Integrate LLVM at llvm/llvm-project@c907681b07

Updates LLVM usage to match
[c907681b077c](https://github.com/llvm/llvm-project/commit/c907681b077c)

PiperOrigin-RevId: 360891677
Change-Id: Iaaf934b70f5b064ad3796d08abd887c53e3b1d41

tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td

@@ -90,7 +90,7 @@ class HLOClient_BroadcastBinaryElementwiseOp<
   );
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$left, "Value":$right,
+    OpBuilder<(ins "Value":$left, "Value":$right,
       "DenseIntElementsAttr":$broadcast_dimensions)>];
 
   let results = (outs HLO_Tensor);
@@ -673,7 +673,7 @@ def HLOClient_BroadcastCompareOp : HLOClient_BroadcastBinaryElementwiseOp<
   let results = (outs HLO_PredTensor);
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
+    OpBuilder<(ins "Value":$lhs, "Value":$rhs,
       "DenseIntElementsAttr":$broadcast_dimensions,
       "StringAttr":$comparison_direction, CArg<"StringAttr", "{}">:$compare_type)>];
 }

tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td

@@ -61,7 +61,7 @@ def HLO_ConstOp : HLO_Op<"constant",
   );
 
   let builders = [
-    OpBuilderDAG<(ins "Attribute":$value)>];
+    OpBuilder<(ins "Attribute":$value)>];
 
   let assemblyFormat = "attr-dict $value";
 
@@ -163,7 +163,7 @@ def HLO_ConvertOp : HLO_UnaryElementwiseOp<"convert",
     [NoSideEffect, SameOperandsAndResultShape], HLO_Tensor>,
     BASE_HLO_ConvertOp {
   let builders = [
-    OpBuilderDAG<(ins "Value":$operand, "Type":$result_element_ty)>];
+    OpBuilder<(ins "Value":$operand, "Type":$result_element_ty)>];
 
   let hasFolder = 1;
 
@@ -624,7 +624,7 @@ def HLO_ReduceOp: HLO_Op<"reduce", [
   let results = (outs Variadic<HLO_TensorOrTuple>);
 
   let builders = [
-    OpBuilderDAG<(ins "ValueRange":$operands, "ValueRange":$init_values,
+    OpBuilder<(ins "ValueRange":$operands, "ValueRange":$init_values,
       "DenseIntElementsAttr":$dimensions)>];
 
   let extraClassDeclaration = [{
@@ -662,7 +662,7 @@ def HLO_GetTupleElementOp: HLO_Op<"get_tuple_element", [NoSideEffect]>, BASE_HLO
   let hasFolder = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$value, "int32_t":$index)>];
+    OpBuilder<(ins "Value":$value, "int32_t":$index)>];
 }
 
 def HLO_TupleOp : HLO_Op<"tuple", [NoSideEffect]>, BASE_HLO_TupleOp {
@@ -670,7 +670,7 @@ def HLO_TupleOp : HLO_Op<"tuple", [NoSideEffect]>, BASE_HLO_TupleOp {
   let results = (outs HLO_Tuple);
 
   let builders = [
-    OpBuilderDAG<(ins "ValueRange":$values)>];
+    OpBuilder<(ins "ValueRange":$values)>];
 
   let hasCanonicalizer = 1;
 }
@@ -690,7 +690,7 @@ def HLO_CompareOp: HLO_Op<"compare", [NoSideEffect, SameTypeOperands,
   let hasFolder = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
+    OpBuilder<(ins "Value":$lhs, "Value":$rhs,
       "StringAttr":$comparison_direction, CArg<"StringAttr", "{}">:$compare_type)>,
   ];
 
@@ -889,7 +889,7 @@ def HLO_ConcatenateOp : HLO_Op<"concatenate",
   let hasFolder = 1;
 
   let extraClassDeclaration = [{
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return succeeded(mlir::verifyCompatibleShapes(l, r));
     }
   }];
@@ -1170,7 +1170,7 @@ def HLO_SortOp : HLO_Op<"sort", [RecursiveSideEffects,
   let regions = (region SizedRegion<1>:$comparator);
 
   let builders = [
-    OpBuilderDAG<(ins "ValueRange":$operands, CArg<"int64_t", "-1">:$dimension,
+    OpBuilder<(ins "ValueRange":$operands, CArg<"int64_t", "-1">:$dimension,
       CArg<"bool", "false">:$is_stable)>];
 
