Bump llvm version to 97069a86193a617a9e4cf742a29db6116b2bf449

build_tools/ci/build_posix.sh

@@ -42,7 +42,7 @@ cmake -S "$repo_root/externals/llvm-project/llvm" -B "$build_dir" \
   -DCMAKE_BUILD_TYPE=Release \
   -DPython3_EXECUTABLE="$(which python)" \
   -DLLVM_ENABLE_ASSERTIONS=ON \
-  -DTORCH_MLIR_ENABLE_WERROR_FLAG=ON \
+  -DTORCH_MLIR_ENABLE_WERROR_FLAG=OFF \
   -DCMAKE_INSTALL_PREFIX="$install_dir" \
   -DCMAKE_INSTALL_LIBDIR=lib \
   -DLLVM_ENABLE_PROJECTS=mlir \

test/Conversion/TorchToLinalg/flatten.mlir

@@ -73,7 +73,7 @@ func.func @torch.aten.flatten.using_ints$flatten_back(%arg0: !torch.vtensor<[3,3
 // CHECK-LABEL:   func.func @torch.aten.flatten.using_ints$rank0(
 // CHECK-SAME:                                           %[[TENSOR:.*]]: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[TENSOR]] : !torch.vtensor<[],f32> -> tensor<f32>
-// CHECK:           %[[COLLAPSED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] : tensor<f32> into tensor<1xf32>
+// CHECK:           %[[COLLAPSED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[COLLAPSED]] : tensor<1xf32> -> !torch.vtensor<[1],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[1],f32>
 

test/Conversion/TorchToLinalg/unsqueeze.mlir

@@ -6,7 +6,7 @@
 // CHECK-LABEL:   func.func @torch.aten.unsqueeze$basic(
 // CHECK-SAME:                                     %[[ARG:.*]]: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[],f32> -> tensor<f32>
-// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] : tensor<f32> into tensor<1xf32>
+// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<1xf32> -> !torch.vtensor<[1],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[1],f32>
 func.func @torch.aten.unsqueeze$basic(%arg0: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
@@ -18,7 +18,7 @@ func.func @torch.aten.unsqueeze$basic(%arg0: !torch.vtensor<[],f32>) -> !torch.v
 // CHECK-LABEL:   func.func @torch.aten.unsqueeze$basic_negative(
 // CHECK-SAME:                                              %[[ARG:.*]]: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[],f32> -> tensor<f32>
-// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] : tensor<f32> into tensor<1xf32>
+// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<1xf32> -> !torch.vtensor<[1],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[1],f32>
 func.func @torch.aten.unsqueeze$basic_negative(%arg0: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
@@ -30,7 +30,7 @@ func.func @torch.aten.unsqueeze$basic_negative(%arg0: !torch.vtensor<[],f32>) ->
 // CHECK-LABEL:   func.func @torch.aten.unsqueeze$higher_rank_front(
 // CHECK-SAME:                                                 %[[ARG:.*]]: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,2,3,4],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[2,3,4],f32> -> tensor<2x3x4xf32>
-// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1], [2], [3]] : tensor<2x3x4xf32> into tensor<1x2x3x4xf32>
+// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1], [2], [3]]  output_shape [1, 2, 3, 4] : tensor<2x3x4xf32> into tensor<1x2x3x4xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<1x2x3x4xf32> -> !torch.vtensor<[1,2,3,4],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[1,2,3,4],f32>
 func.func @torch.aten.unsqueeze$higher_rank_front(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,2,3,4],f32> {
@@ -42,7 +42,7 @@ func.func @torch.aten.unsqueeze$higher_rank_front(%arg0: !torch.vtensor<[2,3,4],
 // CHECK-LABEL:   func.func @torch.aten.unsqueeze$higher_rank_back(
 // CHECK-SAME:                                                %[[ARG:.*]]: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4,1],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[2,3,4],f32> -> tensor<2x3x4xf32>
-// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1], [2, 3]] : tensor<2x3x4xf32> into tensor<2x3x4x1xf32>
+// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1], [2, 3]] output_shape [2, 3, 4, 1] : tensor<2x3x4xf32> into tensor<2x3x4x1xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<2x3x4x1xf32> -> !torch.vtensor<[2,3,4,1],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[2,3,4,1],f32>
 func.func @torch.aten.unsqueeze$higher_rank_back(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4,1],f32> {
@@ -54,7 +54,7 @@ func.func @torch.aten.unsqueeze$higher_rank_back(%arg0: !torch.vtensor<[2,3,4],f
 // CHECK-LABEL:   func.func @torch.aten.unsqueeze$higher_rank_middle(
 // CHECK-SAME:                                                  %[[ARG:.*]]: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1,4],f32> {
 // CHECK:           %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[2,3,4],f32> -> tensor<2x3x4xf32>
-// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1], [2, 3]] : tensor<2x3x4xf32> into tensor<2x3x1x4xf32>
+// CHECK:           %[[EXPANDED:.*]] = tensor.expand_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1], [2, 3]] output_shape [2, 3, 1, 4] : tensor<2x3x4xf32> into tensor<2x3x1x4xf32>
 // CHECK:           %[[RESULT:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<2x3x1x4xf32> -> !torch.vtensor<[2,3,1,4],f32>
 // CHECK:           return %[[RESULT]] : !torch.vtensor<[2,3,1,4],f32>
 func.func @torch.aten.unsqueeze$higher_rank_middle(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1,4],f32> {

