clean up

Author: nbpatel

mlir/test/Dialect/XeGPU/xegpu-wg-to-sg-unify-ops.mlir

@@ -370,8 +370,8 @@ gpu.module @test_distribution {
   // CHECK-SAME: %[[ARG_0:.*]]: memref<256x128xf32>
   gpu.func @vector_reduce(%src: memref<256x128xf32>) {
     // CHECK: %[[CST:.*]] = arith.constant dense<1.000000e+00> : vector<32xf32>
-    // CHECK: %[[TDESC:.*]] = xegpu.create_nd_tdesc %[[ARG_0]][{{%.*}}, {{%.*}}] : memref<256x128xf32> -> !xegpu.tensor_desc<32x32xf32, #xegpu.layout<lane_layout = [8, 4], lane_data = [1, 1]>>
-    // CHECK: %[[LOAD:.*]] = xegpu.load_nd %[[TDESC]] : !xegpu.tensor_desc<32x32xf32, #xegpu.layout<lane_layout = [8, 4], lane_data = [1, 1]>> -> vector<32x32xf32>
+    // CHECK: %[[TDESC:.*]] = xegpu.create_nd_tdesc %[[ARG_0]][{{%.*}}, {{%.*}}] : memref<256x128xf32> -> !xegpu.tensor_desc<32x32xf32>
+    // CHECK: %[[LOAD:.*]] = xegpu.load_nd %[[TDESC]] : !xegpu.tensor_desc<32x32xf32>
     // CHECK: %[[REDUCE:.*]] = vector.multi_reduction <add>, {{%.*}}, %[[CST]] [0] : vector<32x32xf32> to vector<32xf32>
     // CHECK: %[[SHAPECAST:.*]] = vector.shape_cast %[[REDUCE]] : vector<32xf32> to vector<1x32xf32>
     // CHECK: %[[ALLOCA:.*]] = memref.alloca() : memref<4096xi8, 3>
@@ -396,9 +396,9 @@ gpu.module @test_distribution {
     // CHECK: %[[REDUCE:.*]] = vector.multi_reduction <add>, %[[LOAD]], %[[CST]] [0] : vector<8x4xf32> to vector<4xf32>
     %cst = arith.constant {layout_result_0 = #xegpu.slice<#xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32]>, dims = [0]>} dense<1.0> : vector<128xf32>
     %tdesc = xegpu.create_nd_tdesc %src[0, 0] : memref<256x128xf32>
-      -> !xegpu.tensor_desc<256x128xf32, #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32], lane_layout = [8, 4], lane_data = [1, 1]>>
+      -> !xegpu.tensor_desc<256x128xf32, #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32]>>
     %load =  xegpu.load_nd %tdesc
-      : !xegpu.tensor_desc<256x128xf32, #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32], lane_layout = [8, 4], lane_data = [1, 1]>>
+      : !xegpu.tensor_desc<256x128xf32, #xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32]>>
       -> vector<256x128xf32>
     %reduce = vector.multi_reduction <add>, %load, %cst {layout_result_0 = #xegpu.slice<#xegpu.layout<sg_layout = [8, 4], sg_data = [32, 32]>, dims = [0]>} [0]
       : vector<256x128xf32> to vector<128xf32>