diff --git a/mlir/test/Dialect/Linalg/sparse_nd.mlir b/mlir/test/Dialect/Linalg/sparse_nd.mlir --- a/mlir/test/Dialect/Linalg/sparse_nd.mlir +++ b/mlir/test/Dialect/Linalg/sparse_nd.mlir @@ -20,28 +20,28 @@ } // CHECK-LABEL: func @mul( -// CHECK-SAME: %[[VAL_0:.*0]]: tensor<100x200x300x400x500x600x700x800xf32>, -// CHECK-SAME: %[[VAL_1:.*1]]: tensor<100x200x300x400x500x600x700x800xf32>, -// CHECK-SAME: %[[VAL_2:.*2]]: tensor<100x200x300x400x500x600x700x800xf32>) -> tensor<100x200x300x400x500x600x700x800xf32> { +// CHECK-SAME: %[[VAL_0:.*0]]: tensor<10x20x30x40x50x60x70x80xf32>, +// CHECK-SAME: %[[VAL_1:.*1]]: tensor<10x20x30x40x50x60x70x80xf32>, +// CHECK-SAME: %[[VAL_2:.*2]]: tensor<10x20x30x40x50x60x70x80xf32>) -> tensor<10x20x30x40x50x60x70x80xf32> { // CHECK: %[[VAL_3:.*]] = constant 3 : index // CHECK: %[[VAL_4:.*]] = constant 4 : index -// CHECK: %[[VAL_5:.*]] = constant 100 : index -// CHECK: %[[VAL_6:.*]] = constant 200 : index -// CHECK: %[[VAL_7:.*]] = constant 300 : index -// CHECK: %[[VAL_8:.*]] = constant 600 : index -// CHECK: %[[VAL_9:.*]] = constant 700 : index -// CHECK: %[[VAL_10:.*]] = constant 800 : index +// CHECK: %[[VAL_5:.*]] = constant 10 : index +// CHECK: %[[VAL_6:.*]] = constant 20 : index +// CHECK: %[[VAL_7:.*]] = constant 30 : index +// CHECK: %[[VAL_8:.*]] = constant 60 : index +// CHECK: %[[VAL_9:.*]] = constant 70 : index +// CHECK: %[[VAL_10:.*]] = constant 80 : index // CHECK: %[[VAL_11:.*]] = constant 0 : index // CHECK: %[[VAL_12:.*]] = constant 1 : index -// CHECK: %[[VAL_13:.*]] = tensor_to_memref %[[VAL_0]] : memref<100x200x300x400x500x600x700x800xf32> -// CHECK: %[[VAL_14:.*]] = linalg.sparse_pointers %[[VAL_1]], %[[VAL_3]] : tensor<100x200x300x400x500x600x700x800xf32> to memref -// CHECK: %[[VAL_15:.*]] = linalg.sparse_indices %[[VAL_1]], %[[VAL_3]] : tensor<100x200x300x400x500x600x700x800xf32> to memref -// CHECK: %[[VAL_16:.*]] = linalg.sparse_pointers %[[VAL_1]], %[[VAL_4]] : tensor<100x200x300x400x500x600x700x800xf32> to memref -// CHECK: %[[VAL_17:.*]] = linalg.sparse_indices %[[VAL_1]], %[[VAL_4]] : tensor<100x200x300x400x500x600x700x800xf32> to memref -// CHECK: %[[VAL_18:.*]] = linalg.sparse_values %[[VAL_1]] : tensor<100x200x300x400x500x600x700x800xf32> to memref -// CHECK: %[[VAL_19:.*]] = tensor_to_memref %[[VAL_2]] : memref<100x200x300x400x500x600x700x800xf32> -// CHECK: %[[VAL_20:.*]] = alloc() : memref<100x200x300x400x500x600x700x800xf32> -// CHECK: linalg.copy(%[[VAL_19]], %[[VAL_20]]) : memref<100x200x300x400x500x600x700x800xf32>, memref<100x200x300x400x500x600x700x800xf32> +// CHECK: %[[VAL_13:.*]] = tensor_to_memref %[[VAL_0]] : memref<10x20x30x40x50x60x70x80xf32> +// CHECK: %[[VAL_14:.*]] = linalg.sparse_pointers %[[VAL_1]], %[[VAL_3]] : tensor<10x20x30x40x50x60x70x80xf32> to memref +// CHECK: %[[VAL_15:.*]] = linalg.sparse_indices %[[VAL_1]], %[[VAL_3]] : tensor<10x20x30x40x50x60x70x80xf32> to memref +// CHECK: %[[VAL_16:.*]] = linalg.sparse_pointers %[[VAL_1]], %[[VAL_4]] : tensor<10x20x30x40x50x60x70x80xf32> to memref +// CHECK: %[[VAL_17:.*]] = linalg.sparse_indices %[[VAL_1]], %[[VAL_4]] : tensor<10x20x30x40x50x60x70x80xf32> to memref +// CHECK: %[[VAL_18:.