- Fix flatbuffers flatc warning, unused-but-set-variable.
- Address `-Wshorten-64-to-32` warnings (fix in our code, allow in dependencies' code).
- Update CI builds to use Xcode 14.3.
- Update minimum iOS version to 12.0.
- Update Mac hosted agents to MacOS 13 where possible.
### Description
DML_PACKAGE_DIR cmake variable is not getting set properly when dml_path
build options is used.
### Motivation and Context
- Why is this change required? What problem does it solve?
It is required for DML Perf dashboard.
<!--- If it fixes an open issue, please link to the issue here. -->
### Description
Remove the "onnxruntime_BUILD_WEBASSEMBLY" cmake option. Use `if
(CMAKE_SYSTEM_NAME STREQUAL "Emscripten")` instead. It makes some code
look more nature.
For example,
```cmake
if (CMAKE_SYSTEM_NAME STREQUAL "iOS" OR CMAKE_SYSTEM_NAME STREQUAL "Android" OR onnxruntime_BUILD_WEBASSEMBLY)
```
becomes
```cmake
if (CMAKE_SYSTEM_NAME STREQUAL "iOS" OR CMAKE_SYSTEM_NAME STREQUAL "Android" OR CMAKE_SYSTEM_NAME STREQUAL "Emscripten")
```
### Description
Revert a change in #15797: restore the correct version of emsdk
### Motivation and Context
Without change, when you build it on Windows you will see:
```
2023-05-17 19:41:30,093 build [INFO] - Activating emsdk...
2023-05-17 19:41:30,093 util.run [INFO] - Running subprocess in 'C:\src\onnxruntime2\cmake\external\emsdk'
'C:\src\onnxruntime2\cmake\external\emsdk\emsdk.bat' activate 3.1.37
error: tool or SDK not found: '3.1.37'
```
When building the FlatBuffers dependencies, gcc13 emits a
stringop-overflow warning. All warnings being turned into errors, that
fails the compilation of FlatBuffers, and as a consequence also fails
the build of onnxruntime.
This commit adds the application of a patch to FlatBuffers's
CMakeList.txt, to add -Wno-error=stringop-overflow to the
CMAKE_CXX_FLAGS.
### Description
this is for ort 1.15 release to work with onnx 1.14
It shall be merged after onnx 1.14 release and before ort 1.15 release.
### Motivation and Context
---------
Signed-off-by: Liqun Fu <liqfu@microsoft.com>
### Description
- Update DML version to 1.11.0
- Disable Gemm+Softmax fusion
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
Download protoc from Github Release instead of Nuget to avoid having
dependency on nuget.exe on Linux
### Motivation and Context
To avoid having dependency on nuget.exe on Linux. Many users' build
environment do not have nuget or dotnet.
### Description
While building ORT for DML EP with `dml_EXTERNAL_PROJECT` flag, 2
variables (`DML_SHARED_LIB`, `DML_PACKAGE_DIR`) value is not set
properly.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
Add clog back to onnxruntime_EXTERNAL_LIBRARIES.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Fix iOS packaging pipeline build failure.
### Description
Rework some external targets to ease building with
`-DFETCHCONTENT_FULLY_DISCONNECTED=ON`
This will allow package managers to more easily provide an onnxruntime
package by reducing the amount of patching needed downstream at each
version.
### Motivation and Context
Availability of onnxruntime in some C++ package managers
https://github.com/microsoft/onnxruntime/issues/7150https://github.com/conan-io/conan-center-index/issues/16699https://github.com/microsoft/vcpkg/issues/20548
My initial intent is to get this in conan but the PR would most likely
be useful (though not tested) to vcpkg as well (and maybe others).
I tried to get only a first batch of not too specific patches (i.e. not
specific to conan).
The first commit reworks `flatbuffers` and just extends what @snnn did
in https://github.com/microsoft/onnxruntime/pull/13991
The second commit reworks `pytorch_cpuinfo`
The third commit reworks `google_nsync`
### Description
1. Remove Linux jobs for ORT-Extension combined build
2. Add a macOS build job for ORT-Extension combined build
3. Adjust the yaml file so that it can support two different ADO
instances.
### Motivation and Context
To test our code better. And it will enable us to run such tests for
every commit in the main branch. It would be easier for us to figure out
which change caused a build break.
