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merged 4 commits into from
Apr 22, 2025
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[mlir][linalg] Add folder for linalg.index #136640

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492439a
[mlir][linalg] Add folder for `linalg.index`
kuhar Apr 22, 2025
b3e5afe
Update test
kuhar Apr 22, 2025
cbcdb33
Simplify
kuhar Apr 22, 2025
12ba5a3
Add assert message
kuhar Apr 22, 2025
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1 change: 1 addition & 0 deletions mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td
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Original file line number Diff line number Diff line change
Expand Up @@ -88,6 +88,7 @@ def Linalg_IndexOp : Linalg_Op<"index", [Pure]>,

let assemblyFormat = [{ $dim attr-dict `:` type($result) }];
let hasVerifier = 1;
let hasFolder = 1;
}

def Linalg_SoftmaxOp : Linalg_Op<"softmax",
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13 changes: 13 additions & 0 deletions mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
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Expand Up @@ -2283,6 +2283,19 @@ LogicalResult IndexOp::verify() {
return success();
}

OpFoldResult IndexOp::fold(FoldAdaptor adaptor) {
auto linalgOp = cast<LinalgOp>((*this)->getParentOp());

// Index of unit dims is always 0.
SmallVector<int64_t, 4> loopBounds = linalgOp.getStaticLoopRanges();
uint64_t dim = getDim();
assert(dim < loopBounds.size() && "Dim is out of bounds");
if (loopBounds[dim] == 1)
return IntegerAttr::get(IndexType::get(getContext()), 0);

return OpFoldResult{};
}

/////// Operations corresponding to library calls defined with Tablegen ////////

#include "mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yamlgen.cpp.inc"
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80 changes: 80 additions & 0 deletions mlir/test/Dialect/Linalg/canonicalize.mlir
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Expand Up @@ -305,6 +305,86 @@ func.func @self_copy(%arg0 : memref<2x3x?x4xf32>) {
}

// -----

// CHECK: func @fold_linalg_index_tensor_static
func.func @fold_linalg_index_tensor_static(%0: tensor<4x16xi32>, %1: tensor<1x16xi32>,
%2: tensor<4x1xi32>) -> tensor<4x1xi32> {
// CHECK-NEXT: linalg.generic
// CHECK: %[[IDX_0:.+]] = linalg.index 0 : index
// CHECK-NOT: linalg.index 1
// CHECK: %[[IDX_2:.+]] = linalg.index 2 : index
// CHECK: %[[ADD:.+]] = arith.addi %[[IDX_0]], %[[IDX_2]]
// CHECK: %[[CAST:.+]] = arith.index_cast %[[ADD]]
// CHECK: linalg.yield %[[CAST]]
%res = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d2)>,
affine_map<(d0, d1, d2) -> (d1, d2)>,
affine_map<(d0, d1, d2) -> (d0, d1)>],
iterator_types = ["parallel", "parallel", "reduction"]}
ins(%0, %1 : tensor<4x16xi32>, tensor<1x16xi32>)
outs(%2 : tensor<4x1xi32>) {
^bb0(%lhs: i32, %rhs: i32, %out: i32):
%idx0 = linalg.index 0 : index
%idx1 = linalg.index 1 : index
%idx2 = linalg.index 2 : index
%add0 = arith.addi %idx0, %idx1 : index
%add1 = arith.addi %add0, %idx2 : index
%int = arith.index_cast %add1 : index to i32
linalg.yield %int : i32
} -> tensor<4x1xi32>
return %res : tensor<4x1xi32>
}

