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// RUN: mlir-opt -test-linalg-pad-fusion -split-input-file %s | FileCheck %s
func.func @dynamic_pad_fusion(%arg0 : tensor<?x?xf32>, %arg1 : index, %arg2 : index,
%arg3 : index, %arg4 : index, %arg5 : f32) -> tensor<?x?xf32> {
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%d0 = tensor.dim %arg0, %c0 : tensor<?x?xf32>
%d1 = tensor.dim %arg0, %c1 : tensor<?x?xf32>
%init = tensor.empty(%d0, %d1) : tensor<?x?xf32>
%0 = linalg.generic {
indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>],
iterator_types = ["parallel", "parallel"]}
ins(%arg0 : tensor<?x?xf32>) outs(%init : tensor<?x?xf32>) {
^bb0(%arg6 : f32, %arg7 : f32):
%1 = arith.mulf %arg6, %arg6 : f32
linalg.yield %1 : f32
} -> tensor<?x?xf32>
%1 = tensor.pad %0 low [%arg1, %arg2] high [%arg3, %arg4] {
^bb0(%arg6: index, %arg7 : index):
tensor.yield %arg5 : f32
} : tensor<?x?xf32> to tensor<?x?xf32>
return %1 : tensor<?x?xf32>
}
// CHECK-DAG: #[[MAP:.+]] = affine_map<()[s0, s1, s2] -> (s0 + s1 + s2)>
// CHECK: func @dynamic_pad_fusion
// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG4:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG5:[a-zA-Z0-9]+]]: f32
// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[SOURCE:.+]] = linalg.generic
// CHECK-DAG: %[[SOURCE_D0:.+]] = tensor.dim %[[SOURCE]], %[[C0]]
// CHECK-DAG: %[[TARGET_D0:.+]] = affine.apply #[[MAP]]()[%[[ARG1]], %[[ARG3]], %[[SOURCE_D0]]]
// CHECK-DAG: %[[SOURCE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]
// CHECK-DAG: %[[TARGET_D1:.+]] = affine.apply #[[MAP]]()[%[[ARG2]], %[[ARG4]], %[[SOURCE_D1]]]
// CHECK: %[[INIT:.+]] = tensor.empty(%[[TARGET_D0]], %[[TARGET_D1]])
// CHECK: %[[FILL:.+]] = linalg.fill ins(%[[ARG5]]{{.*}}outs(%[[INIT]]
// CHECK-DAG: %[[SIZE_D0:.+]] = tensor.dim %[[SOURCE]], %[[C0]]
// CHECK-DAG: %[[SIZE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]
// CHECK: %[[SLICE:.+]] = tensor.extract_slice %[[FILL]]
// CHECK-SAME: [%[[ARG1]], %[[ARG2]]] [%[[SIZE_D0]], %[[SIZE_D1]]] [1, 1]
// CHECK: %[[SOURCE:.+]] = linalg.generic
// CHECK-SAME: outs(%[[SLICE]] : tensor<?x?xf32>)
// CHECK: %[[RESULT:.+]] = tensor.insert_slice %[[SOURCE]] into %[[FILL]]
// CHECK-SAME: [%[[ARG1]], %[[ARG2]]] [%[[SIZE_D0]], %[[SIZE_D1]]] [1, 1]
// CHECK: return %[[RESULT]]
// -----
func.func @mixed_pad_fusion(%arg0 : tensor<?x42xf32>, %arg1 : index, %arg2 : index,
%arg3 : f32) -> tensor<49x?xf32> {
%c0 = arith.constant 0 : index
%d0 = tensor.dim %arg0, %c0 : tensor<?x42xf32>
%init = tensor.empty(%d0) : tensor<42x?xf32>
%0 = linalg.generic {
indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d1, d0)>],
iterator_types = ["parallel", "parallel"]}
ins(%arg0 : tensor<?x42xf32>) outs(%init : tensor<42x?xf32>) {
^bb0(%arg4 : f32, %arg5 : f32):
%1 = arith.mulf %arg4, %arg4 : f32
linalg.yield %1 : f32
} -> tensor<42x?xf32>
%1 = tensor.pad %0 low [3, %arg1] high [4, %arg2] {
^bb0(%arg4: index, %arg5 : index):
tensor.yield %arg3 : f32
} : tensor<42x?xf32> to tensor<49x?xf32>
return %1 : tensor<49x?xf32>
}
// CHECK-DAG: #[[MAP:.+]] = affine_map<()[s0, s1, s2] -> (s0 + s1 + s2)>
// CHECK: func @mixed_pad_fusion
// CHECK-SAME: %[[ARG0:.+]]: tensor<?x42xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: index
// CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: f32
// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[SOURCE:.+]] = linalg.generic
// CHECK-DAG: %[[SOURCE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]
// CHECK-DAG: %[[TARGET_D1:.+]] = affine.apply #[[MAP]]()[%[[ARG1]], %[[ARG2]], %[[SOURCE_D1]]]
// CHECK: %[[INIT:.+]] = tensor.empty(%[[TARGET_D1]])
// CHECK: %[[FILL:.+]] = linalg.fill ins(%[[ARG3]]{{.*}}outs(%[[INIT]]
// CHECK-DAG: %[[SIZE_D1:.+]] = tensor.dim %[[SOURCE]], %[[C1]]
// CHECK: %[[SLICE:.+]] = tensor.extract_slice %[[FILL]]
// CHECK-SAME: [3, %[[ARG1]]] [42, %[[SIZE_D1]]] [1, 1]
// CHECK: %[[SOURCE:.+]] = linalg.generic
// CHECK-SAME: outs(%[[SLICE]] : tensor<42x?xf32>)
// CHECK: %[[RESULT:.+]] = tensor.insert_slice %[[SOURCE]] into %[[FILL]]
// CHECK-SAME: [3, %[[ARG1]]] [42, %[[SIZE_D1]]] [1, 1]
// CHECK: return %[[RESULT]]
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