See
[AB#13435](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/13435)
### Description
<!-- Describe your changes. -->
1. upgrade cutlass to 3.0 that containing attn_bias support.
2. extend Attention/MHA to use memory efficient attention when
rel_pos_bias with [1, num_head, s, s*] and 1d mask with [2 * batch_size
+ 1] are present.
new mask format introduction:
MASK_1D_KEY_SEQ_LEN_START,
[3 * batch_size + 2] with [key_len[0], ..., key_len[batch_size - 1],
query_start[0], ..., query_start[batch_size - 1], query_end[batch_size -
1], key_start[0], ..., key_start[batch_size - 1], key_end[batch_size -
1]]
e.g
2D mask with [[1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0]] converts to this
1D mask is [3, 5, 0, 6, 12, 0, 6, 12]
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
It potentially benefits tnlrv6 and t5(encoder)
---------
Co-authored-by: Ubuntu <wy@v100-2.0cdb2e52twzevn1i4fi45bylyg.jx.internal.cloudapp.net>
Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com>
Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
### Description
This will enable a user to use a TensorRT timing cache based on #10297
to accelerate build times on a device with the same compute capability.
This will work across models as it simply store kernel runtimes for
specific configurations. Those files are usually very small (only a few
MB) which makes them very easy to ship with an application to accelerate
the build time on the user end.
### Motivation and Context
Especially for workstation use cases TRT build times can be a roadblock.
With a few model from ONNX model zoo i evaluated speedups when a timing
cache is present.
`./build/onnxruntime_perf_test -e tensorrt -I -t 5 -i
"trt_timing_cache_enable|true" <onnx_path>`
|Model | no Cache | with Cache|
| ------------- | ------------- | ------------- |
|efficientnet-lite4-11 | 34.6 s | 7.7 s|
|yolov4 | 108.62 s | 9.4 s|
To capture this is had to modify the onnxruntime_perf_test. The time is
sometimes not captured within "Session creation time cost:" which is why
i introduced "First inference time cost:".
---------
Co-authored-by: Chi Lo <Chi.Lo@microsoft.com>
### Description
<!-- Describe your changes. -->
Merging extensions from Git submodule to cmake FetchContent
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
---------
Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Jian Chen <jchen351@MacBook-Pro.local>
### Description
Update oneDNN version from 2.7 to 3.0
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
**Description**:
Support new feature of TVM Virtual Machine (method `set_outputs`) on TVM
Execution Provider side. It allows to avoid excess copying from TVM EP
output tensor to ONNX Runtime one
**Motivation and Context**
Tests with multiple output topologies and big output tensors shows that
there is overheads spent on copying from TVM EP to ONNX Runtime.
Returning output(s) on preallocated memory for VirtualMachine was
implemented on TVM side.
**Details**
`set_output_zero_copy` provider option for TVM EP switches on/off this
feature. It is true by default.
The feature works for both GraphExecutor and VirtualMachine from TVM.
---------
Co-authored-by: Valery Chernov <valery.chernov@deelvin.com>
### Description
Fix SNPE build issue caused by cmake dependency refactor
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
fix issue: https://github.com/microsoft/onnxruntime/pull/14547
### Description
upgrade protobuf to 3.20.2, same as onnx 1.13.0
### Motivation and Context
Per component governance requirement and Fixes#14060
unused-parameter error occurs in 2 conditions.
1. compile protolbuf
`onnxruntime_src/cmake/external/protobuf/src/google/protobuf/repeated_ptr_field.h:752:66:
error: unused parameter ‘prototype’ [-Werror=unused-parameter]`
2. include onnx_pb.h
```
2023-01-28T10:20:15.0410853Z FAILED: CMakeFiles/onnxruntime_pybind11_state.dir/onnxruntime_src/onnxruntime/python/onnxruntime_pybind_iobinding.cc.o
......
2023-01-28T10:20:15.0466024Z from /build/Debug/_deps/onnx-src/onnx/onnx_pb.h:51,
2023-01-28T10:20:15.0466958Z from /onnxruntime_src/include/onnxruntime/core/framework/to_tensor_proto_element_type.h:10,
....
