[MLIR][Tensor] Clean-up `ops.mlir` test (NFC)

Split input file was not used.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D138009

diff --git a/mlir/test/Dialect/Tensor/ops.mlir b/mlir/test/Dialect/Tensor/ops.mlir
index 4afe128..a561726 100644 (file)
--- a/mlir/test/Dialect/Tensor/ops.mlir
+++ b/mlir/test/Dialect/Tensor/ops.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt <%s | mlir-opt | FileCheck %s
+// RUN: mlir-opt %s | mlir-opt | FileCheck %s
 
 // CHECK-LABEL: func @cast(
 func.func @cast(%arg0: tensor<*xf32>, %arg1 : tensor<4x4xf32>, %arg2: tensor<?x?xf32>) {
@@ -29,7 +29,6 @@ func.func @empty_with_encoding(%sz: index) -> tensor<5x?x6xf32, "foo"> {
   return %0 : tensor<5x?x6xf32, "foo">
 }
 
-
 // CHECK-LABEL:   func @extract(
 // CHECK-SAME:                  %[[TENSOR:.*]]: tensor<?x?x?xf32>,
 // CHECK-SAME:                  %[[INDEX:.*]]: index) {
@@ -121,8 +120,6 @@ func.func @slice(%t: tensor<8x16x4xf32>, %idx : index) {
   return
 }
 
-// -----
-
 // CHECK-LABEL: func @insert_slice({{.*}}) {
 func.func @insert_slice(
     %t: tensor<8x16x4xf32>,
@@ -157,8 +154,6 @@ func.func @insert_slice(
   return
 }
 
-// -----
-
 func.func @tensor_reshape_zero_dim(%arg0 : tensor<1x1xf32>, %arg1 : tensor<f32>)
     -> (tensor<f32>, tensor<1x1xf32>) {
   %0 = tensor.collapse_shape %arg0 [] : tensor<1x1xf32> into tensor<f32>
@@ -180,8 +175,6 @@ func.func @legal_collapsing_reshape_dynamic_tensor
 //      CHECK:   tensor.collapse_shape
 // CHECK-SAME:    [0], [1], [2, 3, 4]
 
-// -----
-
 func.func @rank(%t : tensor<4x4x?xf32>) {
   // CHECK: %{{.*}} = tensor.rank %{{.*}} : tensor<4x4x?xf32>
   %0 = "tensor.rank"(%t) : (tensor<4x4x?xf32>) -> index
@@ -191,8 +184,6 @@ func.func @rank(%t : tensor<4x4x?xf32>) {
   return
 }
 
-// -----
-
 func.func @pad_dynamic(%arg0: tensor<1x2x2x?xf32>, %low: index, %high: index,
                   %pad_value: f32) -> tensor<6x?x?x?xf32> {
   %0 = tensor.pad %arg0 low[2, %low, 3, 3] high[3, 3, %high, 2] {
@@ -210,8 +201,6 @@ func.func @pad_dynamic(%arg0: tensor<1x2x2x?xf32>, %low: index, %high: index,
 //  CHECK-SAME:     high[3, 3, %[[HIGH]], 2]
 //       CHECK:    : tensor<1x2x2x?xf32> to tensor<6x?x?x?xf32>
 
-// -----
-
 func.func @pad_static(%arg0: tensor<3x4xf32>, %pad_value: f32) -> tensor<6x9xf32> {
   %0 = tensor.pad %arg0 low[1, 2] high[2, 3] {
     ^bb0(%arg1 : index, %arg2 : index):
@@ -224,8 +213,6 @@ func.func @pad_static(%arg0: tensor<3x4xf32>, %pad_value: f32) -> tensor<6x9xf32
 //       CHECK:   tensor.pad %[[ARG0]] low[1, 2] high[2, 3]
 //       CHECK:    : tensor<3x4xf32> to tensor<6x9xf32>
 
