75e5f0aac9
After the MemRef has been split out of the Standard dialect, the conversion to the LLVM dialect remained as a huge monolithic pass. This is undesirable for the same complexity management reasons as having a huge Standard dialect itself, and is even more confusing given the existence of a separate dialect. Extract the conversion of the MemRef dialect operations to LLVM into a separate library and a separate conversion pass. Reviewed By: herhut, silvas Differential Revision: https://reviews.llvm.org/D105625
25 lines
1017 B
MLIR
25 lines
1017 B
MLIR
// RUN: mlir-opt %s -linalg-bufferize -std-bufferize \
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// RUN: -tensor-constant-bufferize -tensor-bufferize -func-bufferize \
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// RUN: -finalizing-bufferize \
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// RUN: -convert-linalg-to-loops -convert-scf-to-std -convert-linalg-to-llvm --convert-memref-to-llvm -convert-std-to-llvm | \
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// RUN: mlir-cpu-runner -e main -entry-point-result=void \
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// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext \
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// RUN: | FileCheck %s
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func @main() {
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%const = constant dense<10.0> : tensor<2xf32>
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%insert_val = constant dense<20.0> : tensor<1xf32>
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%inserted = tensor.insert_slice %insert_val into %const[0][1][1] : tensor<1xf32> into tensor<2xf32>
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%unranked = tensor.cast %inserted : tensor<2xf32> to tensor<*xf32>
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call @print_memref_f32(%unranked) : (tensor<*xf32>) -> ()
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// CHECK: Unranked Memref base@ = {{0x[-9a-f]*}}
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// CHECK-SAME: rank = 1 offset = 0 sizes = [2] strides = [1] data =
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// CHECK-NEXT: [20, 10]
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return
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}
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func private @print_memref_f32(%ptr : tensor<*xf32>)
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