cleaner tests

Signed-off-by: dchigarev <[email protected]>

Author: dchigarev

test/mlir/test/gc/Transforms/GPU/linalg-to-xegpu-broadcast-fold.mlir

@@ -77,6 +77,7 @@ func.func @complex_broadcast_3d() {
   %3 = memref.alloc() : memref<7x7x128xf16>
 
   gpu.launch blocks(%arg3, %arg4, %arg5) in (%arg11 = %c2, %arg12 = %c4, %arg13 = %c1) threads(%arg6, %arg7, %arg8) in (%arg14 = %c4, %arg15 = %c1, %arg16 = %c1) {
+    // This broadcast can't be replaced by a single memref.subview. Can't remove it
     // CHECK: linalg.broadcast
     linalg.broadcast ins(%0 : memref<7x128xf16>) outs(%1 : memref<7x7x128xf16>) dimensions = [0]
     linalg.add ins(%1, %2 : memref<7x7x128xf16>, memref<7x7x128xf16>) outs(%3 : memref<7x7x128xf16>)
@@ -99,9 +100,10 @@ func.func @single_broadcast() {
   %1 = memref.alloc() : memref<1x1x7x128xf16>
 
   gpu.launch blocks(%arg3, %arg4, %arg5) in (%arg11 = %c2, %arg12 = %c4, %arg13 = %c1) threads(%arg6, %arg7, %arg8) in (%arg14 = %c4, %arg15 = %c1, %arg16 = %c1) {
+    // broadcast result is not an input of any xegpu operation, we can't lower it
     // CHECK: linalg.broadcast
     linalg.broadcast ins(%0 : memref<7x128xf16>) outs(%1 : memref<1x1x7x128xf16>) dimensions = [0, 1]
     gpu.terminator
   }
   return
-}
+}

test/mlir/test/gc/gpu-runner/XeGPU/rope_sanity_test.mlir

@@ -26,29 +26,20 @@ func.func @RoPE(%iinput: !input_memref_type, %ipos_ids: !pos_ids_memref_type, %i
     %pos_ids = bufferization.to_tensor %ipos_ids restrict : !pos_ids_memref_type
     %pos_id_end = bufferization.to_tensor %ipos_id_end restrict : memref<1xindex>
     %3 = tensor.empty(): !output_tensor_type
-    //call @stopTimerMy() : () -> ()
+
     %transpose_in =  linalg.transpose ins(%input: !input_tensor_type) outs(%3:!output_tensor_type)  permutation = [0, 2, 1, 3]
 
-    //call @startTimerMy() : () -> ()
     %c0 = arith.constant 0 : index
     %c3 = arith.constant 3 : index
     %cos_cache_slice = tensor.extract_slice %cos_cache_tensor[0, 0, 0, 0] [1, 1, 7, 128] [1, 1, 1, 1] : !cos_sin_cache_tensor_type to !cos_sin_cache_tensor_shrink_type
     %cos_cache_slice2 = tensor.collapse_shape %cos_cache_slice [[0, 1], [2],[3]] : tensor<1x1x7x128x!dtype> into tensor<1x7x128x!dtype>
     %cos_cache_slice3 = tensor.collapse_shape %cos_cache_slice2 [[0, 1], [2]] : tensor<1x7x128x!dtype> into tensor<7x128x!dtype>
     %pos_ids_index=tensor.expand_shape %pos_ids [[0],[1,2]] output_shape [1, 7, 1] : tensor<1x7xindex> into tensor<1x7x1xindex>
-    //call @stopTimerMy() : () -> ()
-
-    //call @startTimerMy() : () -> ()
 
     %cos_cache_slice4 = tensor.gather %cos_cache_slice3[%pos_ids_index] gather_dims([0]) : (tensor<7x128x!dtype>, tensor<1x7x1xindex>) -> tensor<1x7x128x!dtype>
 
-    //call @stopTimerMy() : () -> ()
-
-    //call @startTimerMy() : () -> ()
-    // %cos_cache_slice4 = tensor.expand_shape %cos_cache_slice3[[0,1],[2]] output_shape [1,7,128] : tensor<7x128x!dtype> into tensor<1x7x128x!dtype>
     %cos_cache_slice5 = tensor.expand_shape %cos_cache_slice4 [[0,1],[2],[3]] output_shape [1,1,7,128] : tensor<1x7x128x!dtype> into tensor<1x1x7x128x!dtype>
     %cos_cache_slice6 = tensor.collapse_shape %cos_cache_slice5 [[0,1,2],[3]] : tensor<1x1x7x128x!dtype> into tensor<7x128x!dtype>
-    //call @stopTimerMy() : () -> ()
 
     %cos_cache_slice7 = linalg.broadcast ins(%cos_cache_slice6: tensor<7x128x!dtype>) outs(%3: !output_tensor_type) dimensions = [0, 1]
     %input_apply_cos_cache = linalg.mul ins(%transpose_in, %cos_cache_slice7:  !output_tensor_type, !output_tensor_type) outs(%3: !output_tensor_type) -> !output_tensor_type