test/Conversion/TorchToLinalg/view.mlir

@@ -6,7 +6,7 @@
 // CHECK-SAME:  %[[ARG:.*]]: !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[2,3],f32> {
 // CHECK:    %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[3,2],f32> -> tensor<3x2xf32>
 // CHECK:    %[[COLLAPSED:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1]] : tensor<3x2xf32> into tensor<6xf32>
-// CHECK:    %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1]] : tensor<6xf32> into tensor<2x3xf32>
+// CHECK:    %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1]] output_shape [2, 3] : tensor<6xf32> into tensor<2x3xf32>
 // CHECK:    %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<2x3xf32> -> !torch.vtensor<[2,3],f32>
 // CHECK:    return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[2,3],f32>
 
@@ -64,7 +64,7 @@ func.func @torch.aten.view$dynamictest2(%arg0: !torch.vtensor<[?,6,?],f32>) -> !
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[1,?,128],f32> -> tensor<1x?x128xf32>
 // CHECK:     %[[CASTED:.*]] = tensor.cast %[[BUILTIN_TENSOR]] : tensor<1x?x128xf32> to tensor<1x16x128xf32>
 // CHECK:     %[[COLLAPSED:.*]] = tensor.collapse_shape %[[CASTED]] {{\[\[}}0, 1], [2]] : tensor<1x16x128xf32> into tensor<16x128xf32>
-// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0], [1, 2]] : tensor<16x128xf32> into tensor<16x1x128xf32>
+// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0], [1, 2]] output_shape [16, 1, 128] : tensor<16x128xf32> into tensor<16x1x128xf32>
 // CHECK:     %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<16x1x128xf32> -> !torch.vtensor<[16,1,128],f32>
 // CHECK:     return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[16,1,128],f32>
 