2023-01-28T10:20:15.0609678Z /build/Debug/_deps/onnx-build/onnx/onnx-operators-ml.pb.h:1178:25: required from here
2023-01-28T10:20:15.0610895Z /onnxruntime_src/cmake/external/protobuf/src/google/protobuf/repeated_ptr_field.h:752:66: error: unused parameter ‘prototype’ [-Werror=unused-parameter]
2023-01-28T10:20:15.0611707Z cc1plus: all warnings being treated as errors
```
https://dev.azure.com/onnxruntime/2a773b67-e88b-4c7f-9fc0-87d31fea8ef2/_apis/build/builds/874605/logs/22
### Description
Updated DirectML version to 1.10.1
(https://www.nuget.org/packages/Microsoft.AI.DirectML/1.10.1)
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
Add memory efficient attention from CUTLASS.
TODO (in next pull request):
(1) Need performance tests on different GPUs, then add a sequence length
threshold (only activate it for long sequence length).
(2) Merge changes from https://github.com/NVIDIA/cutlass/pull/773 when
it is in cutlass master.
### Description
Enable creating dedicated build for on device training. With this PR we
can build a lean binary for on device training using flag
--enable_training_apis. This binary includes only the essentials like
training ops, optimizers etc and NOT features like Aten fallback,
strided tensors, gradient builders etc . This binary also removes all
the deprecated components like training::TrainingSession and OrtTrainer
etc
### Motivation and Context
This enables our partners to create a lean binary for on device
training.
### Description
<!-- Describe your changes. -->
Add GemmFastGelu CK implementation.
TODO
1. The performance of CK GemmFastGelu in ORT is not good as using CK
directly, still need to investigate the reason and improve the CK in
ORT.
`GemmFastGeluUnfused float16 NN m=49152 n=3072 k=768 2298.8064 us 100.89
tflops`
`withbias DeviceGemmMultipleD_Xdl_CShuffle<256, 256, 128, 32, 8, 8,
Default> LoopScheduler: Default, PipelineVersion: v1 float16 NN m=49152
n=3072 k=768 2401.9799 us 96.56 tflops`
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Co-authored-by: peixuanzuo <peixuanzuo@linmif39a000004.zvflicr54joexhdgnhvmxrxygg.phxx.internal.cloudapp.net>
Implement CloudEP for hybrid inferencing.
The PR introduces zero new API, customers could configure session and
run options to do inferencing with Azure [triton
endpoint.](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-with-triton?tabs=azure-cli%2Cendpoint)
Sample configuration in python be like:
```
sess_opt.add_session_config_entry('cloud.endpoint_type', 'triton');
sess_opt.add_session_config_entry('cloud.uri', 'https://cloud.com');
sess_opt.add_session_config_entry('cloud.model_name', 'detection2');
sess_opt.add_session_config_entry('cloud.model_version', '7'); // optional, default 1
sess_opt.add_session_config_entry('cloud.verbose', '1'); // optional, default '0', meaning no verbose
...
run_opt.add_run_config_entry('use_cloud', '1') # 0 for local inferencing, 1 for cloud endpoint.
run_opt.add_run_config_entry('cloud.auth_key', '...')
...
sess.run(None, {'input':input_}, run_opt)
```
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
### Description
Remove Abseil module placement specifications
### Motivation and Context
Allow Cmake defaults take place and possible redirection of all
submodules for sharing between the local builds.
### Description
Use target name for flatbuffers.
Add version range for flatbuffers. It is similar to #13870
### Motivation and Context
To fix a build error:
```
CMake Error at onnxruntime_graph.cmake:88 (add_dependencies):
The dependency target "flatbuffers" of target "onnxruntime_graph" does not
exist.
Call Stack (most recent call first):
CMakeLists.txt:1490 (include)
```
It happens when flatbuffers library is already installed. For example,
on Ubuntu people may get it from apt-get. But, the one provided by
Ubuntu 20.04 is not compatible with our code. The one in Ubuntu 22.04
works fine.
### Description
Update absl to a new version
### Motivation and Context
The new version contains fixes that are needed for Nvidia GPU build.
Once we update it to that version, we don't need to maintain our private
patches for Nvidia GPU build.
