Integrate LLVM at 03f616eb3acf1ae5a219ea247d9efe3cbfd41b59 (#4226)

Update LLVM to
llvm/llvm-project@03f616e.

This commit also updates the tosa test related to aten.scatter op
because of the op changes made in the downstream tosa.scatter op here:
llvm/llvm-project@c140783.

Add failing tosa tests to xfail_set.
---------

Signed-off-by: Vivek Khandelwal <[email protected]>

Author: vivekkhandelwal1

externals/llvm-project

@@ -3906,6 +3906,14 @@
     "ScaledDotProductAttentionSameDynamicModule_basic",
     "ScaledDotProductAttentionSameModule_basic",
     "ScaledDotProductAttentionGQAModule_basic",
+    # error: 'tosa.scatter' op requires dimensions K >= W
+    "IndexPut1DFloatNonAccumulateModule_basic",
+    "IndexPut1DIntNonAccumulateModule_basic",
+    "IndexPutHackedTwin1DFloatNonAccumulateModule_basic",
+    "IndexPutHackedTwin1DIntNonAccumulateModule_basic",
+    "IndexPutImpl1DFloatNonAccumulateModule_basic",
+    "IndexPutImpl1DIntNonAccumulateModule_basic",
+    "UnsafeIndexPutHackedTwin1DFloatNonAccumulateModule_basic",
 }
 