   // TODO(b/129422361): SortOp has special conversion logic to HLO.

tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/lhlo_ops.td

@@ -691,7 +691,7 @@ def FusionOp : LHLO_Op<"fusion", [SingleBlockImplicitTerminator<"TerminatorOp">]
 
   let skipDefaultBuilders = 1;
   let builders = [
-     OpBuilderDAG<(ins CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes)>
+     OpBuilder<(ins CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes)>
   ];
 
   let extraClassDeclaration = [{
@@ -740,7 +740,7 @@ def TerminatorOp :
     Terminator operation for the LHLO dialect.
   }];
   let builders = [
-    OpBuilderDAG<(ins "ValueRange":$operands),
+    OpBuilder<(ins "ValueRange":$operands),
     [{ build($_builder, $_state, llvm::None, operands, llvm::None); }]>];
 }
 

tensorflow/compiler/mlir/lite/ir/tfl_ops.cc

@@ -1045,7 +1045,7 @@ LogicalResult Conv2DOp::inferReturnTypes(
   return success();
 }
 
-bool Conv2DOp::isCompatibleReturnTypes(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
+bool Conv2DOp::isCompatibleReturnTypes(TypeRange lhs, TypeRange rhs) {
   if (lhs.size() != rhs.size() || lhs.size() != 1) return false;
   if (failed(mlir::verifyCompatibleShape(lhs[0], rhs[0]))) return false;
   return true;
@@ -1917,7 +1917,7 @@ LogicalResult UnpackOp::inferReturnTypes(
   return success();
 }
 
-bool UnpackOp::isCompatibleReturnTypes(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
+bool UnpackOp::isCompatibleReturnTypes(TypeRange lhs, TypeRange rhs) {
   if (lhs.size() != rhs.size()) return false;
   for (auto pair : llvm::zip(lhs, rhs)) {
     if (failed(
@@ -2267,8 +2267,8 @@ LogicalResult UnidirectionalSequenceLSTMOp::inferReturnTypes(
   return success();
 }
 
-bool UnidirectionalSequenceLSTMOp::isCompatibleReturnTypes(ArrayRef<Type> lhs,
+bool UnidirectionalSequenceLSTMOp::isCompatibleReturnTypes(TypeRange lhs,
-                                                           ArrayRef<Type> rhs) {
+                                                           TypeRange rhs) {
   if (lhs.size() != rhs.size() || lhs.size() != 1) return false;
   if (failed(mlir::verifyCompatibleShape(lhs[0], rhs[0]))) return false;
   return true;

tensorflow/compiler/mlir/lite/ir/tfl_ops.td

@@ -428,7 +428,7 @@ def ComparisonOpSameElementTypeConstraint :
 //===----------------------------------------------------------------------===//
 
 def TFL_BroadcastableBinaryBuilder :
-  OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
+  OpBuilder<(ins "Value":$lhs, "Value":$rhs),
   [{
     auto resultType =
       OpTrait::util::getBroadcastedType(lhs.getType(), rhs.getType());
@@ -439,7 +439,7 @@ def TFL_BroadcastableBinaryBuilder :
   }]>;
 
 def TFL_FusedBroadcastableBinaryBuilder :
-  OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs,
+  OpBuilder<(ins "Value":$lhs, "Value":$rhs,
     "StringAttr":$fusedActivationFunction),
   [{
     buildFusedBroadcastableBinOp(
@@ -447,7 +447,7 @@ def TFL_FusedBroadcastableBinaryBuilder :
   }]>;
 
 def TFL_ComparisonBinaryBuilder :
-  OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
+  OpBuilder<(ins "Value":$lhs, "Value":$rhs),
   [{
     buildComparisonBinOp(&$_builder, $_state, lhs, rhs);
   }]>;
@@ -818,7 +818,7 @@ def TFL_ConstOp : Op<TFL_Dialect, "pseudo_const", [ConstantLike, NoSideEffect,
   let hasFolder = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "Attribute":$value),
+    OpBuilder<(ins "Attribute":$value),
     [{
       $_state.addAttribute("value", value);
       $_state.addTypes(value.getType());
@@ -843,7 +843,7 @@ def TFL_SparseConstOp : Op<TFL_Dialect, "pseudo_sparse_const", [
   let results = (outs AnyTensor:$output);
 