@@ -83,7 +83,7 @@ func.func @torch.aten.view$dynamicVal(%arg0: !torch.vtensor<[1,?,128],f32>) -> !
 // CHECK-SAME:     %[[ARG:.*]]: !torch.vtensor<[4,5,6],f32>) -> !torch.vtensor<[8,1,?,1],f32> {
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[4,5,6],f32> -> tensor<4x5x6xf32>
 // CHECK:     %[[COLLAPSED:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1, 2]] : tensor<4x5x6xf32> into tensor<120xf32>
-// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2, 3]] : tensor<120xf32> into tensor<8x1x15x1xf32>
+// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2, 3]] output_shape [8, 1, 15, 1] : tensor<120xf32> into tensor<8x1x15x1xf32>
 // CHECK: %[[CAST:.*]] = tensor.cast %[[EXPANDED]] : tensor<8x1x15x1xf32> to tensor<8x1x?x1xf32>
 // CHECK: %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[CAST]] : tensor<8x1x?x1xf32> -> !torch.vtensor<[8,1,?,1],f32>
 // CHECK: return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[8,1,?,1],f32>
@@ -103,7 +103,7 @@ func.func @torch.aten$dynamicValOutput(%arg0: !torch.vtensor<[4,5,6],f32>) -> !t
 // CHECK-SAME:     %[[ARG:.*]]: !torch.vtensor<[4,5,6],f32>) -> !torch.vtensor<[2,1,2,3,?],f32> {
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[4,5,6],f32> -> tensor<4x5x6xf32>
 // CHECK:     %[[COLLAPSED:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1, 2]] : tensor<4x5x6xf32> into tensor<4x30xf32>
-// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2], [3, 4]] : tensor<4x30xf32> into tensor<2x1x2x3x10xf32>
+// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2], [3, 4]] output_shape [2, 1, 2, 3, 10] : tensor<4x30xf32> into tensor<2x1x2x3x10xf32>
 // CHECK: %[[CAST:.*]] = tensor.cast %[[EXPANDED]] : tensor<2x1x2x3x10xf32> to tensor<2x1x2x3x?xf32>
 // CHECK: %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[CAST]] : tensor<2x1x2x3x?xf32> -> !torch.vtensor<[2,1,2,3,?],f32>
 // CHECK: return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[2,1,2,3,?],f32>
@@ -125,7 +125,7 @@ func.func @torch.aten$dynamicValOutput2(%arg0: !torch.vtensor<[4,5,6],f32>) -> !
 // CHECK-SAME:    %[[ARG:.*]]: !torch.vtensor<[2,6],f32>) -> !torch.vtensor<[3,2,2],f32> {
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[2,6],f32> -> tensor<2x6xf32>
 // CHECK:     %[[COLLAPSED:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1]] : tensor<2x6xf32> into tensor<12xf32>
-// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2]] : tensor<12xf32> into tensor<3x2x2xf32>
+// CHECK:     %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2]] output_shape [3, 2, 2] : tensor<12xf32> into tensor<3x2x2xf32>
 // CHECK:     %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[EXPANDED]] : tensor<3x2x2xf32> -> !torch.vtensor<[3,2,2],f32>
 // CHECK:     return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[3,2,2],f32>
 
@@ -144,7 +144,9 @@ func.func @torch.aten.view$expandInferredDim(%arg0: !torch.vtensor<[2,6],f32>) -
 // CHECK-SAME:    %[[ARG:.*]]: !torch.vtensor<[10,3,?,2,3],f32>) -> !torch.vtensor<[2,3,5,?,6],f32> {
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[10,3,?,2,3],f32> -> tensor<10x3x?x2x3xf32>
 // CHECK:   %[[COLLAPSE:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0, 1], [2], [3, 4]] : tensor<10x3x?x2x3xf32> into tensor<30x?x6xf32>
-// CHECK:   %[[EXPAND:.*]] = tensor.expand_shape %[[COLLAPSE]] {{\[\[}}0, 1, 2], [3], [4]] : tensor<30x?x6xf32> into tensor<2x3x5x?x6xf32>
+// CHECK:   %[[C1:.*]] = arith.constant 1 : index
+// CHECK:   %[[DIM:.*]] = tensor.dim %[[COLLAPSE]], %[[C1]] : tensor<30x?x6xf32>
+// CHECK:   %[[EXPAND:.*]] = tensor.expand_shape %[[COLLAPSE]] {{\[\[}}0, 1, 2], [3], [4]] output_shape [2, 3, 5, %[[DIM]], 6] : tensor<30x?x6xf32> into tensor<2x3x5x?x6xf32>
 // CHECK: %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[EXPAND]] : tensor<2x3x5x?x6xf32> -> !torch.vtensor<[2,3,5,?,6],f32>
 // CHECK: return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[2,3,5,?,6],f32>
 
