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Update to clang 20 (rapidsai#18818)
Contributes to rapidsai/build-planning#177 This PR updates the clang version to 20. Authors: - Bradley Dice (https://github.com/bdice) Approvers: - Vyas Ramasubramani (https://github.com/vyasr) - David Wendt (https://github.com/davidwendt) URL: rapidsai#18818
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.pre-commit-config.yaml

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@@ -42,7 +42,7 @@ repos:
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"python/dask_cudf/dask_cudf"]
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pass_filenames: false
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- repo: https://github.com/pre-commit/mirrors-clang-format
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rev: v16.0.6
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rev: v20.1.4
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hooks:
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- id: clang-format
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types_or: [c, c++, cuda]

conda/environments/all_cuda-118_arch-aarch64.yaml

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@@ -14,8 +14,9 @@ dependencies:
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- c-compiler
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- cachetools
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- certifi
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- clang-tools=16.0.6
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- clang==16.0.6
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- clang-tools=20.1.4
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- clang-tools==20.1.4
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- clang==20.1.4
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- cmake>=3.30.4
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- cramjam
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- cubinlinker
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- gcc_linux-aarch64=11.*
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- hypothesis>=6.131.7
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- identify>=2.5.20
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- include-what-you-use==0.24.0
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- ipython
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- jupyter_client
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- libcurand-dev=10.3.0.86

conda/environments/all_cuda-118_arch-x86_64.yaml

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@@ -14,8 +14,9 @@ dependencies:
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- c-compiler
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- cachetools
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- certifi
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- clang-tools=16.0.6
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- clang==16.0.6
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- clang-tools=20.1.4
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- clang-tools==20.1.4
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- clang==20.1.4
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- cmake>=3.30.4
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- cramjam
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- cubinlinker
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- gcc_linux-64=11.*
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- hypothesis>=6.131.7
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- identify>=2.5.20
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- include-what-you-use==0.24.0
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- ipython
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- jupyter_client
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- libcufile-dev=1.4.0.31

conda/environments/all_cuda-128_arch-aarch64.yaml

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@@ -14,8 +14,9 @@ dependencies:
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- c-compiler
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- cachetools
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- certifi
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- clang-tools=16.0.6
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- clang==16.0.6
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- clang-tools=20.1.4
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- clang-tools==20.1.4
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- clang==20.1.4
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- cmake>=3.30.4
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- cramjam
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- cuda-cudart-dev
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- gcc_linux-aarch64=13.*
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- hypothesis>=6.131.7
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- identify>=2.5.20
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- include-what-you-use==0.24.0
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- ipython
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- jupyter_client
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- libcurand-dev

conda/environments/all_cuda-128_arch-x86_64.yaml

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@@ -14,8 +14,9 @@ dependencies:
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- c-compiler
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- cachetools
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- certifi
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- clang-tools=16.0.6
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- clang==16.0.6
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- clang-tools=20.1.4
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- clang-tools==20.1.4
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- clang==20.1.4
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- cmake>=3.30.4
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- cramjam
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- cuda-cudart-dev
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- gcc_linux-64=13.*
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- hypothesis>=6.131.7
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- identify>=2.5.20
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- include-what-you-use==0.24.0
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- ipython
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- jupyter_client
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- libcufile-dev

cpp/CMakeLists.txt

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@@ -187,7 +187,7 @@ if(CUDF_CLANG_TIDY)
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# versions are skipped so we don't want to constrain to a patch version that the user can't
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# install.
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set(LLVM_VERSION "${CMAKE_MATCH_1}")
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set(expected_clang_tidy_version 19.1)
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set(expected_clang_tidy_version 20.1)
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if(NOT expected_clang_tidy_version VERSION_EQUAL LLVM_VERSION)
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message(

cpp/benchmarks/ndsh/utilities.hpp

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@@ -1,5 +1,5 @@
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/*
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* Copyright (c) 2024, NVIDIA CORPORATION.
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* Copyright (c) 2024-2025, NVIDIA CORPORATION.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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class table_with_names {
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public:
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table_with_names(std::unique_ptr<cudf::table> tbl, std::vector<std::string> col_names)
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: tbl(std::move(tbl)), col_names(col_names){};
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: tbl(std::move(tbl)), col_names(col_names) {};
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/**
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* @brief Return the table view
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*/

cpp/benchmarks/string/translate.cpp

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/*
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* Copyright (c) 2021-2024, NVIDIA CORPORATION.
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* Copyright (c) 2021-2025, NVIDIA CORPORATION.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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std::transform(thrust::counting_iterator<int>(0),
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thrust::counting_iterator<int>(entry_count),
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entries.begin(),
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[](auto idx) -> entry_type {
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return entry_type{'!' + idx, '~' - idx};
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});
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[](auto idx) -> entry_type { return entry_type{'!' + idx, '~' - idx}; });
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auto stream = cudf::get_default_stream();
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state.set_cuda_stream(nvbench::make_cuda_stream_view(stream.value()));

cpp/examples/parquet_io/parquet_io_multithreaded.cpp

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/*
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* Copyright (c) 2024, NVIDIA CORPORATION.
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* Copyright (c) 2024-2025, NVIDIA CORPORATION.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
@@ -321,12 +321,11 @@ std::vector<io_source> extract_input_sources(std::string const& paths,
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std::vector<io_source> input_sources;
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input_sources.reserve(parquet_files.size());
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// Transform input files to the specified io sources
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std::transform(parquet_files.begin(),
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parquet_files.end(),
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std::back_inserter(input_sources),
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[&](auto const& file_name) {
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return io_source{file_name, io_source_type, stream};
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});
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std::transform(
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parquet_files.begin(),
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parquet_files.end(),
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std::back_inserter(input_sources),
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[&](auto const& file_name) { return io_source{file_name, io_source_type, stream}; });
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stream.synchronize();
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return input_sources;
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}

cpp/include/cudf/column/column_view.hpp

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@@ -478,7 +478,7 @@ class column_view : public detail::column_view_base {
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std::vector<column_view> _children{}; ///< Based on element type, children
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///< may contain additional data
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}; // namespace cudf
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}; // namespace cudf
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/**
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* @brief A non-owning, mutable view of device data as a column of elements,
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public:
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mutable_column_view() = default;
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~mutable_column_view() override{
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~mutable_column_view() override {
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// Needed so that the first instance of the implicit destructor for any TU isn't 'constructed'
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// from a host+device function marking the implicit version also as host+device
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};

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