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// RUN: mlir-opt %s -test-lower-to-arm-sme -test-lower-to-llvm | \
// RUN: %mcr_aarch64_cmd \
// RUN: -e=main -entry-point-result=void \
// RUN: -march=aarch64 -mattr="+sve,+sme" \
// RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils,%arm_sme_abi_shlib,%mlir_arm_runner_utils | \
// RUN: FileCheck %s
#transpose = affine_map<(d0, d1) -> (d1, d0)>
func.func @fill2DMemrefRows(%memref: memref<?x?xf32>) {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%rows = memref.dim %memref, %c0 : memref<?x?xf32>
%cols = memref.dim %memref, %c1 : memref<?x?xf32>
scf.for %i = %c0 to %rows step %c1 {
scf.for %j = %c0 to %cols step %c1 {
%n = arith.addi %i, %c1 : index
%val = arith.index_cast %n : index to i32
%val_f32 = arith.sitofp %val : i32 to f32
memref.store %val_f32, %memref[%i, %j] : memref<?x?xf32>
}
}
return
}
func.func @testTransposedReadWithMask(%maskRows: index, %maskCols: index) {
%in = memref.alloca() : memref<4x16xf32>
%out = memref.alloca() : memref<16x4xf32>
%inDyn = memref.cast %in : memref<4x16xf32> to memref<?x?xf32>
%outDyn = memref.cast %out : memref<16x4xf32> to memref<?x?xf32>
func.call @fill2DMemrefRows(%inDyn) : (memref<?x?xf32>) -> ()
/// A mask so we only read the first maskRows x maskCols portion of %in.
%mask = vector.create_mask %maskRows, %maskCols : vector<[4]x[16]xi1>
%pad = arith.constant 0.0 : f32
%c0 = arith.constant 0 : index
/// A vector.transfer_read with a transpose permutation map. So the input data
/// (and mask) have a [4]x[16] shape, but the output is [16]x[4].
%readTransposed = vector.transfer_read %inDyn[%c0, %c0], %pad, %mask
{permutation_map = #transpose, in_bounds = [true, true]} : memref<?x?xf32>, vector<[16]x[4]xf32>
/// Write the vector back to a memref (that also has a transposed shape).
vector.transfer_write %readTransposed, %outDyn[%c0, %c0] {in_bounds = [true, true]} : vector<[16]x[4]xf32>, memref<?x?xf32>
/// Print the input memref.
vector.print str "Input memref:"
%inUnranked = memref.cast %inDyn : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%inUnranked) : (memref<*xf32>) -> ()
/// Print the result memref.
vector.print str "Masked transposed result:"
%outUnranked = memref.cast %outDyn : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%outUnranked) : (memref<*xf32>) -> ()
return
}
func.func @testTransposedWriteWithMask(%maskRows: index, %maskCols: index) {
%in = memref.alloca() : memref<16x4xf32>
%out = memref.alloca() : memref<4x16xf32>
%c0_f32 = arith.constant 0.0 : f32
linalg.fill ins(%c0_f32 : f32) outs(%out : memref<4x16xf32>)
%inDyn = memref.cast %in : memref<16x4xf32> to memref<?x?xf32>
%outDyn = memref.cast %out : memref<4x16xf32> to memref<?x?xf32>
func.call @fill2DMemrefRows(%inDyn) : (memref<?x?xf32>) -> ()
/// A regular read.
%c0 = arith.constant 0 : index
%read = vector.transfer_read %inDyn[%c0, %c0], %c0_f32 {in_bounds = [true, true]}
: memref<?x?xf32>, vector<[16]x[4]xf32>
/// A mask so we only write the first maskRows x maskCols portion of transpose(%in).
%mask = vector.create_mask %maskRows, %maskCols : vector<[4]x[16]xi1>
/// Write out the data with a transpose. Here (like the read test) the mask
/// matches the shape of the memory, not the vector.
vector.transfer_write %read, %outDyn[%c0, %c0], %mask {permutation_map = #transpose, in_bounds = [true, true]}
: vector<[16]x[4]xf32>, memref<?x?xf32>
/// Print the input memref.
vector.print str "Input memref:"
%inUnranked = memref.cast %inDyn : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%inUnranked) : (memref<*xf32>) -> ()
/// Print the result memref.
vector.print str "Masked transposed result:"
%outUnranked = memref.cast %outDyn : memref<?x?xf32> to memref<*xf32>
call @printMemrefF32(%outUnranked) : (memref<*xf32>) -> ()
return
}
func.func @main() {
/// Set the SVL to 128-bits (i.e. vscale = 1).
/// This test is for the use of multiple tiles rather than scalability.
%c128 = arith.constant 128 : i32
func.call @setArmSVLBits(%c128) : (i32) -> ()
// CHECK: Input memref:
// CHECK: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
// CHECK-NEXT: [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
// CHECK-NEXT: [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
// CHECK-NEXT: [4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4]
//
// CHECK: Masked transposed result:
// CHECK: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [1, 2, 0, 0]
// CHECK-NEXT: [0, 0, 0, 0]
%readMaskRows = arith.constant 2 : index
%readMaskCols = arith.constant 15 : index
func.call @testTransposedReadWithMask(%readMaskRows, %readMaskCols) : (index, index) -> ()
// CHECK: Input memref:
// CHECK: [1, 1, 1, 1]
// CHECK-NEXT: [2, 2, 2, 2]
// CHECK-NEXT: [3, 3, 3, 3]
// CHECK-NEXT: [4, 4, 4, 4]
// CHECK-NEXT: [5, 5, 5, 5]
// CHECK-NEXT: [6, 6, 6, 6]
// CHECK-NEXT: [7, 7, 7, 7]
// CHECK-NEXT: [8, 8, 8, 8]
// CHECK-NEXT: [9, 9, 9, 9]
// CHECK-NEXT: [10, 10, 10, 10]
// CHECK-NEXT: [11, 11, 11, 11]
// CHECK-NEXT: [12, 12, 12, 12]
// CHECK-NEXT: [13, 13, 13, 13]
// CHECK-NEXT: [14, 14, 14, 14]
// CHECK-NEXT: [15, 15, 15, 15]
// CHECK-NEXT: [16, 16, 16, 16]
//
// CHECK: Masked transposed result:
// CHECK: [1, 2, 3, 4, 5, 6, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0]
// CHECK-NEXT: [1, 2, 3, 4, 5, 6, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0]
// CHECK-NEXT: [1, 2, 3, 4, 5, 6, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0]
// CHECK-NEXT: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
%writeMaskRows = arith.constant 3 : index
%writeMaskCols = arith.constant 8 : index
func.call @testTransposedWriteWithMask(%writeMaskRows, %writeMaskCols) : (index, index) -> ()
return
}
func.func private @printMemrefF32(%ptr : memref<*xf32>)
func.func private @setArmSVLBits(%bits : i32)
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