To fix a build error:
/home/xxxxxxxxxxxxx/onnxruntime/build/Linux/Debug/tensorboard/compat/proto/cost_graph.pb.cc:17:8:
error:
‘PROTOBUF_INTERNAL_EXPORT_tensorboard_2fcompat_2fproto_2ftensor_5fshape_2eproto’
does not name a type
17 | extern
PROTOBUF_INTERNAL_EXPORT_tensorboard_2fcompat_2fproto_2ftensor_5fshape_2eproto
::PROTOBUF_NAMESPACE_ID::internal::SCCInfo<1>
scc_info_TensorShapeProto_tensorboard_2fcompat_2fproto_2ftensor_5fshape_2eproto;
## Description
1. Convert some git submodules to cmake external projects
2. Update nsync from
[1.23.0](https://github.com/google/nsync/releases/tag/1.23.0) to
[1.25.0](https://github.com/google/nsync/releases/tag/1.25.0)
3. Update re2 from 2021-06-01 to 2022-06-01
4. Update wil from an old commit to 1.0.220914.1 tag
5. Update gtest to a newer commit so that it can optionally leverage
absl/re2 for parsing command line flags.
The following git submodules are deleted:
1. FP16
2. safeint
3. XNNPACK
4. cxxopts
5. dlpack
7. flatbuffers
8. googlebenchmark
9. json
10. mimalloc
11. mp11
12. pthreadpool
More will come.
## Motivation and Context
There are 3 ways of integrating 3rd party C/C++ libraries into ONNX
Runtime:
1. Install them to a system location, then use cmake's find_package
module to locate them.
2. Use git submodules
6. Use cmake's external projects(externalproject_add).
At first when this project was just started, we considered both option 2
and option 3. We preferred option 2 because:
1. It's easier to handle authentication. At first this project was not
open source, and it had some other non-public dependencies. If we use
git submodule, ADO will handle authentication smoothly. Otherwise we
need to manually pass tokens around and be very careful on not exposing
them in build logs.
2. At that time, cmake fetched dependencies after "cmake" finished
generating vcprojects/makefiles. So it was very difficult to make cflags
consistent. Since cmake 3.11, it has a new command: FetchContent, which
fetches dependencies when it generates vcprojects/makefiles just before
add_subdirectories, so the parent project's variables/settings can be
easily passed to the child projects.
And when the project went on, we had some new concerns:
1. As we started to have more and more EPs and build configs, the number
of submodules grew quickly. For more developers, most ORT submodules are
not relevant to them. They shouldn't need to download all of them.
2. It is impossible to let two different build configs use two different
versions of the same dependency. For example, right now we have protobuf
3.18.3 in the submodules. Then every EP must use the same version.
Whenever we have a need to upgrade protobuf, we need to coordinate
across the whole team and many external developers. I can't manage it
anymore.
3. Some projects want to manage the dependencies in a different way,
either because of their preference or because of compliance
requirements. For example, some Microsoft teams want to use vcpkg, but
we don't want to force every user of onnxruntime using vcpkg.
7. Someone wants to dynamically link to protobuf, but our build script
only does static link.
8. Hard to handle security vulnerabilities. For example, whenever
protobuf has a security patch, we have a lot of things to do. But if we
allowed people to build ORT with a different version of protobuf without
changing ORT"s source code, the customer who build ORT from source will
be able to act on such things in a quicker way. They will not need to
wait ORT having a patch release.
9. Every time we do a release, github will also publish a source file
zip file and a source file tarball for us. But they are not usable,
because they miss submodules.
### New features
After this change, users will be able to:
1. Build the dependencies in the way they want, then install them to
somewhere(for example, /usr or a temp folder).
2. Or download the dependencies by using cmake commands from these
dependencies official website
3. Similar to the above, but use your private mirrors to migrate supply
chain risks.
4. Use different versions of the dependencies, as long as our source
code is compatible with them. For example, you may use you can't use
protobuf 3.20.x as they need code changes in ONNX Runtime.
6. Only download the things the current build needs.
10. Avoid building external dependencies again and again in every build.
### Breaking change
The onnxruntime_PREFER_SYSTEM_LIB build option is removed you could think from now
it is default ON. If you don't like the new behavior, you can set FETCHCONTENT_TRY_FIND_PACKAGE_MODE to NEVER.
Besides, for who relied on the onnxruntime_PREFER_SYSTEM_LIB build
option, please be aware that this PR will change find_package calls from
Module mode to Config mode. For example, in the past if you have
installed protobuf from apt-get from ubuntu 20.04's official repo,
find_package can find it and use it. But after this PR, it won't. This
is because that protobuf version provided by Ubuntu 20.04 is too old to
support the "config mode". It can be resolved by getting a newer version
of protobuf from somewhere.
