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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

71 lines
3.2 KiB
MLIR

// RUN: mlir-opt %s --transform-interpreter --split-input-file --verify-diagnostics
func.func @fusable_with_matching_offsets(%arg0: tensor<10x20xf32>, %arg1: tensor<10x20xf32>, %dest: tensor<100x200xf32>) -> tensor<100x200xf32> {
%c0 = arith.constant 0 : index
%c10 = arith.constant 10 : index
%c20 = arith.constant 20 : index
%slice0 = tensor.insert_slice %arg0 into %dest[%c0, %c0] [10, 20] [1, 1] : tensor<10x20xf32> into tensor<100x200xf32>
%slice1 = tensor.insert_slice %arg1 into %dest[%c0, %c0] [10, 20] [1, 1] : tensor<10x20xf32> into tensor<100x200xf32>
// expected-remark @+1 {{can be fused with producer tensor.insert_slice ops}}
%result = linalg.add ins(%slice0, %slice1 : tensor<100x200xf32>, tensor<100x200xf32>)
outs(%dest : tensor<100x200xf32>) -> tensor<100x200xf32>
return %result : tensor<100x200xf32>
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg: !transform.any_op) {
%add = transform.structured.match ops{["linalg.add"]} in %arg : (!transform.any_op) -> !transform.any_op
transform.test.query_producer_fusability %add : !transform.any_op
transform.yield
}
}
// -----
func.func @not_fusable_with_different_offsets(%arg0: tensor<10x20xf32>, %arg1: tensor<10x20xf32>, %dest: tensor<100x200xf32>) -> tensor<100x200xf32> {
%c0 = arith.constant 0 : index
%c10 = arith.constant 10 : index
%c20 = arith.constant 20 : index
%slice0 = tensor.insert_slice %arg0 into %dest[%c0, %c0] [10, 20] [1, 1] : tensor<10x20xf32> into tensor<100x200xf32>
%slice1 = tensor.insert_slice %arg1 into %dest[%c10, %c20] [10, 20] [1, 1] : tensor<10x20xf32> into tensor<100x200xf32>
// expected-remark @+1 {{cannot be fused with producer tensor.insert_slice ops}}
%result = linalg.add ins(%slice0, %slice1 : tensor<100x200xf32>, tensor<100x200xf32>)
outs(%dest : tensor<100x200xf32>) -> tensor<100x200xf32>
return %result : tensor<100x200xf32>
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg: !transform.any_op) {
%add = transform.structured.match ops{["linalg.add"]} in %arg : (!transform.any_op) -> !transform.any_op
transform.test.query_producer_fusability %add : !transform.any_op
transform.yield
}
}
// -----
func.func @fusable_with_consumer_extract_slice(%arg0: tensor<100x200xf32>, %arg1: tensor<100x200xf32>, %dest: tensor<100x200xf32>) -> tensor<10x20xf32> {
// expected-remark @+1 {{can be fused with consumer tensor.extract_slice op}}
%add = linalg.add ins(%arg0, %arg1 : tensor<100x200xf32>, tensor<100x200xf32>)
outs(%dest : tensor<100x200xf32>) -> tensor<100x200xf32>
%c0 = arith.constant 0 : index
%slice = tensor.extract_slice %add[%c0, %c0] [10, 20] [1, 1] : tensor<100x200xf32> to tensor<10x20xf32>
return %slice : tensor<10x20xf32>
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg: !transform.any_op) {
%add = transform.structured.match ops{["linalg.add"]} in %arg : (!transform.any_op) -> !transform.any_op
transform.test.query_consumer_fusability %add : !transform.any_op
transform.yield
}
}