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/llvm-project/compiler-rt/lib/sanitizer_common/
H A D	sanitizer_allocator_local_cache.h	1 //===-- sanitizer_allocator_local_cache.h ------------------------ C++ --===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 11 //===----------------------------------------------------------------------===// 25 s->Register(&stats_); in Init() 31 s->Unregister(&stats_); in Destroy() 38 if (UNLIKELY(c->count == 0)) { in Allocate() 41 DCHECK_GT(c->count, 0); in Allocate() 43 CompactPtrT chunk = c->chunks[--c->count]; in Allocate() 44 stats_.Add(AllocatorStatAllocated, c->class_size); in Allocate() [all …]
/llvm-project/mlir/lib/Dialect/Linalg/Transforms/
H A D	DropUnitDims.cpp	`1 //===- DropUnitDims.cpp - Pass to drop use of unit-extent for broadcasting ===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===--- [all...]`
H A D	BlockPackMatmul.cpp	`1 //===- BlockPackMatmul.cpp - Linalg matmul block packing -------- [all...]`
H A D	TransposeMatmul.cpp	`1 //===- TransposeMatmul.cpp - Convert Linalg matmul to transposed variants -===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===--- [all...]`
/llvm-project/mlir/lib/Dialect/Linalg/IR/
H A D	LinalgInterfaces.cpp	`1 //===- LinalgInterfaces.cpp - Linalg interfaces implementation -------- 641 llvm::SmallDenseSet<int64_t> batch = inputExprWalker.unConvolvedDims; inferConvolutionDimsImpl() local [all...]`
/llvm-project/lldb/test/Shell/SymbolFile/DWARF/
H A D	dwo-debug-file-search-paths-filename-only-absolute-compdir.c	1 /// Check that LLDB uses the paths in target.debug-file-search-paths to find 2 /// split DWARF files with DW_AT_comp_dir set to some non-relative path, when 5 /// it to %t.compdir/main-main.dwo and it's name is c/d/main-main.dwo. 6 // UNSUPPORTED: system-darwin 7 // RUN: rm -rf %t.compdir/ %t.e/ 8 // RUN: mkdir -p %t.compdir/a/b/c/d/ 11 /// The produced DWO is named c/d/main-main.dwo, with a non-relative 13 // RUN: %clang_host -g -gsplit-dwarf c/d/main.c -o c/d/main 20 // RUN: mkdir -p %t.e/ 23 // RUN: %lldb --no-lldbinit %t.compdir/a/main \ [all …]
H A D	dwo-debug-file-search-paths-dwoname-absolute-compdir.c	1 /// Check that LLDB uses the paths in target.debug-file-search-paths to find 5 /// directory but is still at it's name. Here, %t.compdir/c/d/main-main.dwo. 6 // UNSUPPORTED: system-darwin 7 // RUN: rm -rf %t.compdir/ %t.e/ 8 // RUN: mkdir -p %t.compdir/a/b/c/d/ 11 /// The produced DWO is named c/d/main-main.dwo, with a non-relative 13 // RUN: %clang_host -g -gsplit-dwarf c/d/main.c -o c/d/main 18 // RUN: mkdir -p %t.compdir/c/d/ 21 // RUN: mkdir -p %t.e/ 24 // RUN: %lldb --no-lldbinit %t.compdir/a/main \ [all …]
/llvm-project/clang-tools-extra/clangd/
H A D	Selection.cpp	1 //===--- Selection.cpp ----------------------------------------------------===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 53 for (const auto N = Common; N; N = N->Parent) { in recordMetrics() 54 if (const auto RE = N->ASTNode.get<RecoveryExpr>()) { in recordMetrics() 56 RecoveryType.record(RE->isTypeDependent() ? 0 : 1, LanguageLabel); in recordMetrics() 71 // [----] MemberExpr, base = A().<anonymous>, member = b in getSourceRange() 72 // [----] MemberExpr: base = A(), member = <anonymous> in getSourceRange() 73 // [-] CXXConstructExpr in getSourceRange() 78 if (!ME->getMemberDecl()->getDeclName()) in getSourceRange() [all …]
/llvm-project/mlir/include/mlir/Dialect/SparseTensor/IR/
H A D	Enums.h	1 //===- Enums.h - Enums for the SparseTensor dialect -------------- C++ --===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 17 // This file also defines x-macros <https://en.wikipedia.org/wiki/X_Macro> 19 // supported primary- and/or overhead-type. 26 //===----------------------------------------------------------------------===// 44 /// values with the built-in type "index". For now, we simply assume that 45 /// type is 64-bit, but targets with different "index" bitwidths should 59 // This x-macro calls its argument on every overhead type which has 60 // fixed-width. It excludes `index_type` because that type is often [all …]
H A D	SparseTensorAttrDefs.td	`1 //===-- SparseTensorAttrDefs.td - attributes definitions ---- tablegen --===// 5 // SPDX-Licens [all...]`
/llvm-project/mlir/python/mlir/dialects/linalg/opdsl/ops/