 ONNX_TOSA_CRASHING_SET = {

projects/pt1/e2e_testing/xfail_sets.py

@@ -2372,8 +2372,8 @@ func.func @torch.aten.empty.memory_format$basic() -> !torch.vtensor<[3,4],si64>
 // CHECK-LABEL:   func.func @torch.aten.scatter.src$basic(
 // CHECK-SAME:                                            %[[VAL_0:.*]]: !torch.vtensor<[10,8,6],f32>,
 // CHECK-SAME:                                            %[[VAL_1:.*]]: !torch.vtensor<[2,4,3],si64>,
-// CHECK-SAME:                                            %[[VAL_2:.*]]: !torch.vtensor<[3,4,3],f32>) -> !torch.vtensor<[10,8,6],f32> {
-// CHECK:           %[[VAL_3:.*]] = torch_c.to_builtin_tensor %[[VAL_2]] : !torch.vtensor<[3,4,3],f32> -> tensor<3x4x3xf32>
+// CHECK-SAME:                                            %[[VAL_2:.*]]: !torch.vtensor<[2,4,3],f32>) -> !torch.vtensor<[10,8,6],f32> {
+// CHECK:           %[[VAL_3:.*]] = torch_c.to_builtin_tensor %[[VAL_2]] : !torch.vtensor<[2,4,3],f32> -> tensor<2x4x3xf32>
 // CHECK:           %[[VAL_4:.*]] = torch_c.to_builtin_tensor %[[VAL_1]] : !torch.vtensor<[2,4,3],si64> -> tensor<2x4x3xi64>
 // CHECK:           %[[VAL_5:.*]] = torch_c.to_builtin_tensor %[[VAL_0]] : !torch.vtensor<[10,8,6],f32> -> tensor<10x8x6xf32>
 // CHECK:           %[[VAL_6:.*]] = torch.constant.int 1
@@ -2383,8 +2383,8 @@ func.func @torch.aten.empty.memory_format$basic() -> !torch.vtensor<[3,4],si64>
 // CHECK:           %[[VAL_10:.*]] = "tosa.const"() <{values = dense<{{\[\[}}{{\[\[}}0], [0], [0]], {{\[\[}}0], [0], [0]], {{\[\[}}0], [0], [0]], {{\[\[}}0], [0], [0]]], {{\[\[}}[1], [1], [1]], {{\[\[}}1], [1], [1]], {{\[\[}}1], [1], [1]], {{\[\[}}1], [1], [1]]]]> : tensor<2x4x3x1xi32>}> : () -> tensor<2x4x3x1xi32>
 // CHECK:           %[[VAL_11:.*]] = "tosa.const"() <{values = dense<{{\[\[}}{{\[\[}}0], [1], [2]], {{\[\[}}0], [1], [2]], {{\[\[}}0], [1], [2]], {{\[\[}}0], [1], [2]]], {{\[\[}}[0], [1], [2]], {{\[\[}}0], [1], [2]], {{\[\[}}0], [1], [2]], {{\[\[}}0], [1], [2]]]]> : tensor<2x4x3x1xi32>}> : () -> tensor<2x4x3x1xi32>
 // CHECK:           %[[VAL_12:.*]] = tosa.concat %[[VAL_10]], %[[VAL_9]], %[[VAL_11]] {axis = 3 : i32} : (tensor<2x4x3x1xi32>, tensor<2x4x3x1xi32>, tensor<2x4x3x1xi32>) -> tensor<2x4x3x3xi32>
-// CHECK:           %[[VAL_13:.*]] = tosa.const_shape  {values = dense<[1, 36, 1]> : tensor<3xindex>} : () -> !tosa.shape<3>
-// CHECK:           %[[VAL_14:.*]] = tosa.reshape %[[VAL_3]], %[[VAL_13]] : (tensor<3x4x3xf32>, !tosa.shape<3>) -> tensor<1x36x1xf32>
+// CHECK:           %[[VAL_13:.*]] = tosa.const_shape  {values = dense<[1, 24, 1]> : tensor<3xindex>} : () -> !tosa.shape<3>
+// CHECK:           %[[VAL_14:.*]] = tosa.reshape %[[VAL_3]], %[[VAL_13]] : (tensor<2x4x3xf32>, !tosa.shape<3>) -> tensor<1x24x1xf32>
 // CHECK:           %[[VAL_15:.*]] = tosa.const_shape  {values = dense<[1, 480, 1]> : tensor<3xindex>} : () -> !tosa.shape<3>
 // CHECK:           %[[VAL_16:.*]] = tosa.reshape %[[VAL_5]], %[[VAL_15]] : (tensor<10x8x6xf32>, !tosa.shape<3>) -> tensor<1x480x1xf32>
 // CHECK:           %[[VAL_17:.*]] = tosa.const_shape  {values = dense<[24, 3]> : tensor<2xindex>} : () -> !tosa.shape<2>
@@ -2397,15 +2397,15 @@ func.func @torch.aten.empty.memory_format$basic() -> !torch.vtensor<[3,4],si64>
 // CHECK:           %[[VAL_24:.*]] = tosa.reduce_sum %[[VAL_23]] {axis = 1 : i32} : (tensor<24x3xi32>) -> tensor<24x1xi32>
 // CHECK:           %[[VAL_25:.*]] = tosa.const_shape  {values = dense<[1, 24]> : tensor<2xindex>} : () -> !tosa.shape<2>
 // CHECK:           %[[VAL_26:.*]] = tosa.reshape %[[VAL_24]], %[[VAL_25]] : (tensor<24x1xi32>, !tosa.shape<2>) -> tensor<1x24xi32>
-// CHECK:           %[[VAL_27:.*]] = tosa.scatter %[[VAL_16]], %[[VAL_26]], %[[VAL_14]] : (tensor<1x480x1xf32>, tensor<1x24xi32>, tensor<1x36x1xf32>) -> tensor<1x480x1xf32>
+// CHECK:           %[[VAL_27:.*]] = tosa.scatter %[[VAL_16]], %[[VAL_26]], %[[VAL_14]] : (tensor<1x480x1xf32>, tensor<1x24xi32>, tensor<1x24x1xf32>) -> tensor<1x480x1xf32>
 // CHECK:           %[[VAL_28:.*]] = tosa.const_shape  {values = dense<[10, 8, 6]> : tensor<3xindex>} : () -> !tosa.shape<3>
 // CHECK:           %[[VAL_29:.*]] = tosa.reshape %[[VAL_27]], %[[VAL_28]] : (tensor<1x480x1xf32>, !tosa.shape<3>) -> tensor<10x8x6xf32>
 // CHECK:           %[[VAL_30:.*]] = torch_c.from_builtin_tensor %[[VAL_29]] : tensor<10x8x6xf32> -> !torch.vtensor<[10,8,6],f32>
 // CHECK:           return %[[VAL_30]] : !torch.vtensor<[10,8,6],f32>
 // CHECK:         }
-func.func @torch.aten.scatter.src$basic(%arg0: !torch.vtensor<[10,8,6],f32>, %arg1: !torch.vtensor<[2,4,3],si64>, %arg2: !torch.vtensor<[3,4,3],f32>) -> !torch.vtensor<[10,8,6],f32> {
+func.func @torch.aten.scatter.src$basic(%arg0: !torch.vtensor<[10,8,6],f32>, %arg1: !torch.vtensor<[2,4,3],si64>, %arg2: !torch.vtensor<[2,4,3],f32>) -> !torch.vtensor<[10,8,6],f32> {
   %int1 = torch.constant.int 1
-  %0 = torch.aten.scatter.src %arg0, %int1, %arg1, %arg2 : !torch.vtensor<[10,8,6],f32>, !torch.int, !torch.vtensor<[2,4,3],si64>, !torch.vtensor<[3,4,3],f32> -> !torch.vtensor<[10,8,6],f32>
+  %0 = torch.aten.scatter.src %arg0, %int1, %arg1, %arg2 : !torch.vtensor<[10,8,6],f32>, !torch.int, !torch.vtensor<[2,4,3],si64>, !torch.vtensor<[2,4,3],f32> -> !torch.vtensor<[10,8,6],f32>
   return %0 : !torch.vtensor<[10,8,6],f32>
 }