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26 lines
1.1 KiB
MLIR
26 lines
1.1 KiB
MLIR
// RUN: mlir-opt %s -transform-interpreter -split-input-file | FileCheck %s
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// CHECK-LABEL: func @tile_offset
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// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]:
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func.func @tile_offset(%arg0 : tensor<9xf32>) -> tensor<6xf32> {
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%empty = tensor.empty() : tensor<6xf32>
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// CHECK: scf.for %[[ITER:[a-zA-Z0-9_]+]] =
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// CHECK: tensor.extract_slice %[[ARG0]][%[[ITER]]] [6] [1]
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%generic = linalg.generic
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{indexing_maps = [affine_map<(d0) -> (d0 + 3)>,
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affine_map<(d0) -> (d0)>],
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iterator_types = ["parallel"]} ins(%arg0: tensor<9xf32>) outs(%empty : tensor<6xf32>) {
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^bb0(%in : f32, %out: f32):
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linalg.yield %in : f32
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} -> tensor<6xf32>
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return %generic : tensor<6xf32>
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}
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module attributes {transform.with_named_sequence} {
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transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
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%0 = transform.structured.match ops{["linalg.generic"]} in %arg1 : (!transform.any_op) -> !transform.any_op
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%1, %loop = transform.structured.tile_using_for %0 tile_sizes [3] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
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transform.yield
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}
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}
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