* Add disentangled attention TRT plugin as contrib op
* update plugin name & remove null character
* update onnx-tensorrt submodule with my beta version
* use suggested plugin name & simpler shape propagation
* update onnx-tensorrt gitsubmodule to temporary fork
* update onnx-tensorrt to temporary commit
* redirect submodule back to latest 8.2-GA release of onnx-tensorrt repo
Co-authored-by: HHH-ComputeLab <haohangh@nvidia.com>
* use the lightweight compile api as default; use dnnl ep for testing
* apply to tensorrt ep
* fix the missing files
* fix build
* fix the copy issue on linux
* migrate migraphx and openvino ep
* fix openvino build break
* fix linux build
* fix unused parameter
* fix coreml build
* use graph view's filtered initializers
* fix openvino break
* fix tvm compile api
* fix tvm / rknpu / vitisai ep build
* add IsInitializedTensor in graph_viewer; fix nuphar build
* use serializer directly as tvm ep is still static lib
* fix the type mismatch
* fix the type mismatch
* fix merge conflict
* add a comment
* fix minimal build
* fix the DML EP's legacy approach
* save type/shape in dnnl IR
* fix linux break
* fix tvm failure
* dnnl ep: move initializer referenced out of dnnl subgraph
* Revert "add IsInitializedTensor in graph_viewer; fix nuphar build"
This reverts commit 1cc3c7f08c16fee4fe3309a67209eb769d479587.
* add IsInitializedTensor to graph viewer
* add the legacy code for nuphar build to temporarily make nuphar build work
* ignore internal test for nuphar
* remove the out of date tests
* keep the legacy API in EP for a while
* turn serializer into a static function
* update comments
* fix tvm build
* Update include/onnxruntime/core/framework/execution_provider.h
Co-authored-by: Pranav Sharma <prs@microsoft.com>
* Update include/onnxruntime/core/framework/execution_provider.h
Co-authored-by: Pranav Sharma <prs@microsoft.com>
* Update onnxruntime/core/framework/execution_provider.cc
Co-authored-by: Pranav Sharma <prs@microsoft.com>
* updatee comments; add warning message for legacy compil call
* add a flag to control out of scope arg in serialization
* fix trt build; improve the test
* resolve merege errors
* fix a typo
Co-authored-by: Cheng Tang <chenta@microsoft.com>
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Pranav Sharma <prs@microsoft.com>
* update TVM
* small fixes
* update TVM with new set_input and NDArray API
* use set_input instead of set_one_input
Co-authored-by: Valery Chernov <valery.chernov@deelvin.com>
Description:
Add the extra param to match gelu in PyTorch in the contrib symbolic function
Motivation and Context
Why is this change required? What problem does it solve?
The symbolic function in /onnxruntime/python/tools/pytorch_export_contrib_ops.py is missing a recently added parameter approximate. We add this parameter and use the exporter defined gelu if approximate is "tanh".
* support ort device tensor in ort module inference
* fallback aten equal to cpu; add ortmodule inference test case
* fix python format
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
* draft kernel creation
* setup eager context
* call into kernel in eager mode
* redefine test case
* refact eager context
* add comment
* remove header
* rename argument
* redefine API definition with types
* list outputs as argument
* switch to int to represent length
* fix compile err
* create attribute API
* add test case for topk
* remove bool from c api
* add gru test case
* remove var
* fix compile warnings
* rename status
* fix compile err
* exclude sparse tensor
* fix comments
* fix comments
* fix build err
* rename file and move location
* format code
* move file to session folder
* fix comments
Co-authored-by: Randy <Randy@randysmac.attlocal.net>
* Move some of the tranpose kernel code to onnxruntime_framework.lib
* Fix C4244 warnings in the tranpose code
* Rename IsMovingSingleAxis to IsTransposeMovingSingleAxis
This reverts commit 4983d6e5d6. We can't destroy OrtEnv through python's atexit function, because at that time there might be many other ORT python objects alive.
* move all logic for ubuntu dockerfiles
* pass in trt version
* update trt 8.0 file
* downgrade protobuf
* uncomment
* and
* change to 8.0
* update dockerfiles
* checkout protobuf based on version
* adding last dockerfile:
:
* checkout 3.10 protobuf
* fix checkout version
* update to 8.2
* keep only one submodule sync
* cleanup
* Delete Dockerfile.custom-trt-perf
* create checkout submodules script
* properly compare decimals in bin/sh
* combine build ort paths
* deprecate TRT 7.2
* only checkout protobuf if we checkout older onnx-tensorrt
* only pull nvidia container if true, update image
* downgrade protobuf only if we checkout onnx-trt
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* Update linux-gpu-tensorrt-daily-perf-pipeline.yml for Azure Pipelines
* Add quotes to avoid path splitting
* address shellcheck
* use shellcheck suggestions
* Create new pipeline to sign ov ep binaries
* make codesign available
* make codesign available
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* add codesign task
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* Update sign_ov_ep_binaries.yml for Azure Pipelines
* windows
* reduce timeout to 15 minutes
* initial fix
* refactor the function handle
* update the implementation
* fix linux build break
* fix training build
* fix minmal build
* fix gradient checker
* deprecate the local function members in graph. host it in model
* fix changming's comments
* fix comments about inlined containers
* fix a missed inlined container
* fix training build
* avoid const for std string_view
Co-authored-by: Cheng Tang <chenta@microsoft.com>
Fix the order of onnx and onnxruntime imports. Importing onnx before onnxruntime causes a dependency issue in the tensorrt containers that prevents onnxruntime_pybind11_state.so from finding the system libstdc++. This is a workaround to get the EP Perf pipeline working until we can investigate the issue more closely.
Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
* add aten export for max, max.dim
* rewrite grad of max (no dim); add cases for min
* update UT cases
* mod sym shape infer
* resolve comments: shape infer, add comments, etc.
* add test for torch.max of two tensors
* resolve peng's comments: keepdim; test case
* correct python format
* fix recently introduced lint error
* Specify list/map capacity when initializing where possible
- This really depends on the use case, but in some cases the array/map resizing can be slightly costly, there is effectively no downside setting the initial capacity for a collection if we know for sure its final size
* Supply list/map capacity when initializing where possible
- This really depends on the use case, but in some cases the array/map resizing can be slightly costly, there is effectively no downside setting the initial capacity for a collection if we know for sure its final size
- Introduce an extra utility to help creating maps with expected capacity
* Move utility function to OrtUtil and drop MapUtil, also add Java doc to method
* Move test to the right class
Description: Set black's target version to be py37 - py310
Motivation and Context
Black by default targets its format for py3.10. Since our project supports python 3.7, we need to target version to all the python versions supported.
Re-ran black. 13 files reformatted.
* Add stub implementation of the NNAPI interface so that model builder code can be unit tested on all platforms.
Needed to fix a lot of type mismatch warnings. As these don't occur on Android builds used static_cast for simplicity.