*]] = linalg.sparse_values %[[VAL_1]] : tensor<10x20x30x40x50x60x70x80xf32> to memref +// CHECK: %[[VAL_19:.*]] = tensor_to_memref %[[VAL_2]] : memref<10x20x30x40x50x60x70x80xf32> +// CHECK: %[[VAL_20:.*]] = alloc() : memref<10x20x30x40x50x60x70x80xf32> +// CHECK: linalg.copy(%[[VAL_19]], %[[VAL_20]]) : memref<10x20x30x40x50x60x70x80xf32>, memref<10x20x30x40x50x60x70x80xf32> // CHECK: scf.for %[[VAL_21:.*]] = %[[VAL_11]] to %[[VAL_10]] step %[[VAL_12]] { // CHECK: scf.for %[[VAL_22:.*]] = %[[VAL_11]] to %[[VAL_9]] step %[[VAL_12]] { // CHECK: %[[VAL_23:.*]] = muli %[[VAL_21]], %[[VAL_9]] : index @@ -68,10 +68,10 @@ // CHECK: scf.for %[[VAL_44:.*]] = %[[VAL_11]] to %[[VAL_5]] step %[[VAL_12]] { // CHECK: %[[VAL_45:.*]] = muli %[[VAL_43]], %[[VAL_5]] : index // CHECK: %[[VAL_46:.*]] = addi %[[VAL_45]], %[[VAL_44]] : index -// CHECK: %[[VAL_47:.*]] = load %[[VAL_13]]{{\[}}%[[VAL_44]], %[[VAL_41]], %[[VAL_38]], %[[VAL_37]], %[[VAL_32]], %[[VAL_25]], %[[VAL_22]], %[[VAL_21]]] : memref<100x200x300x400x500x600x700x800xf32> +// CHECK: %[[VAL_47:.*]] = load %[[VAL_13]]{{\[}}%[[VAL_44]], %[[VAL_41]], %[[VAL_38]], %[[VAL_37]], %[[VAL_32]], %[[VAL_25]], %[[VAL_22]], %[[VAL_21]]] : memref<10x20x30x40x50x60x70x80xf32> // CHECK: %[[VAL_48:.*]] = load %[[VAL_18]]{{\[}}%[[VAL_46]]] : memref // CHECK: %[[VAL_49:.*]] = mulf %[[VAL_47]], %[[VAL_48]] : f32 -// CHECK: store %[[VAL_49]], %[[VAL_20]]{{\[}}%[[VAL_44]], %[[VAL_41]], %[[VAL_38]], %[[VAL_37]], %[[VAL_32]], %[[VAL_25]], %[[VAL_22]], %[[VAL_21]]] : memref<100x200x300x400x500x600x700x800xf32> +// CHECK: store %[[VAL_49]], %[[VAL_20]]{{\[}}%[[VAL_44]], %[[VAL_41]], %[[VAL_38]], %[[VAL_37]], %[[VAL_32]], %[[VAL_25]], %[[VAL_22]], %[[VAL_21]]] : memref<10x20x30x40x50x60x70x80xf32> // CHECK: } // CHECK: } // CHECK: } @@ -80,20 +80,20 @@ // CHECK: } // CHECK: } // CHECK: } -// CHECK: %[[VAL_50:.*]] = tensor_load %[[VAL_20]] : memref<100x200x300x400x500x600x700x800xf32> -// CHECK: return %[[VAL_50]] : tensor<100x200x300x400x500x600x700x800xf32> +// CHECK: %[[VAL_50:.*]] = tensor_load %[[VAL_20]] : memref<10x20x30x40x50x60x70x80xf32> +// CHECK: return %[[VAL_50]] : tensor<10x20x30x40x50x60x70x80xf32> // CHECK: } -func @mul(%arga: tensor<100x200x300x400x500x600x700x800xf32>, - %argb: tensor<100x200x300x400x500x600x700x800xf32>, - %argx: tensor<100x200x300x400x500x600x700x800xf32>) - -> tensor<100x200x300x400x500x600x700x800xf32> { +func @mul(%arga: tensor<10x20x30x40x50x60x70x80xf32>, + %argb: tensor<10x20x30x40x50x60x70x80xf32>, + %argx: tensor<10x20x30x40x50x60x70x80xf32>) + -> tensor<10x20x30x40x50x60x70x80xf32> { %0 = linalg.generic #trait_mul - ins(%arga, %argb: tensor<100x200x300x400x500x600x700x800xf32>, - tensor<100x200x300x400x500x600x700x800xf32>) - outs(%argx: tensor<100x200x300x400x500x600x700x800xf32>) { + ins(%arga, %argb: tensor<10x20x30x40x50x60x70x80xf32>, + tensor<10x20x30x40x50x60x70x80xf32>) + outs(%argx: tensor<10x20x30x40x50x60x70x80xf32>) { ^bb(%a: f32, %b: f32, %x: f32): %0 = mulf %a, %b : f32 linalg.yield %0 : f32 - } -> tensor<100x200x300x400x500x600x700x800xf32> - return %0 : tensor<100x200x300x400x500x600x700x800xf32> + } -> tensor<10x20x30x40x50x60x70x80xf32> + return %0 : tensor<10x20x30x40x50x60x70x80xf32> }