// -----

// CHECK: func @fold_linalg_index_tensor_dynamic
func.func @fold_linalg_index_tensor_dynamic(%0: tensor<?x1xi32>,
%1: tensor<?x1xi32>) -> tensor<?x1xi32> {
// CHECK-NEXT: linalg.generic
// CHECK: %[[IDX_0:.+]] = linalg.index 0 : index
// CHECK-NOT: linalg.index 1
// CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX_0]]
// CHECK: linalg.yield %[[CAST]]
%res = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
affine_map<(d0, d1) -> (d1, d1)>],
iterator_types = ["parallel", "parallel"]}
ins(%0 : tensor<?x1xi32>)
outs(%1 : tensor<?x1xi32>) {
^bb0(%lhs: i32, %out: i32):
%idx0 = linalg.index 0 : index
%idx1 = linalg.index 1 : index
%add = arith.addi %idx0, %idx1 : index
%int = arith.index_cast %add : index to i32
linalg.yield %int : i32
} -> tensor<?x1xi32>
return %res : tensor<?x1xi32>
}

// -----

// CHECK: func @fold_linalg_index_memref
func.func @fold_linalg_index_memref(%0: memref<1x?xi32>, %1: memref<1x?xi32>) {
// CHECK-NEXT: linalg.generic
// CHECK-NOT: linalg.index 0
// CHECK: %[[IDX_1:.+]] = linalg.index 1 : index
// CHECK: %[[CAST:.+]] = arith.index_cast %[[IDX_1]]
// CHECK: linalg.yield %[[CAST]]
linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
affine_map<(d0, d1) -> (d1, d1)>],
iterator_types = ["parallel", "parallel"]}
ins(%0 : memref<1x?xi32>)
outs(%1 : memref<1x?xi32>) {
^bb0(%lhs: i32, %out: i32):
%idx0 = linalg.index 0 : index
%idx1 = linalg.index 1 : index
%add = arith.addi %idx0, %idx1 : index
%int = arith.index_cast %add : index to i32
linalg.yield %int : i32
}
return
}

// -----

// CHECK-LABEL: func @fold_fill_reshape()
func.func @fold_fill_reshape() -> tensor<6x4xf32> {
%zero = arith.constant 0.0 : f32
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5 changes: 2 additions & 3 deletions mlir/test/Dialect/Linalg/vectorize-tensor-extract.mlir
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Expand Up @@ -278,12 +278,11 @@ func.func @vectorize_nd_tensor_extract_load_1d_column_vector_using_gather_load(%
// CHECK: %[[EMPTY:.*]] = tensor.empty() : tensor<8x1xf32>
// CHECK: %[[B1:.*]] = vector.broadcast %[[CST_3]] : vector<8xindex> to vector<1x8xindex>
// CHECK: %[[ADDI_ARG1:.*]] = arith.addi %[[ARG1]], %[[ARG1]] : index
// CHECK: %[[B2:.*]] = vector.broadcast %[[ADDI_ARG1]] : index to vector<1xindex>
// CHECK: %[[MULI_1:.*]] = arith.muli %[[B1]], %[[CST_0]] : vector<1x8xindex>
// CHECK: %[[MULI_2:.*]] = arith.muli %[[MULI_1]], %[[CST]] : vector<1x8xindex>
// CHECK: %[[T:.*]] = vector.transpose %[[MULI_2]], [1, 0] : vector<1x8xindex> to vector<8x1xindex>
// CHECK: %[[B3:.*]] = vector.broadcast %[[B2]] : vector<1xindex> to vector<8x1xindex>
// CHECK: %[[ADDI:.*]] = arith.addi %[[B3]], %[[T]] : vector<8x1xindex>
// CHECK: %[[B2:.*]] = vector.broadcast %[[ADDI_ARG1]] : index to vector<8x1xindex>
// CHECK: %[[ADDI:.*]] = arith.addi %[[B2]], %[[T]] : vector<8x1xindex>
// CHECK: %[[GATHER:.*]] = vector.gather %[[ARG0]][%[[C0]], %[[C0]], %[[C0]]] [%[[ADDI]]], %[[CST_2]], %[[PASSTHRU]] : tensor<8x128x768xf32>, vector<8x1xindex>, vector<8x1xi1>, vector<8x1xf32> into vector<8x1xf32>
// CHECK: vector.transfer_write %[[GATHER]], %[[EMPTY]][%[[C0]], %[[C0]]] {in_bounds = [true, true]} : vector<8x1xf32>, tensor<8x1xf32>

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