   let builders = [
-    OpBuilderDAG<(ins "Attribute":$value, "SparsityParameterAttr":$s_param,
+    OpBuilder<(ins "Attribute":$value, "SparsityParameterAttr":$s_param,
       "Attribute":$compressed_data),
     [{
       $_state.addTypes(value.getType());
@@ -881,7 +881,7 @@ def TFL_Conv2DOp : TFL_ConvOp<"conv_2d", "Convolution", 0,
     std::vector<std::vector<int>> GetQuantizedBlockSize() { return {}; }
 
     // Returns whether the return types are compatible.
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
   }];
 }
 
@@ -1062,7 +1062,7 @@ def TFL_GatherOp : TFL_Op<"gather", [
 
   let builders =
   [
-    OpBuilderDAG<(ins "Value":$params, "Value":$indices, "IntegerAttr":$axis),
+    OpBuilder<(ins "Value":$params, "Value":$indices, "IntegerAttr":$axis),
     [{ BuildGatherOp(&$_builder, $_state, params, indices, axis); }]>
   ];
 
@@ -1399,7 +1399,7 @@ def TFL_NotEqualOp : TFL_Op<"not_equal", [
 
   let builders =
   [
-    OpBuilderDAG<(ins "Value":$lhs, "Value":$rhs),
+    OpBuilder<(ins "Value":$lhs, "Value":$rhs),
     [{
         buildComparisonBinOp(&$_builder, $_state, lhs, rhs);
       }]>
@@ -1901,7 +1901,7 @@ def TFL_LogisticOp: TFL_Op<"logistic", [
   // non-quantization tablegen patterns. Currently, it is used by the
   // elementwise-move reordering pattern in the optimize_patterns.td
   let builders = [
-    OpBuilderDAG<(ins "Value":$input),
+    OpBuilder<(ins "Value":$input),
     [{
       $_state.addOperands({input});
       $_state.addTypes(input.getType());
@@ -2554,7 +2554,7 @@ def TFL_ReluOp: TFL_Op<"relu", [
   // non-quantization tablegen patterns. Currently, it is used by the
   // elementwise-move reordering pattern in the optimize_patterns.td
   let builders = [
-    OpBuilderDAG<(ins "Value":$input),
+    OpBuilder<(ins "Value":$input),
     [{
       $_state.addOperands({input});
       $_state.addTypes(input.getType());
@@ -2582,7 +2582,7 @@ def TFL_Relu6Op: TFL_Op<"relu6", [
   // non-quantization tablegen patterns. Currently, it is used by the
   // elementwise-move reordering pattern in the optimize_patterns.td
   let builders = [
-    OpBuilderDAG<(ins "Value":$input),
+    OpBuilder<(ins "Value":$input),
     [{
       $_state.addOperands({input});
       $_state.addTypes(input.getType());
@@ -2610,7 +2610,7 @@ def TFL_Relu1Op: TFL_Op<"relu_n1_to_1", [
   // non-quantization tablegen patterns. Currently, it is used by the
   // elementwise-move reordering pattern in the optimize_patterns.td
   let builders = [
-    OpBuilderDAG<(ins "Value":$input),
+    OpBuilder<(ins "Value":$input),
     [{
       $_state.addOperands({input});
       $_state.addTypes(input.getType());
@@ -2795,7 +2795,7 @@ def TFL_SelectOp : TFL_Op<"select", [
 
