* fix aten view op
* add test case
* fix signature
* fix the build
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
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.
* Add Reduce Ops to DNNL ep
Combine the Reduction ops into one class
Add ReduceL1, ReduceL2, ReduceSum, ReduceMax, ReduceMin, and ReduceProd,
ReduceSumSquare, ReduceLogSum, and ReduceLogSumExp
Reduce code now also handles the keepdims attribute
Also updated code to use HandleNegativeAxis function from
the providers/common.h code instead of manually calculating.
In code documentation exists to help explain complex reduction op code
Add elementwise ops to Reduction op capability code removed keepdims check
from the Reduction op capability code.
Updated the error_tolerance for LogGrad(DNNL EP only) after finding a few
instances that the tests were a little out of tolerance.
Signed-off-by: George Nash <george.nash@intel.com>
* Documentation cleanup in dnnl_qattention
Cleaned up the Comments documenting the QAttention operator
For some reason a bunch of new lines were introduced to the
comment making it harder to read.
Signed-off-by: George Nash <george.nash@intel.com>
* Add AtenOp at:bitwise_or
* Specify overload name for bitwise_or
* undo unnecessary import
* set output element type to BOOL
* Add broadcasting support
* Fix test
Co-authored-by: Gani Nazirov <ganaziro@OrtTrainingDev4.af05slrtruoetgaxwwjv5nsq5e.px.internal.cloudapp.net>
Co-authored-by: Gani Nazirov <ganaziro@microsoft.com>
* adding view operator changes
* adding the slice operator definition
* moving to opgen script for slice op and removing redundant steps in view op and reshape_copy
* adding for at definition
* adding for at::infer_size definition
* changing template style for reshape_copy to ensure int64_t type
* 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
* convert between aten ort tensor and ortvalue
* register the EP to ortmodule using ort device information
* remove duplicated test
* remove useless dependency
* handle half precision type for ortmodule outputs
* adjust the tensor conversion python code
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Potential comparison of a constant with another constant.
at D:\a\_work\1\s\orttraining\orttraining\training_ops\cuda\reduction\\reduction_all.cu@97,42
Co-authored-by: Weixing Zhang <wezhan@microsoft.com>
* 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>
* fix reshape implementation in eager mode
* test code
* update opgen script to support fallback to cpu
* enhance the eager backend to support torch cpu fallback
* add more testes
* disable the printensor test for now, as we need to erge a PR to pytorch first
* register custom symbolic for einsum
* bugfix for case needs permute at the end
* refactor
* refactor equation parser
* support new case, use ReduceProd
* optimize perf and graph
* remove some Gather node
* add more ut, fix gemm trans fusion
When the pattern Sum(Gemm(A, B), C) exists, we can convert it to
Gemm(A, B, C), assuming that C the output of the original Gemm is
not used elsewhere, and this change does not break broadcasting.
* remove default python ep registration. raise exception if providers are not explicitly set if there are available providers
* temporarily disable exception
* fix python tests
* explicitly set CUDAProvider for python iobinding tests
* explicitly set providers param for InferenceSession())
* onnxrt
* raise ValueError if not explicitly set providers when creating InferenceSession
* add required providers param
* explicitly set providers
* typo
Add support for saving graph runtime optimizations in an ORT format model. The idea is to allow some optimizations to be "replayed" at runtime in a minimal build. The replaying part will be in a future change.
* Add source for conv_grad
* Add sources for ROCm EP.
* Transliterate sources for conv_grad for ROCm EP.
* Add conv_grad to ROCm EP
Add conv_grad to ROCm execution
provider.
* Update ROCm EP ConvGrad
Update ConvGrad for the ROCm EP to match other EP
changes and fix a build issue.
