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// RUN: mlir-opt %s -test-transform-dialect-interpreter --split-input-file | FileCheck %s
// CHECK-LABEL: func.func @matmul_tensors_1(
func.func @matmul_tensors_1(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>,
%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// This operation is marked for tiling only.
// CHECK-COUNT-3: scf.for
// CHECK-COUNT-3: tensor.extract_slice
// CHECK: linalg.matmul
// CHECK-SAME: -> tensor<4x4xf32>
%0 = linalg.matmul { test.attrA }
ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
func.return %0 : tensor<128x128xf32>
}
func.func @matmul_tensors_2(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>,
%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// This operation is marked f
// This operation is marked for tiling and vectorization.
// CHECK-COUNT-3: scf.for
// CHECK-COUNT-3: vector.transfer_read
// CHECK: vector.contract
// CHECK-NOT: linalg.matmul
// CHECK: vector.transfer_write
%0 = linalg.matmul { test.attrA, test.attrC }
ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
func.return %0 : tensor<128x128xf32>
}
func.func @matmul_tensors_3(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>,
%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// This operation is marked for vectorization only.
// CHECK-NOT: scf.for
// CHECK-COUNT-3: vector.transfer_read
// CHECK: vector.contract
// CHECK-SAME: into vector<128x128xf32>
// CHECK: vector.transfer_write
%0 = linalg.matmul { test.attrC }
ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
func.return %0 : tensor<128x128xf32>
}
transform.with_pdl_patterns {
^bb0(%arg0: !pdl.operation):
// Match matmul operations inside @matmul_tensors with test.attrA set.
pdl.pattern @pdl_target_attrA : benefit(1) {
%args = operands
%results = types
%attr = attribute
%0 = operation "linalg.matmul"(%args : !pdl.range<value>) {"test.attrA" = %attr}-> (%results : !pdl.range<type>)
// TODO: we don't want this, but it is the required terminator for pdl.pattern
rewrite %0 with "transform.dialect"
}
// Match matmul operations inside @matmul_tensors with test.attrC set.
pdl.pattern @pdl_target_attrC : benefit(1) {
%args = operands
%results = types
%attr = attribute
%0 = operation "linalg.matmul"(%args : !pdl.range<value>) {"test.attrC" = %attr}-> (%results : !pdl.range<type>)
// TODO: we don't want this, but it is the required terminator for pdl.pattern
rewrite %0 with "transform.dialect"
}
transform.sequence %arg0 {
^bb1(%arg1: !pdl.operation):
%0 = pdl_match @pdl_target_attrA in %arg1
transform.structured.tile %0 [4, 4, 4]
%1 = pdl_match @pdl_target_attrC in %arg1
%2 = transform.get_closest_isolated_parent %1
transform.structured.vectorize %2
}
}
// -----
// CHECK-LABEL: @vectorize_one
func.func @vectorize_one(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>,
%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// CHECK: vector.contract
%0 = linalg.matmul {test.attrA}
ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
func.return %0 : tensor<128x128xf32>
}
func.func @vectorize_none(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>,
%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// CHECK: linalg.matmul
%0 = linalg.matmul ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
func.return %0 : tensor<128x128xf32>
}
transform.with_pdl_patterns {
^bb0(%arg0: !pdl.operation):
pdl.pattern @pdl_target : benefit(1) {
%args = operands
%results = types
%attr = attribute
%0 = operation "linalg.matmul"(%args : !pdl.range<value>) {"test.attrA" = %attr}-> (%results : !pdl.range<type>)
// TODO: we don't want this, but it is the required terminator for pdl.pattern
rewrite %0 with "transform.dialect"
}
transform.sequence %arg0 {
^bb1(%arg1: !pdl.operation):
%0 = pdl_match @pdl_target in %arg1
%1 = get_closest_isolated_parent %0
transform.structured.vectorize %1
}
}
// -----
// CHECK-LABEL: @vectorize_all
func.func @vectorize_all(
%arg0: tensor<128x128xf32>, %arg1: tensor<128x128xf32>, %arg2: tensor<128x128xf32>,
%arg3: tensor<128x128xf32>)
-> tensor<128x128xf32> {
// CHECK: vector.contract
%0 = linalg.matmul {test.attrA}
ins(%arg0, %arg1: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg2: tensor<128x128xf32>)
-> tensor<128x128xf32>
// CHECK: vector.contract
%1 = linalg.matmul ins(%arg0, %0: tensor<128x128xf32>, tensor<128x128xf32>)
outs(%arg3: tensor<128x128xf32>)
-> tensor<128x128xf32>
return %1 : tensor<128x128xf32>
}
transform.sequence {
^bb0(%arg0: !pdl.operation):
transform.structured.vectorize %arg0
}
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