H A D	core_named_ops.py	6 Batch = S.Batch variable 398 includes zero-point adjustments for the left and right operands of the 402 C[D.m, D.n] += (TypeFn.cast_signed(U, A[D.m, D.k]) - TypeFn.cast_signed(U, AZp)) * ( 403 TypeFn.cast_signed(U, B[D.k, D.n]) - TypeFn.cast_signed(U, BZp) 449 """Performs a matrix-matrix-transpose multiplication of two 4D inputs. 468 lhs=TensorDef(TV.LhsType, Batch, S.M, S.K, S.M0, S.K0), 469 rhs=TensorDef(TV.RhsType, Batch, S.N, S.K, S.N0, S.K0), 470 accum=TensorDef(TV.AccumType, Batch, 491 batch_mmt4d( lhs=TensorDef(TV.LhsType, Batch, S.M, S.K, S.M0, S.K0), rhs=TensorDef(TV.RhsType, Batch, S.N, S.K, S.N0, S.K0), accum=TensorDef(TV.AccumType, Batch, S.M, S.N, S.M0, S.N0, output=True), ) global() argument 512 batch_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 530 batch_matmul_transpose_a( A=TensorDef(T1, Batch, S.K, S.M), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 549 batch_matmul_transpose_b( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.N, S.K), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 568 quantized_batch_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), AZp=ScalarDef(I32), BZp=ScalarDef(I32), C=TensorDef(U, Batch, S.M, S.N, output=True), ) global() argument 589 batch_reduce_matmul( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, S.M, S.N, output=True), ) global() argument 636 batch_matvec( A=TensorDef(T1, Batch, S.M, S.K), B=TensorDef(T2, Batch, S.K), C=TensorDef(U, Batch, S.M, output=True), ) global() argument 654 batch_vecmat( A=TensorDef(T1, Batch, S.K), B=TensorDef(T2, Batch, S.K, S.N), C=TensorDef(U, Batch, S.N, output=True), ) global() argument [all...]
/llvm-project/llvm/include/llvm/Support/
H A D	GenericDomTreeConstruction.h	`1 //===- GenericDomTreeConstruction.h - Dominator Calculation ------- C++ - [all...]`
/llvm-project/mlir/lib/Dialect/SparseTensor/Transforms/Utils/
H A D	SparseTensorIterator.cpp	1 //===- SparseTensorIterator.cpp -------------------------------------------===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 21 //===----------------------------------------------------------------------===// 23 //===----------------------------------------------------------------------===// 43 //===----------------------------------------------------------------------===// 45 //===----------------------------------------------------------------------===// 92 llvm_unreachable("locate random-accessible level instead"); in peekCrdAt() 99 assert(parentPos.size() == 1 && "Dense level can not be non-unique."); in peekRangeAt() 110 : SparseTensorLevel(tid, lvl, LevelFormat::Batch, lvlSize) {} in BatchLevel() [all …]
H A D	SparseTensorIterator.h	`1 //===- SparseTensorIterator.h --------- [all...]`
/llvm-project/mlir/docs/Dialects/Linalg/
H A D	_index.md	`7 <img width="90" align="left" alt="MLIR Codegen Flow" src="https://user-images.githubusercontent.com/10148468/73613629-c5586580-45c5-11ea-94b7-074aeea94c7b.png"> 9 Linalg is designed to solve the High-level Hierarchical Optimization (HHO box) 21 one-off op knowledge. 30 1. Tiled Producer-Consumer Fusion with Parametric Tile-An [all...]`
/llvm-project/mlir/lib/Dialect/Tosa/Transforms/
H A D	TosaDecomposeTransposeConv.cpp	`1 //===- TosaDecomposeTransposeConv.cpp --------- 175 int64_t batch = inputTy.getDimSize(0); matchAndRewrite() local [all...]`
/llvm-project/mlir/lib/Dialect/SparseTensor/Transforms/
H A D	SparseIterationToScf.cpp	`49 // TODO: handle batch dimension. in convertIteratorType() 52 // Segment high for non-unique iterator. 73 op.getRegionDefinedSpace(newBlock->getParent()->getRegionNumber()); 77 it->getCrd(), loopCrd); 86 // Set up block arguments: user-provided values -> loop coord -> iterators. in matchAndRewrite() 90 llvm::append_range(blockArgs, iters[idx]->getCurso in matchAndRewrite() [all...]`
/llvm-project/llvm/docs/
H A D	HowToAddABuilder.rst	28 commits from the llvm-zorg repository. 52 with the "config owner". We do expect "resource owners" - who are generally 53 the contact listed in a workers attributes - to proxy requests to the relevant 74 of parallelism (-j param) would give the fastest build. You can build 77 #. Install buildbot-worker (currently we are using buildbot version 2.8.4). 79 as ``pip3 install buildbot-worker==2.8.4``. 81 #. Create a designated user account, your buildbot-worker will be running under, 84 #. Choose the buildbot-worker root directory (all builds will be placed under 85 it), buildbot-worker access name and password the build master will be using 86 to authenticate your buildbot-worke [all...]
