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1 change: 1 addition & 0 deletions mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
Original file line number Diff line number Diff line change
Expand Up @@ -1383,6 +1383,7 @@ def Tosa_ConcatOp : Tosa_Op<"concat", [
);

let hasCanonicalizer = 1;
let hasFolder = 1;
}

//===----------------------------------------------------------------------===//
Expand Down
34 changes: 34 additions & 0 deletions mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -995,3 +995,37 @@ OpFoldResult TransposeOp::fold(ArrayRef<Attribute> operands) {
return getInput1();
return {};
}

OpFoldResult ConcatOp::fold(ArrayRef<Attribute> operands) {
// Fold consecutive concats on the same axis into a single op.
// Keep track of the operands so we are able to construct a new concat
// later. Conservatively assume that we double the number of operands when
// folding
SmallVector<Value, 8> concatOperands;
concatOperands.reserve(2 * getNumOperands());

// Find all operands that are foldable concats
bool canFold = false;
for (Value operand : getOperands()) {
concatOperands.emplace_back(operand);

auto producer = dyn_cast_or_null<ConcatOp>(operand.getDefiningOp());
if (!producer)
continue;

// Foldable if axes are the same
if (getAxis() != producer.getAxis())
continue;

// Replace the original operand with all incoming operands
canFold = true;
concatOperands.pop_back();
llvm::append_range(concatOperands, producer->getOperands());
}

if (!canFold)
return {};

getOperation()->setOperands(concatOperands);
return getResult();
}
93 changes: 93 additions & 0 deletions mlir/test/Dialect/Tosa/fold_concats.mlir
Original file line number Diff line number Diff line change
@@ -0,0 +1,93 @@
// RUN: mlir-opt --split-input-file --canonicalize %s | FileCheck %s

func.func @single_concat(%arg0: tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32> {
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
return %0 : tensor<1x2x7x7xf32>
}

// CHECK-LABEL: func.func @single_concat(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32> {
// CHECK: %[[VAL_1:.*]] = "tosa.concat"(%[[VAL_0]], %[[VAL_0]]) {axis = 1 : i64} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
// CHECK: return %[[VAL_1]] : tensor<1x2x7x7xf32>
// CHECK: }

// -----

func.func @concat_different_axis(%arg0: tensor<1x1x7x7xf32>) -> tensor<2x2x7x7xf32> {
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
%1 = "tosa.concat"(%0, %0) {axis = 0} : (tensor<1x2x7x7xf32>, tensor<1x2x7x7xf32>) -> tensor<2x2x7x7xf32>
return %1 : tensor<2x2x7x7xf32>
}

// CHECK-LABEL: func.func @concat_different_axis(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x7x7xf32>) -> tensor<2x2x7x7xf32> {
// CHECK: %[[VAL_1:.*]] = "tosa.concat"(%[[VAL_0]], %[[VAL_0]]) {axis = 1 : i64} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_1]], %[[VAL_1]]) {axis = 0 : i64} : (tensor<1x2x7x7xf32>, tensor<1x2x7x7xf32>) -> tensor<2x2x7x7xf32>
// CHECK: return %[[VAL_2]] : tensor<2x2x7x7xf32>
// CHECK: }

// -----

func.func @fold_concats(%arg0: tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32> {
%tmp = tensor.empty() : tensor<1x1x7x7xf32>
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
%1 = "tosa.concat"(%tmp, %0, %tmp) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x2x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32>
return %1 : tensor<1x4x7x7xf32>
}

// CHECK-LABEL: func.func @fold_concats(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32> {
// CHECK: %[[VAL_1:.*]] = tensor.empty() : tensor<1x1x7x7xf32>
// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_1]], %[[VAL_0]], %[[VAL_0]], %[[VAL_1]]) {axis = 1 : i64} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32>
// CHECK: return %[[VAL_2]] : tensor<1x4x7x7xf32>
// CHECK: }

// -----

func.func @nested_fold(%arg0: tensor<1x1x7x7xf32>) -> tensor<1x8x7x7xf32> {
%tmp = tensor.empty() : tensor<1x1x7x7xf32>
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
%1 = "tosa.concat"(%tmp, %0, %tmp) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x2x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32>
%2 = "tosa.concat"(%1, %1) {axis = 1} : (tensor<1x4x7x7xf32>, tensor<1x4x7x7xf32>) -> tensor<1x8x7x7xf32>
return %2 : tensor<1x8x7x7xf32>
}

// CHECK-LABEL: func.func @nested_fold(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x7x7xf32>) -> tensor<1x8x7x7xf32> {
// CHECK: %[[VAL_1:.*]] = tensor.empty() : tensor<1x1x7x7xf32>
// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_1]], %[[VAL_0]], %[[VAL_0]], %[[VAL_1]], %[[VAL_1]], %[[VAL_0]], %[[VAL_0]], %[[VAL_1]]) {axis = 1 : i64} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x8x7x7xf32>
// CHECK: return %[[VAL_2]] : tensor<1x8x7x7xf32>
// CHECK: }

// -----

func.func @wide_fold(%arg0: tensor<1x1x7x7xf32>, %arg1: tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32> {
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
%1 = "tosa.concat"(%arg1, %arg1) {axis = 1} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x2x7x7xf32>
%2 = "tosa.concat"(%0, %1) {axis = 1} : (tensor<1x2x7x7xf32>, tensor<1x2x7x7xf32>) -> tensor<1x4x7x7xf32>
return %2 : tensor<1x4x7x7xf32>
}

// CHECK-LABEL: func.func @wide_fold(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x7x7xf32>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32> {
// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_0]], %[[VAL_0]], %[[VAL_1]], %[[VAL_1]]) {axis = 1 : i64} : (tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>, tensor<1x1x7x7xf32>) -> tensor<1x4x7x7xf32>
// CHECK: return %[[VAL_2]] : tensor<1x4x7x7xf32>
// CHECK: }

// -----

func.func @partially_foldable(%arg0: tensor<1x1x8x8xf32>, %arg1: tensor<1x2x4x8xf32>) -> tensor<1x4x8x8xf32> {
%0 = "tosa.concat"(%arg0, %arg0) {axis = 1} : (tensor<1x1x8x8xf32>, tensor<1x1x8x8xf32>) -> tensor<1x2x8x8xf32>
%1 = "tosa.concat"(%arg1, %arg1) {axis = 2} : (tensor<1x2x4x8xf32>, tensor<1x2x4x8xf32>) -> tensor<1x2x8x8xf32>
%2 = "tosa.concat"(%0, %1) {axis = 1} : (tensor<1x2x8x8xf32>, tensor<1x2x8x8xf32>) -> tensor<1x4x8x8xf32>
return %2 : tensor<1x4x8x8xf32>
}

// CHECK-LABEL: func.func @partially_foldable(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x8x8xf32>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x4x8xf32>) -> tensor<1x4x8x8xf32> {
// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_1]], %[[VAL_1]]) {axis = 2 : i64} : (tensor<1x2x4x8xf32>, tensor<1x2x4x8xf32>) -> tensor<1x2x8x8xf32>
// CHECK: %[[VAL_3:.*]] = "tosa.concat"(%[[VAL_0]], %[[VAL_0]], %[[VAL_2]]) {axis = 1 : i64} : (tensor<1x1x8x8xf32>, tensor<1x1x8x8xf32>, tensor<1x2x8x8xf32>) -> tensor<1x4x8x8xf32>
// CHECK: return %[[VAL_3]] : tensor<1x4x8x8xf32>
// CHECK: }