[flang-commits] [flang] 4c5b535 - Revert "[flang] Handle array constants of any rank"
Leandro Lupori via flang-commits
flang-commits at lists.llvm.org
Mon May 22 12:11:31 PDT 2023
Author: Leandro Lupori
Date: 2023-05-22T16:11:12-03:00
New Revision: 4c5b535439e842d33cfe50de8384f3d1ca055ab1
URL: https://github.com/llvm/llvm-project/commit/4c5b535439e842d33cfe50de8384f3d1ca055ab1
DIFF: https://github.com/llvm/llvm-project/commit/4c5b535439e842d33cfe50de8384f3d1ca055ab1.diff
LOG: Revert "[flang] Handle array constants of any rank"
This reverts commit e26e68a4905cc13064987c9b19fa153b54035d36.
This broke gfortran test-suite, test regression/intrinsic_pack_3.f90.
Added:
Modified:
flang/lib/Lower/ConvertConstant.cpp
flang/lib/Lower/ConvertVariable.cpp
flang/test/Lower/array.f90
Removed:
flang/test/Lower/dense-array-any-rank.f90
################################################################################
diff --git a/flang/lib/Lower/ConvertConstant.cpp b/flang/lib/Lower/ConvertConstant.cpp
index de8830a7287d..7afcc96ba65d 100644
--- a/flang/lib/Lower/ConvertConstant.cpp
+++ b/flang/lib/Lower/ConvertConstant.cpp
@@ -20,8 +20,6 @@
#include "flang/Optimizer/Builder/Complex.h"
#include "flang/Optimizer/Builder/Todo.h"
-#include <algorithm>
-
/// Convert string, \p s, to an APFloat value. Recognize and handle Inf and
/// NaN strings as well. \p s is assumed to not contain any spaces.
static llvm::APFloat consAPFloat(const llvm::fltSemantics &fsem,
@@ -68,12 +66,17 @@ namespace {
/// Helper class to lower an array constant to a global with an MLIR dense
/// attribute.
///
-/// If we have an array of integer, real, or logical, then we can
+/// If we have a rank-1 array of integer, real, or logical, then we can
/// create a global array with the dense attribute.
///
/// The mlir tensor type can only handle integer, real, or logical. It
/// does not currently support nested structures which is required for
/// complex.
+///
+/// Also, we currently handle just rank-1 since tensor type assumes
+/// row major array ordering. We will need to reorder the dimensions
+/// in the tensor type to support Fortran's column major array ordering.
+/// How to create this tensor type is to be determined.
class DenseGlobalBuilder {
public:
static fir::GlobalOp tryCreating(fir::FirOpBuilder &builder,
@@ -121,6 +124,8 @@ class DenseGlobalBuilder {
&constant) {
static_assert(TC != Fortran::common::TypeCategory::Character,
"must be numerical or logical");
+ if (constant.Rank() != 1)
+ return;
auto attrTc = TC == Fortran::common::TypeCategory::Logical
? Fortran::common::TypeCategory::Integer
: TC;
@@ -153,16 +158,12 @@ class DenseGlobalBuilder {
llvm::StringRef globalName,
mlir::StringAttr linkage,
bool isConst) const {
- // Not a "trivial" intrinsic constant array, or empty array.
+ // Not a rank 1 "trivial" intrinsic constant array, or empty array.
if (!attributeElementType || attributes.empty())
return {};
- assert(symTy.isa<fir::SequenceType>() && "expecting an array global");
- auto arrTy = symTy.cast<fir::SequenceType>();
- llvm::SmallVector<int64_t> tensorShape(arrTy.getShape());
- std::reverse(tensorShape.begin(), tensorShape.end());
auto tensorTy =
- mlir::RankedTensorType::get(tensorShape, attributeElementType);
+ mlir::RankedTensorType::get(attributes.size(), attributeElementType);
auto init = mlir::DenseElementsAttr::get(tensorTy, attributes);
return builder.createGlobal(loc, symTy, globalName, linkage, init, isConst);
}
@@ -543,13 +544,6 @@ genOutlineArrayLit(Fortran::lower::AbstractConverter &converter,
true, constant);
}
if (!global)
- // If the number of elements of the array is huge, the compilation may
- // use a lot of memory and take a very long time to complete.
- // Empirical evidence shows that an array with 150000 elements of
- // complex type takes roughly 30 seconds to compile and uses 4GB of RAM,
- // on a modern machine.
- // It would be nice to add a driver switch to control the array size
- // after which flang should not continue to compile.
global = builder.createGlobalConstant(
loc, arrayTy, globalName,
[&](fir::FirOpBuilder &builder) {
diff --git a/flang/lib/Lower/ConvertVariable.cpp b/flang/lib/Lower/ConvertVariable.cpp
index b0dcf4d4256a..2204505571ce 100644
--- a/flang/lib/Lower/ConvertVariable.cpp
+++ b/flang/lib/Lower/ConvertVariable.cpp
@@ -431,9 +431,14 @@ static fir::GlobalOp defineGlobal(Fortran::lower::AbstractConverter &converter,
// If this is an array, check to see if we can use a dense attribute
// with a tensor mlir type. This optimization currently only supports
- // Fortran arrays of integer, real, or logical. The tensor type does
- // not support nested structures which are needed for complex numbers.