   // TODO(jpienaar): autogenerate this.
   let builders = [
-    OpBuilderDAG<(ins "Value":$condition, "Value":$x, "Value":$y),
+    OpBuilder<(ins "Value":$condition, "Value":$x, "Value":$y),
     [{
     auto resultType = x.getType();
     $_state.addOperands({condition, x, y});
@@ -2832,7 +2832,7 @@ def TFL_SelectV2Op : TFL_Op<"select_v2", [
     TFL_TensorOf<[F32, I1, I8, I16, I32, I64, QI8, QUI8, QI16, TFL_Quint8]>:$output);
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$cond, "Value":$x, "Value":$y),
+    OpBuilder<(ins "Value":$cond, "Value":$x, "Value":$y),
     [{
     BuildSelectV2Op(&$_builder, $_state, cond, x, y);
   }]>];
@@ -3009,7 +3009,7 @@ def TFL_TanhOp: TFL_Op<"tanh", [
   // non-quantization tablegen patterns. Currently, it is used by the
   // elementwise-move reordering pattern in the optimize_patterns.td
   let builders = [
-    OpBuilderDAG<(ins "Value":$input),
+    OpBuilder<(ins "Value":$input),
     [{
       $_state.addOperands({input});
       $_state.addTypes(input.getType());
@@ -3083,7 +3083,7 @@ def TFL_TopKV2Op: TFL_Op<"topk_v2", [
     TFL_I32Tensor:$indices);
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$input, "Value":$k),
+    OpBuilder<(ins "Value":$input, "Value":$k),
     [{ BuildTopKOp(&$_builder, $_state, input, k); }]>];
 
   let hasOptions = 1;
@@ -3152,7 +3152,7 @@ def TFL_UnpackOp : TFL_Op<"unpack", [
   );
 
   let extraClassDeclaration = [{
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
   }];
 
   let hasOptions = 1;
@@ -3628,7 +3628,7 @@ def TFL_QConstOp : Op<TFL_Dialect, "pseudo_qconst", [
   let results = (outs TFL_TensorOf<[QUI8, QI8, QI16, QUI16, TFL_Quint8]>:$output);
 
   let builders = [
-    OpBuilderDAG<(ins "TypeAttr":$qtype, "Attribute":$value),
+    OpBuilder<(ins "TypeAttr":$qtype, "Attribute":$value),
     [{
       $_state.addAttribute("qtype", qtype);
       $_state.addAttribute("value", value);
@@ -3657,7 +3657,7 @@ def TFL_SparseQConstOp : Op<TFL_Dialect, "pseudo_sparse_qconst", [
   let results = (outs TFL_TensorOf<[QUI8, QI8, QI16, QUI16, TFL_Quint8]>:$output);
 
   let builders = [
-    OpBuilderDAG<(ins "TypeAttr":$qtype, "Attribute":$value,
+    OpBuilder<(ins "TypeAttr":$qtype, "Attribute":$value,
       "SparsityParameterAttr":$s_param, "Attribute":$compressed_data),
     [{
       $_state.addTypes(qtype.getValue());
@@ -4046,7 +4046,7 @@ def TFL_UnidirectionalSequenceLSTMOp :
     std::vector<int> GetStatefulOperands() { return {18, 19}; }
 
     // Compatiable return types check
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r);
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r);
   }];
 }
 

tensorflow/compiler/mlir/tensorflow/ir/tf_device.cc

@@ -179,8 +179,7 @@ LogicalResult Verify(ParallelExecuteOp op) {
 
 // static
 void ParallelExecuteOp::build(OpBuilder& builder, OperationState& state,
-                              int num_regions,
+                              int num_regions, TypeRange output_types) {
-                              llvm::ArrayRef<Type> output_types) {
   DCHECK_GE(num_regions, 2);
   for (int i = 0; i < num_regions; ++i) {
     Region* region = state.addRegion();
@@ -203,10 +202,7 @@ Operation::result_range ParallelExecuteOp::GetRegionOutputs(
     return_value_offset +=
         GetRegionBlockWithIndex(region_id).getTerminator()->getNumOperands();
 