-// -----
-
 func.func @pad_asymmetrical(%arg0: tensor<2x3xf32>, %ub0: index, %ub1: index,
                        %pad_value: f32) -> tensor<?x?xf32> {
   %0 = tensor.pad %arg0 low[0, 0] high[%ub0, %ub1] {
@@ -243,8 +230,6 @@ func.func @pad_asymmetrical(%arg0: tensor<2x3xf32>, %ub0: index, %ub1: index,
 //  CHECK-SAME:     high[%[[UB0]], %[[UB1]]]
 //       CHECK:    : tensor<2x3xf32> to tensor<?x?xf32>
 
-// -----
-
 func.func @pad_to_static_size(%arg0: tensor<?x?xf32>, %ub0: index, %ub1: index,
                          %pad_value: f32) -> tensor<2x3xf32> {
   %0 = tensor.pad %arg0 low[0, 0] high[%ub0, %ub1] {
@@ -262,8 +247,6 @@ func.func @pad_to_static_size(%arg0: tensor<?x?xf32>, %ub0: index, %ub1: index,
 //  CHECK-SAME:     high[%[[UB0]], %[[UB1]]]
 //       CHECK:    : tensor<?x?xf32> to tensor<2x3xf32>
 
-// -----
-
 // CHECK-LABEL: func @test_splat_op
 // CHECK-SAME: [[S:%arg[0-9]+]]: f32
 func.func @test_splat_op(%s : f32) {
@@ -275,19 +258,24 @@ func.func @test_splat_op(%s : f32) {
   return
 }
 
-// -----
-
-// CHECK-LABEL: func @gather_scatter
+// CHECK-LABEL: func.func @gather_scatter(
+// CHECK-SAME:  %[[ARG0:.*]]: tensor<4x5x6xf32>,
+// CHECK-SAME:  %[[ARG1:.*]]: tensor<1x3x2xindex>,
+// CHECK-SAME:  %[[ARG2:.*]]: tensor<1x3x2xi32>) {
 func.func @gather_scatter(
     %dest : tensor<4x5x6xf32>, %indices: tensor<1x3x2xindex>, %indices_i32: tensor<1x3x2xi32>) {
+  // CHECK: %[[GATHER:.*]] = tensor.gather %[[ARG0]][%[[ARG2]]] gather_dims([1, 2]) unique : (tensor<4x5x6xf32>, tensor<1x3x2xi32>) -> tensor<1x3x4x1x1xf32>
   %gathered = tensor.gather %dest[%indices_i32] gather_dims([1, 2]) unique:
     (tensor<4x5x6xf32>, tensor<1x3x2xi32>) -> tensor<1x3x4x1x1xf32>
+  // CHECK: %[[GATHER0:.*]] = tensor.gather %[[ARG0]][%[[ARG1]]] gather_dims([1, 2]) unique : (tensor<4x5x6xf32>, tensor<1x3x2xindex>) -> tensor<1x3x4xf32>
   %rank_reduced_gathered = tensor.gather %dest[%indices] gather_dims([1, 2]) unique:
     (tensor<4x5x6xf32>, tensor<1x3x2xindex>) -> tensor<1x3x4xf32>
 
+  // CHECK: %{{.*}} = tensor.scatter %[[GATHER]] into %[[ARG0]][%[[ARG1]]] scatter_dims([1, 2]) unique : (tensor<1x3x4x1x1xf32>, tensor<4x5x6xf32>, tensor<1x3x2xindex>) -> tensor<4x5x6xf32>
   %scattered = tensor.scatter %gathered into %dest[%indices] 
       scatter_dims([1, 2]) unique:
     (tensor<1x3x4x1x1xf32>, tensor<4x5x6xf32>, tensor<1x3x2xindex>) -> tensor<4x5x6xf32>
+  // CHECK: %{{.*}} = tensor.scatter %[[GATHER0]] into %[[ARG0]][%[[ARG2]]] scatter_dims([1, 2]) unique : (tensor<1x3x4xf32>, tensor<4x5x6xf32>, tensor<1x3x2xi32>) -> tensor<4x5x6xf32>
   %rank_reduced_scattered = tensor.scatter %rank_reduced_gathered into %dest[%indices_i32] 
       scatter_dims([1, 2]) unique:
     (tensor<1x3x4xf32>, tensor<4x5x6xf32>, tensor<1x3x2xi32>) -> tensor<4x5x6xf32>