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### Description This PR is to update the win-ort-main branch to the tip main branch as of 2025-01-23. ### PR List ddf0d377a7 [QNN EP] Add LoggingManager::HasDefaultLogger() to provider bridge API (#23467) 05fbbdf91f [QNN EP] Make QNN EP a shared library (#23120) 1336566d7f Add custom vcpkg ports (#23456) 2e1173c411 Update the compile flags for vcpkg packages (#23455) 1f628a9858 [Mobile] Add BrowserStack Android MAUI Test (#23383) 009cae0ec8 [js/webgpu] Optimize ConvTranspose (Continue) (#23429) 04a4a694cb Use onnx_protobuf.h to suppress some GCC warnings (#23453) 2e3b62b4b0 Suppress some strict-aliasing related warnings in WebGPU EP (#23454) b708f9b1dc Bump ruff from 0.9.1 to 0.9.2 (#23427) c0afc66b2a [WebNN] Remove workarounds for TFLite backend (#23406) 8a821ff7f9 Bump vite from 6.0.7 to 6.0.11 in /js/web/test/e2e/exports/testcases/vite-default (#23446) 220c1a203e Make ORT and Dawn use the same protobuf/abseil source code (#23447) b7b5792147 Change MacOS-13 to ubuntu on for android-java-api-aar-test.yml. (#23444) 19d0d2a30f WIP: Dp4MatMulNBits accuracy level 4 matmul for WebGPU EP (#23365) 95b8effbc4 [QNN EP]: Clean up QNN logging resources if an error occurs during initialization (#23435) 626134c5b5 Bump clang-format from 19.1.6 to 19.1.7 (#23428) 0cf975301f Fix eigen external deps (#23439) f9440aedce Moving RN_CI Android Testing to Linux (#23422) 1aa5902ff4 [QNN EP] workaround for QNN validation bug for Tanh with uint16 quantized output (#23432) 7f5582a0e2 Seperate RN andriod and IOS into 2 separated Stages. (#23400) 73deac2e7f Implement some missing element wise Add/Sub/Mul/Div/Neg operations for CPU and CUDA EPs (#23090) 949fe42af4 Upgrade Java version from react-native/android to Java 17 (#23066) 0892c23463 Update Qnn SDK default version to 2.30 (#23411) 94c099bcec Fix type cast build error (#23423) d633e571d1 [WebNN EP] Fix AddInitializersToSkip issues (#23354) e988ef00e2 [QNN EP] Fix regression for MatMul with two quantized/dynamic uint16 inputs (#23419) 7538795f6b Update onnxruntime binary size checks ci pipeline's docker image (#23405) 6c5ea41cad Revert "[QNN EP] Clean up correctly from a partial setup (#23320)" (#23420) e866804bbe Enable comprehension simplification in ruff rules (#23414) 0a5f1f392c bugfix: string_view of invalid memory (#23417) 4cc38e0277 fix crash when first input of BatchNormalization is 1-D (#23387) 033441487f Target py310 and modernize codebase with ruff (#23401) 87341ac010 [QNN EP] Fix segfault when unregistering HTP shared memory handles (#23402) ### Motivation and Context This update includes the change to make QNN-EP a shared library. --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com> Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com> Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com> Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com> Co-authored-by: Changming Sun <chasun@microsoft.com> Co-authored-by: Peishen Yan <peishen.yan@intel.com> Co-authored-by: Tianlei Wu <tlwu@microsoft.com> Co-authored-by: Hector Li <hecli@microsoft.com> Co-authored-by: Jian Chen <cjian@microsoft.com> Co-authored-by: Alexis Tsogias <1114095+Zyrin@users.noreply.github.com> Co-authored-by: junchao-zhao <68935141+junchao-loongson@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: sushraja-msft <44513542+sushraja-msft@users.noreply.github.com> Co-authored-by: Wanming Lin <wanming.lin@intel.com> Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com> Co-authored-by: Caroline Zhu <wolfivyaura@gmail.com>
73 lines
3 KiB
TOML
73 lines
3 KiB
TOML
[tool.pydocstyle]
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convention = "google"
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[tool.pyright]
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exclude = ["onnxruntime/core/flatbuffers/*"]
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reportMissingImports = false
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[tool.ruff]
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# NOTE: Do not create an exclude list. Edit .lintrunner.toml instead
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target-version = "py310"
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line-length = 120
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[tool.ruff.lint]
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select = [
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"B", # flake8-bugbear
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"C4", # flake8-comprehensions
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"E", # pycodestyle
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"F", # Pyflakes
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"FURB", # refurb
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"G", # flake8-logging-format
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"I", # isort
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"ISC", # flake8-implicit-str-concat
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"N", # pep8-naming
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"NPY", # numpy
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"PERF", # Perflint
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"PIE", # flake8-pie
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"PLC", # pylint conventions
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"PLE", # pylint errors
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"PLW", # pylint warnings
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"PYI", # flake8-pyi
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"RUF", # Ruff-specific rules
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"SIM", # flake8-simplify
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"SLOT", # flake8-slots
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"T10", # flake8-debugger
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"UP", # pyupgrade
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"W", # pycodestyle
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"YTT", # flake8-2020
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]
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# NOTE: Refrain from growing the ignore list unless for exceptional cases.
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# Always include a comment to explain why.
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ignore = [
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"B028", # FIXME: Add stacklevel to warnings
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"C408", # Sometimes it is preferable when we construct kwargs
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"E501", # Line length controlled by black
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"G004", # FIXME: Enable when the rule can be autofixed
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"N803", # Argument casing
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"N812", # Allow import torch.nn.functional as F
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"N813", # Allow importing camelcase names in lowercase
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"N999", # Module names
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"NPY002", # np.random.Generator may not always fit our use cases
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"PERF203", # "try-except-in-loop" only affects Python <3.11, and the improvement is minor; can have false positives
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"PERF401", # List comprehensions are not always readable
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"PYI041", # May create confusion
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"PYI024", # May create confusion
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"SIM102", # We don't perfer always combining if branches
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"SIM103", # Do not collapse if-else
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"SIM108", # We don't encourage ternary operators
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"SIM114", # Don't combine if branches for debugability
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"SIM116", # Don't use dict lookup to replace if-else
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"UP038", # Using X | Y in isinstance checks is a little aggresive
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]
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[tool.ruff.lint.per-file-ignores]
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# NOTE: Refrain from growing the ignore list unless for exceptional cases.
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# Prefer inline ignores with `noqa: xxx`.
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# Eventually this list should become empty.
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"orttraining/orttraining/test/**" = ["N802"] # Function casing
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"tools/nuget/generate_nuspec_for_native_nuget.py" = ["ISC003"] # Too many errors to fix
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"onnxruntime/contrib_ops/cuda/sparse/sparse_attention_v1/sparse_attention_triton.py" = ["N806"] # use of Q, K and V in triton script
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"onnxruntime/contrib_ops/cuda/sparse/sparse_attention_v2/sparse_attention_v2_triton.py" = ["N806"] # use of Q, K and V in triton script
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"onnxruntime/test/python/quantization/test_op_gemm.py" = ["N806"] # use of A for a matrix
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"onnxruntime/test/python/quantization/op_test_utils.py" = ["N806", "PERF203", "RUF012"] # use of A for a matrix
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"orttraining/orttraining/python/training/ort_triton/kernel/_flash_attn.py" = ["N806", "PLW2901", "ISC001", "E731"] # Long triton code from other repo.
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