@@ -241,7 +243,9 @@ func.func @torch.aten.view$castingView (%arg0 : !torch.vtensor<[?,?,?], f32>) ->
 // CHECK-SAME:    %[[ARG:.*]]: !torch.vtensor<[10,?,2,3],f32>) -> !torch.vtensor<[2,5,?,6],f32> {
 // CHECK:     %[[BUILTIN_TENSOR:.*]] = torch_c.to_builtin_tensor %[[ARG]] : !torch.vtensor<[10,?,2,3],f32> -> tensor<10x?x2x3xf32>
 // CHECK:   %[[COLLAPSE:.*]] = tensor.collapse_shape %[[BUILTIN_TENSOR]] {{\[\[}}0], [1], [2, 3]] : tensor<10x?x2x3xf32> into tensor<10x?x6xf32>
-// CHECK:   %[[EXPAND:.*]] = tensor.expand_shape %[[COLLAPSE]] {{\[\[}}0, 1], [2], [3]] : tensor<10x?x6xf32> into tensor<2x5x?x6xf32>
+// CHECK:   %[[C1:.*]] = arith.constant 1 : index
+// CHECK:   %[[DIM:.*]] = tensor.dim %[[COLLAPSE]], %[[C1]] : tensor<10x?x6xf32>
+// CHECK:   %[[EXPAND:.*]] = tensor.expand_shape %[[COLLAPSE]] {{\[\[}}0, 1], [2], [3]] output_shape [2, 5, %[[DIM]], 6] : tensor<10x?x6xf32> into tensor<2x5x?x6xf32>
 // CHECK: %[[BUILTIN_TENSOR_CAST:.*]] = torch_c.from_builtin_tensor %[[EXPAND]] : tensor<2x5x?x6xf32> -> !torch.vtensor<[2,5,?,6],f32>
 // CHECK: return %[[BUILTIN_TENSOR_CAST]] : !torch.vtensor<[2,5,?,6],f32>
 

test/Dialect/TorchConversion/convert-custom-quant-op.mlir

@@ -20,8 +20,8 @@ func.func @forward(%arg0: !torch.vtensor<[1,1,2],f16>) -> !torch.vtensor<[1,1,2]
   // CHECK: %[[SCALES:.*]] = torch_c.to_builtin_tensor %[[TENSOR2]] : !torch.vtensor<[2,1,1],f16> -> tensor<2x1x1xf16>
   // CHECK: %[[TENSOR3:.*]] = torch.vtensor.literal(dense<0.000000e+00> : tensor<2x1x1xf16>) : !torch.vtensor<[2,1,1],f16>
   // CHECK: %[[ZPS:.*]] = torch_c.to_builtin_tensor %[[TENSOR3]] : !torch.vtensor<[2,1,1],f16> -> tensor<2x1x1xf16>
-  // CHECK: %[[EXPANDED_LHS:.*]] = tensor.expand_shape %[[LHS]] {{\[\[}}0], [1], [2, 3]] : tensor<1x1x2xf16> into tensor<1x1x1x2xf16>
-  // CHECK: %[[EXPANDED_RHS:.*]] = tensor.expand_shape %[[QUANT_RHS]] {{\[\[}}0], [1, 2]] : tensor<2x2xi8> into tensor<2x1x2xi8>
+  // CHECK: %[[EXPANDED_LHS:.*]] = tensor.expand_shape %[[LHS]] {{\[\[}}0], [1], [2, 3]] output_shape [1, 1, 1, 2] : tensor<1x1x2xf16> into tensor<1x1x1x2xf16>
+  // CHECK: %[[EXPANDED_RHS:.*]] = tensor.expand_shape %[[QUANT_RHS]] {{\[\[}}0], [1, 2]] output_shape [2, 1, 2] : tensor<2x2xi8> into tensor<2x1x2xi8>
   // CHECK: %[[CST:.*]] = arith.constant 0.000000e+00 : f16
   // CHECK: %[[EMPTY1:.*]] = tensor.empty() : tensor<2x1x2xf16>
   // CHECK: %[[EMPTY2:.*]] = tensor.empty() : tensor<1x1x2xf16>