foo.mlir

#map0 = affine_map<(d0, d1, d2) -> (d0, d1)>
#map1 = affine_map<(d0, d1, d2) -> (d1, d2)>
#map2 = affine_map<(d0, d1, d2) -> (d0, d2)>
#map3 = affine_map<(d0, d1) -> (d0, d1)>
module  {
  func private @actual(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>) -> tensor<?x?xf32> attributes {noinline} {
    %0 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32>
    return %0 : tensor<?x?xf32>
  }
  func private @expected(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>) -> tensor<?x?xf32> attributes {noinline} {
    %0 = linalg.generic {indexing_maps = [#map0, #map1, #map2], iterator_types = ["parallel", "reduction", "parallel"]} ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%arg2 : tensor<?x?xf32>) {
    ^bb0(%arg3: f32, %arg4: f32, %arg5: f32):  // no predecessors
      %1 = mulf %arg3, %arg4 : f32
      %2 = addf %1, %arg5 : f32
      linalg.yield %2 : f32
    } -> tensor<?x?xf32>
    return %0 : tensor<?x?xf32>
  }
  func @matmul_test() attributes {iree.abi.stub, iree.reflection = {MatmulTest = "entry"}} {
    %c10 = constant 10 : index
    %c10_0 = constant 10 : index
    %0 = linalg.init_tensor [%c10, %c10_0] : tensor<?x?xf32>
    %1 = linalg.generic {indexing_maps = [#map3, #map3], iterator_types = ["parallel", "parallel"]} ins(%0 : tensor<?x?xf32>) outs(%0 : tensor<?x?xf32>) {
    ^bb0(%arg0: f32, %arg1: f32):  // no predecessors
      %8 = linalg.index 0 : index
      %9 = linalg.index 1 : index
      %10 = cmpi eq, %8, %9 : index
      %cst = constant 0.000000e+00 : f32
      %cst_5 = constant 1.000000e+00 : f32
      %11 = select %10, %cst, %cst_5 : f32
      linalg.yield %11 : f32
    } -> tensor<?x?xf32>
    %c10_1 = constant 10 : index
    %c10_2 = constant 10 : index
    %2 = linalg.init_tensor [%c10_1, %c10_2] : tensor<?x?xf32>
    %3 = linalg.generic {indexing_maps = [#map3, #map3], iterator_types = ["parallel", "parallel"]} ins(%2 : tensor<?x?xf32>) outs(%2 : tensor<?x?xf32>) {
    ^bb0(%arg0: f32, %arg1: f32):  // no predecessors
      %8 = linalg.index 0 : index
      %9 = linalg.index 1 : index
      %10 = cmpi eq, %8, %9 : index
      %cst = constant 0.000000e+00 : f32
      %cst_5 = constant 1.000000e+00 : f32
      %11 = select %10, %cst, %cst_5 : f32
      linalg.yield %11 : f32
    } -> tensor<?x?xf32>
    %c10_3 = constant 10 : index
    %c10_4 = constant 10 : index
    %4 = linalg.init_tensor [%c10_3, %c10_4] : tensor<?x?xf32>
    %5 = linalg.generic {indexing_maps = [#map3, #map3], iterator_types = ["parallel", "parallel"]} ins(%4 : tensor<?x?xf32>) outs(%4 : tensor<?x?xf32>) {
    ^bb0(%arg0: f32, %arg1: f32):  // no predecessors
      %8 = linalg.index 0 : index
      %9 = linalg.index 1 : index
      %10 = cmpi eq, %8, %9 : index
      %cst = constant 0.000000e+00 : f32
      %cst_5 = constant 1.000000e+00 : f32
      %11 = select %10, %cst, %cst_5 : f32
      linalg.yield %11 : f32
    } -> tensor<?x?xf32>
    %6 = call @actual(%1, %3, %5) : (tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
    %7 = call @expected(%1, %3, %5) : (tensor<?x?xf32>, tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
    check.expect_eq(%6, %7) : tensor<?x?xf32>
    return
  }
}