* Update Java instructions to include gradle
* Roadmap refresh
Reformat some data, fix link, minor rewording
* Clarify Visual C++ runtime req
Co-authored-by: Nat Kershaw (MSFT) <nakersha@microsoft.com>
Co-authored-by: Prasanth Pulavarthi <prasantp@microsoft.com>
Co-authored-by: manashgoswami <magoswam@microsoft.com>
Update Android build instructions to provide more information.
Add info on testing directly on Android
Update build.py to better support using Ninja generator to build Android on Windows.
Update install_deps.sh to use relative path from script directory to symbolic_opset10.py. This allows install_deps.sh to be called from different working directories.
* [java] - adding a cuda enabled test.
* Adding --build_java to the windows gpu ci pipeline.
* Removing a stray line from the unit tests that always enabled CUDA for Java.
If a symbolic dimension is found allow the user to provide a value, or default to 1.
`python .\onnxruntime_test.py --symbolic_dims batch=1,seqlen=4 onnxruntime\test\testdata\transform\fusion\fast_gelu_use_graph_input.onnx`
Disable ORT in offline optimization script (ORT could generate some fused ops (like FusedGemm) which cannot be converted to fp16).
Remove some models from benchmark until we have optimizations for them.