- if (symTy.isa<fir::SequenceType>() &&
+ // rank-1 Fortran arrays of integer, real, or logical. The tensor
+ // type does not support nested structures which are needed for
+ // complex numbers.
+ // To get multidimensional arrays to work, we will have to use column major
+ // array ordering with the tensor type (so it matches column major ordering
+ // with the Fortran fir.array). By default, tensor types assume row major
+ // ordering. How to create this tensor type is to be determined.
+ if (symTy.isa<fir::SequenceType>() && sym.Rank() == 1 &&
!Fortran::semantics::IsAllocatableOrPointer(sym)) {
mlir::Type eleTy = symTy.cast<fir::SequenceType>().getEleTy();
if (eleTy.isa<mlir::IntegerType, mlir::FloatType, fir::LogicalType>()) {
diff --git a/flang/test/Lower/array.f90 b/flang/test/Lower/array.f90
index c64da68f3027..9d15b3b30115 100644
--- a/flang/test/Lower/array.f90
+++ b/flang/test/Lower/array.f90
@@ -102,25 +102,33 @@ subroutine range()
integer, dimension(10) :: a0
real, dimension(2,3) :: a1
integer, dimension(3,4) :: a2
- integer, dimension(2,3,4) :: a3
a0 = (/1, 2, 3, 3, 3, 3, 3, 3, 3, 3/)
a1 = reshape((/3.5, 3.5, 3.5, 3.5, 3.5, 3.5/), shape(a1))
a2 = reshape((/1, 3, 3, 5, 3, 3, 3, 3, 9, 9, 9, 8/), shape(a2))
- a3 = reshape((/1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12/), shape(a3))
end subroutine range
! a0 array constructor
! CHECK: fir.global internal @_QQro.10xi4.{{.*}}(dense<[1, 2, 3, 3, 3, 3, 3, 3, 3, 3]> : tensor<10xi32>) constant : !fir.array<10xi32>
! a1 array constructor
-! CHECK: fir.global internal @_QQro.2x3xr4.{{.*}}(dense<3.500000e+00> : tensor<3x2xf32>) constant : !fir.array<2x3xf32>
+! CHECK: fir.global internal @_QQro.2x3xr4.{{.*}} constant : !fir.array<2x3xf32> {
+ ! CHECK-DAG: %cst = arith.constant {{.*}} : f32
+ ! CHECK: %{{.*}} = fir.insert_on_range %{{[0-9]+}}, %cst from (0, 0) to (1, 2) :
! a2 array constructor
-! CHECK: fir.global internal @_QQro.3x4xi4.{{.*}}(dense<{{\[\[1, 3, 3], \[5, 3, 3], \[3, 3, 9], \[9, 9, 8]]}}> : tensor<4x3xi32>) constant : !fir.array<3x4xi32>
-
-! a3 array constructor
-! CHECK: fir.global internal @_QQro.2x3x4xi4.{{.*}}(dense<{{\[\[\[1, 1], \[2, 2], \[3, 3]], \[\[4, 4], \[5, 5], \[6, 6]], \[\[7, 7], \[8, 8], \[9, 9]], \[\[10, 10], \[11, 11], \[12, 12]]]}}> : tensor<4x3x2xi32>) constant : !fir.array<2x3x4xi32>
+! CHECK: fir.global internal @_QQro.3x4xi4.{{.*}} constant : !fir.array<3x4xi32> {
+ ! CHECK-DAG: %[[c1_i32:.*]] = arith.constant 1 : i32
+ ! CHECK-DAG: %[[c3_i32:.*]] = arith.constant 3 : i32
+ ! CHECK-DAG: %[[c5_i32:.*]] = arith.constant 5 : i32
+ ! CHECK-DAG: %[[c8_i32:.*]] = arith.constant 8 : i32
+ ! CHECK-DAG: %[[c9_i32:.*]] = arith.constant 9 : i32
+ ! CHECK: %[[r1:.*]] = fir.insert_value %{{.*}}, %{{.*}}, [0 : index, 0 : index] :
+ ! CHECK: %[[r2:.*]] = fir.insert_on_range %[[r1]], %[[c3_i32]] from (1, 0) to (2, 0) :
+ ! CHECK: %[[r3:.*]] = fir.insert_value %[[r2]], %{{.*}}, [0 : index, 1 : index] :
+ ! CHECK: %[[r4:.*]] = fir.insert_on_range %[[r3]], %[[c3_i32]] from (1, 1) to (1, 2) :
+ ! CHECK: %[[r5:.*]] = fir.insert_on_range %[[r4]], %[[c9_i32]] from (2, 2) to (1, 3) :
