Cjian/1.13 cherry pick round 2 #13206
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… rel-1.13.0 branch. (#13187)
…13091) ### Description <!-- Describe your changes. --> Update React Native documentation to reflect change to use full ORT. Fix broken links. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? ORT v1.13 uses the full ORT package. Instructions for performing a custom build did not cover this. Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description We fix iGPU Unit and Python tests with this PR We add packaging pip pkg to build Many Linux DockerFile ### Motivation and Context This change is required to make sure iGPU Unit Test/Python Tests with OV are fixed - If it fixes an open issue, please link to the issue here. --> Co-authored-by: shamaksx <shamax.kshirsagar@intel.com> Co-authored-by: mayavijx <mayax.vijayan@intel.com> Co-authored-by: pratiksha <pratikshax.bapusaheb.vanse@intel.com> Co-authored-by: pratiksha <mohsinx.mohammad@intel.com> Co-authored-by: Sahar Fatima <sfatima.3001@gmail.com> Co-authored-by: Preetha Veeramalai <preetha.veeramalai@intel.com> Co-authored-by: nmaajidk <n.maajid.khan@intel.com> Co-authored-by: Mateusz Tabaka <mateusz.tabaka@intel.com>
### Description fix XNNPACK on WebAssembly SIMD. Flag "-msimd128" need to be applied to every source file when compiling WASM SIMD. Currently only a part of the source files are compiled with this flag so we get inconsistent result for `sizeof(xnn_f32_minmax_params)` because the type definition include a `#ifdef` for `__wasm_simd128__`. The inconsistency causes writing garbage data to a stack variable and eventually cause the crash. XNNPACK libraries are C libraries so need to apply the build flags not only to `CMAKE_CXX_FLAGS` but also to `CMAKE_C_FLAGS`.
Refine the QuantConfig: 1. Remove the default EP config. 2. pass QuantConfig to quantize API direclty.
### Description <!-- Describe your changes. --> A fix for parity issue in huggingface bart model with beam search #12779 ### 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. -->
Previously OnnxSequence would flatten out a list of tensors into a single output array assuming they were all scalar values. This doesn't accurately represent the semantics of an ONNX sequence, but was what the semantics appeared to be years ago when I first wrote that class. This PR changes it so that the `getValue` method on `OnnxSequence` unwraps the sequence and returns `List<? extends OnnxValue>` allowing the user to process the individual ONNX values separately. It's done this way rather than returning a multidimensional array for a tensor and a Java map for a map as multidimensional arrays are very inefficient in Java and best practice when operating with a OnnxTensor in Java is to use a `java.nio.ByteBuffer`. So allowing users to access each `OnnxTensor`s individually allows them to control how the data is materialised on the Java heap.
**Description**: This PR adds support for "XNNPACK EP" in ORTWeb and changes the behavior of how ORTWeb deals with "backends", or "EPs" in API. **Background**: Term "backend" is introduced in ONNX.js to representing a TypeScript type which implements a "backend" interface, which is a similar but different concept to ORT's EP (execution provider). There was 3 backends in ONNX.js: "cpu", "wasm" and "webgl". When ORT Web is launched, the concept is derived to help users to integrate smoothly. Technically, when "wasm" backend is used, users need to also specify "EP" in the session options. Considering it may get complicated and confused for users to figure out the difference between "backend" and "EP", the JS API hide the "backend" concept and made a mapping between names, backends and EPs: "webgl" (Name) <==> "onnxjsBackend" (Backend) "wasm" (Name) <==> "wasmBackend" (Backend) <==> "CPU" (EP) **Details**: The following changes are applied in this PR: 1. allow multi-registration for backends using the same name. This is for use scenarios where both "onnxruntime-node" and "onnxruntime-web" are consumed in a Node.js App ( so "cpu" will be registered twice in this scenario. ) 2. re-assign priority values to backends. I give 100 as base to "cpu" for node and react_native, and 10 as base to "cpu" in web. 3. add "cpu", "xnnpack" as new names of backends. 4. update onnxruntime wasm exported functions to support EP registration. 5. update implementations in ort web to handle execution providers in session options. 6. add '--use_xnnpack' as default build flag for ort-web
baijumeswani
previously approved these changes
Oct 3, 2022
yufenglee
previously approved these changes
Oct 3, 2022
skottmckay
previously approved these changes
Oct 3, 2022
### Description <!-- Describe your changes. --> Add handling for variadic inputs/outputs in a function. ### 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. --> #13121
jchen351
dismissed stale reviews from skottmckay, yufenglee, edgchen1, and baijumeswani
via
44af30e
skottmckay
previously approved these changes
Oct 3, 2022
snnn
previously approved these changes
Oct 4, 2022
(1) Hot fixes reshape fusion, which causes stable diffusion unet model invalid. (2) Update remove_cascaded_cast_nodes to make it faster
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signing off for:
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This pull request fixes 1 alert when merging 2e55c57 into c0bb9d5 - view on LGTM.com fixed alerts:
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snnn
approved these changes
Oct 4, 2022
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signing off on cherry pick of #13122 |
baijumeswani
approved these changes
Oct 4, 2022
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Description
This is the round 2 of cherry-pick into 1.13
Motivation and Context