/llvm-project/mlir/docs/Tutorials/transform/
H A D	Ch4.md	3 **Check the continuously-tested version of MLIR files under 4 [mlir/test/Examples/transform/Ch4](https://github.com/llvm/llvm-project/tree/main/mlir/test/Example… 23 becomes possible to set up a higher-level match and rewrite infrastructure 30 1](Ch1.md/#chaining-transformations-with-handles), reproduced below for 38 -> tensor<512x512xf32> { 39 // Matrix-matrix multiplication. 42 outs(%output: tensor<512x512xf32>) -> tensor<512x512xf32> 47 outs(%output : tensor<512x512xf32>) -> tensor<512x512xf32> 53 outs(%output : tensor<512x512xf32>) -> tensor<512x512xf32> 61 additional arguments, `bind-first-extra-to-ops=linalg.matmul [all …]
/llvm-project/libcxx/docs/
H A D	BuildingLibcxx.rst
/llvm-project/mlir/lib/Dialect/SparseTensor/IR/
H A D	SparseTensorDialect.cpp	`1 //===- SparseTensorDialect.cpp - Sparse tensor dialect implementation -----===// 5 // SPDX-License-Identifier: Apache-2. [all...]`
/llvm-project/compiler-rt/lib/profile/
H A D	InstrProfilingInternal.h	`1 /*===- InstrProfiling.h- Support library for PGO instrumentation -------- [all...]`
/llvm-project/mlir/docs/Rationale/
H A D	Rationale.md	5 decisions we made. This is not intended to be a "finely groomed" document - we 14 three-address SSA representations (like 19 high level dataflow graphs as well as target-specific code generated for high 24 MLIR stands for one of "Multi-Level IR" or "Multi-dimensional Loop IR" or 26 provides the rationale behind MLIR -- its actual 31 The Multi-Level Intermediate Representation (MLIR) is intended for easy 33 matrices of high dimensionality. It is thus well-suited to deep learning 35 sequential computation. The representation allows high-level optimization and 37 deep memory hierarchies --- general-purpose multicores, GPUs, and specialized 45 MLIR is a multi-level IR, i.e., it represents code at a domain-specific [all …]
/llvm-project/llvm/test/tools/llvm-objcopy/ELF/
H A D	preserve-segment-contents.test	12 # RUN: yaml2obj %s -o %t.base 13 # RUN: llvm-objcopy %t.base %t.stripped --regex -R blob.* 16 # RUN: od -t x1 -j 0x2000 -N 28 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK1 -DPA… 17 # RUN: od -t x1 -j 0x2100 -N 12 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK2 -DPA… 18 # RUN: od -t x1 -j 0x2200 -N 4 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK3 -DPA… 19 # RUN: od -t x1 -j 0x2300 -N 12 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK4 -DPA… 20 # RUN: od -t x1 -j 0x3000 -N 68 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK5 -DPA… 21 # RUN: od -t x1 -j 0x4000 -N 60 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK6 -DPA… 22 # RUN: od -t x1 -j 0x5000 -N 60 %t.stripped \| FileCheck %s --ignore-case --check-prefix=CHECK7 -DPA… 34 # RUN: llvm-objcopy %t.in %t.out [all …]
/llvm-project/mlir/include/mlir/Dialect/LLVMIR/
H A D	LLVMTypes.h	`1 //===- LLVMTypes.h - MLIR LLVM dialect types -------- [all...]`

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