+ ! CHECK: %[[r6:.*]] = fir.insert_value %[[r5]], %{{.*}}, [2 : index, 3 : index] :
! CHECK-LABEL rangeGlobal
subroutine rangeGlobal()
@@ -129,15 +137,6 @@ subroutine rangeGlobal()
end subroutine rangeGlobal
-! CHECK-LABEL hugeGlobal
-subroutine hugeGlobal()
- integer, parameter :: D = 500
- integer, dimension(D, D) :: a
-
-! CHECK: fir.global internal @_QQro.500x500xi4.{{.*}}(dense<{{.*}}> : tensor<500x500xi32>) constant : !fir.array<500x500xi32>
- a = reshape((/(i, i = 1, D * D)/), shape(a))
-end subroutine hugeGlobal
-
block data
real(selected_real_kind(6)) :: x(5,5)
common /block/ x
diff --git a/flang/test/Lower/dense-array-any-rank.f90 b/flang/test/Lower/dense-array-any-rank.f90
deleted file mode 100644
index 437fdec2da10..000000000000
--- a/flang/test/Lower/dense-array-any-rank.f90
+++ /dev/null
@@ -1,25 +0,0 @@
-! RUN: bbc -emit-fir -o - %s | FileCheck --check-prefixes="CHECK-FIR" %s
-! RUN: %flang_fc1 -emit-llvm -o - %s | FileCheck --check-prefixes="CHECK-LLVMIR" %s
-
-! CHECK-LABEL: test
-subroutine test()
- integer, dimension(10) :: a1
- integer, dimension(3,4) :: a2
- integer, dimension(2,3,4) :: a3
-
- a1 = (/1, 2, 3, 4, 5, 6, 7, 8, 9, 10/)
- a2 = reshape((/11, 12, 13, 21, 22, 23, 31, 32, 33, 41, 42, 43/), shape(a2))
- a3 = reshape((/111, 112, 121, 122, 131, 132, 211, 212, 221, 222, 231, 232, 311, 312, 321, 322, 331, 332, 411, 412, 421, 422, 431, 432/), shape(a3))
-end subroutine
-
-! a1 array constructor
-! CHECK-FIR: fir.global internal @_QQro.10xi4.{{.*}}(dense<[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]> : tensor<10xi32>) constant : !fir.array<10xi32>
-! CHECK-LLVMIR: @_QQro.10xi4.0 = internal constant [10 x i32] [i32 1, i32 2, i32 3, i32 4, i32 5, i32 6, i32 7, i32 8, i32 9, i32 10]
-
-! a2 array constructor
-! CHECK-FIR: fir.global internal @_QQro.3x4xi4.{{.*}}(dense<{{\[\[11, 12, 13], \[21, 22, 23], \[31, 32, 33], \[41, 42, 43]]}}> : tensor<4x3xi32>) constant : !fir.array<3x4xi32>
-! CHECK-LLVMIR: @_QQro.3x4xi4.1 = internal constant [4 x [3 x i32]] {{\[\[3 x i32] \[i32 11, i32 12, i32 13], \[3 x i32] \[i32 21, i32 22, i32 23], \[3 x i32] \[i32 31, i32 32, i32 33], \[3 x i32] \[i32 41, i32 42, i32 43]]}}
-
-! a3 array constructor
-! CHECK-FIR: fir.global internal @_QQro.2x3x4xi4.{{.*}}(dense<{{\[\[\[111, 112], \[121, 122], \[131, 132]], \[\[211, 212], \[221, 222], \[231, 232]], \[\[311, 312], \[321, 322], \[331, 332]], \[\[411, 412], \[421, 422], \[431, 432]]]}}> : tensor<4x3x2xi32>) constant : !fir.array<2x3x4xi32>
-! CHECK-LLVMIR: @_QQro.2x3x4xi4.2 = internal constant [4 x [3 x [2 x i32]]] {{\[\[3 x \[2 x i32]] \[\[2 x i32] \[i32 111, i32 112], \[2 x i32] \[i32 121, i32 122], \[2 x i32] \[i32 131, i32 132]], \[3 x \[2 x i32]] \[\[2 x i32] \[i32 211, i32 212], \[2 x i32] \[i32 221, i32 222], \[2 x i32] \[i32 231, i32 232]], \[3 x \[2 x i32]] \[\[2 x i32] \[i32 311, i32 312], \[2 x i32] \[i32 321, i32 322], \[2 x i32] \[i32 331, i32 332]], \[3 x \[2 x i32]] \[\[2 x i32] \[i32 411, i32 412], \[2 x i32] \[i32 421, i32 422], \[2 x i32] \[i32 431, i32 432]]]}}
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