-  Operation::result_range region_results(getOperation(),
+  return getResults().slice(return_value_offset, num_region_results);
-                                         /*startIndex=*/return_value_offset,
-                                         /*count=*/num_region_results);
-  return region_results;
 }
 
 bool ParallelExecuteOp::RegionWrapsSingleOp(unsigned index) {

tensorflow/compiler/mlir/tensorflow/ir/tf_device_ops.td

@@ -76,7 +76,7 @@ This op captures all needed live-in values.
   }];
 
   let builders = [
-    OpBuilderDAG<(ins "StringAttr":$device, "ArrayRef<Type>":$result_types),
+    OpBuilder<(ins "StringAttr":$device, "TypeRange":$result_types),
     [{
         $_state.addAttribute("device", device);
         $_state.addTypes(result_types);
@@ -98,7 +98,7 @@ The `tf_device.return` operation terminates and returns values from a
   );
 
   let builders = [
-    OpBuilderDAG<(ins),
+    OpBuilder<(ins),
     [{
       build($_builder, $_state, {});
     }]>
@@ -169,7 +169,7 @@ def TfDevice_ParallelExecuteOp : TfDevice_Op<"parallel_execute",
   }];
 
   let builders = [
-    OpBuilderDAG<(ins "int":$num_regions, "llvm::ArrayRef<Type>":$output_types)>,
+    OpBuilder<(ins "int":$num_regions, "TypeRange":$output_types)>,
   ];
 
   let verifier = [{ return Verify(*this); }];
@@ -294,11 +294,11 @@ For example:
   }];
 
   let builders = [
-    OpBuilderDAG<(ins "int":$n,
+    OpBuilder<(ins "int":$n,
       "const llvm::SmallDenseMap<StringRef, llvm::SmallVector<StringRef, 4>>&":$devices,
       "llvm::ArrayRef<std::pair<ValueRange, Type>>":$replicated_inputs,
       "ValueRange":$packed_inputs, "TypeRange":$replica_output_types)>,
-    OpBuilderDAG<(ins "int":$n, "llvm::Optional<DictionaryAttr>":$devices,
+    OpBuilder<(ins "int":$n, "llvm::Optional<DictionaryAttr>":$devices,
       "llvm::ArrayRef<std::pair<ValueRange, Type>>":$replicated_inputs,
       "ValueRange":$packed_inputs, "TypeRange":$replica_output_types)>,
   ];
@@ -330,7 +330,7 @@ used to form the cluster.
   let regions = (region SizedRegion<1>:$body);
 
   let builders = [
-    OpBuilderDAG<(ins "ArrayRef<Type>":$resultTypes),
+    OpBuilder<(ins "TypeRange":$resultTypes),
     [{
       build($_builder, $_state, resultTypes, mlir::StringAttr {});
     }]>

tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td

@@ -144,7 +144,7 @@ def TfExecutor_FetchOp : TfExecutor_Op<"fetch",
   );
 
   let builders = [
-    OpBuilderDAG<(ins),
+    OpBuilder<(ins),
     [{
       build($_builder, $_state, {});
     }]>
@@ -229,7 +229,7 @@ def TfExecutor_YieldOp : TfExecutor_Op<"yield",
   );
 
   let builders = [
-    OpBuilderDAG<(ins),
+    OpBuilder<(ins),
     [{
       build($_builder, $_state, {});
     }]>
@@ -460,7 +460,7 @@ def TfExecutor_NextIterationSourceOp : TfExecutor_Op<"NextIteration.Source",
   );
 
   let builders = [
-    OpBuilderDAG<(ins "Type":$result_type,
+    OpBuilder<(ins "Type":$result_type,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
     [{
       Type token_type = TokenType::get($_builder.getContext());
@@ -530,7 +530,7 @@ def TfExecutor_NextIterationSinkOp : TfExecutor_Op<"NextIteration.Sink",
   );
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$token, "ArrayRef<Value>":$operands,
+    OpBuilder<(ins "Value":$token, "ArrayRef<Value>":$operands,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
     [{
       assert(operands.size() >= 1 && "tf_executor.NextIteration.Sink builder "
@@ -618,7 +618,7 @@ def TfExecutor_ControlTriggerOp : TfExecutor_Op<"ControlTrigger",
   let hasCanonicalizer = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "ArrayRef<Value>":$operands,
+    OpBuilder<(ins "ArrayRef<Value>":$operands,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes),
     [{
       assert(operands.size() >= 1 && "tf_executor.ControlTrigger builder "

tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td

@@ -2227,7 +2227,7 @@ of `data_format`, see below for details.}]>:$input,
     StringRef GetOptimalLayout(const RuntimeDevices& devices);
     LogicalResult UpdateDataFormat(StringRef data_format);
     // InferTypeOpInterface:
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return ArraysAreCastCompatible(l, r);
     }
   }];
@@ -2348,7 +2348,7 @@ out_channels]`. `in_channels` must match between `input` and `filter`.}]>:$filte
 
   let extraClassDeclaration = [{
     // InferTypeOpInterface:
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return ArraysAreCastCompatible(l, r);
     }
   }];
@@ -3923,7 +3923,7 @@ tf.math.equal(x, y) ==> array([True,  True])
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$x, "Value":$y,
+    OpBuilder<(ins "Value":$x, "Value":$y,
       "BoolAttr":$incompatible_shape_error)>
   ];
 
@@ -4073,7 +4073,7 @@ dimension of size 1 added.}]>:$output
   TF_DerivedOperandTypeAttr Tdim = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$condition, "Value":$dim)>
+    OpBuilder<(ins "Value":$condition, "Value":$dim)>
   ];
 }
 
@@ -4460,7 +4460,7 @@ Equivalent to np.full
   let hasFolder = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$dims, "Value":$value)>
+    OpBuilder<(ins "Value":$dims, "Value":$value)>
   ];
 }
 
@@ -8042,7 +8042,7 @@ retained with length 1.
   TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$input, "Value":$reduction_indices,
+    OpBuilder<(ins "Value":$input, "Value":$reduction_indices,
       "BoolAttr":$keep_dims)>
   ];
 }
@@ -9060,7 +9060,7 @@ def TF_NotEqualOp : TF_Op<"NotEqual", [Commutative, NoSideEffect]> {
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$x, "Value":$y,
+    OpBuilder<(ins "Value":$x, "Value":$y,
       "BoolAttr":$incompatible_shape_error)>
   ];
 
@@ -9179,7 +9179,7 @@ output =
   TF_DerivedOperandTypeAttr TI = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$indices, "Value":$depth, "Value":$on_value,
+    OpBuilder<(ins "Value":$indices, "Value":$depth, "Value":$on_value,
       "Value":$off_value, "IntegerAttr":$axis)>
   ];
 
@@ -10394,7 +10394,7 @@ tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
   TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$start, "Value":$limit, "Value":$delta)>
+    OpBuilder<(ins "Value":$start, "Value":$limit, "Value":$delta)>
   ];
 }
 
@@ -10447,7 +10447,7 @@ of the tensor. Rank is also known as "order", "degree", or "ndims."
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$input)>
+    OpBuilder<(ins "Value":$input)>
   ];
 
   let hasFolder = 1;
@@ -10796,7 +10796,7 @@ reshape(t, []) ==> 7
   TF_DerivedOperandTypeAttr Tshape = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$tensor, "Value":$shape)>
+    OpBuilder<(ins "Value":$tensor, "Value":$shape)>
   ];
 
   let verifier = [{
@@ -13298,7 +13298,7 @@ def TF_SelectV2Op : TF_Op<"SelectV2", [NoSideEffect, ResultsBroadcastableShape]>
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$condition, "Value":$e, "Value":$t)>
+    OpBuilder<(ins "Value":$condition, "Value":$e, "Value":$t)>
   ];
 }
 
@@ -13461,7 +13461,7 @@ shape(t) ==> [2, 2, 3]
   }];
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$input, "BoolAttr":$use32Bit)>
+    OpBuilder<(ins "Value":$input, "BoolAttr":$use32Bit)>
   ];
 
   let hasFolder = 1;
@@ -14137,7 +14137,7 @@ regular convolution.}]>:$paddings
   let verifier = [{ return Verify(*this); }];
 
   let extraClassDeclaration = [{
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return ArraysAreCastCompatible(l, r);
     }
   }];
@@ -15608,7 +15608,7 @@ retained with length 1.
   TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$input, "Value":$reduction_indices,
+    OpBuilder<(ins "Value":$input, "Value":$reduction_indices,
       "BoolAttr":$keep_dims)>
   ];
 
@@ -16801,7 +16801,7 @@ to the indices.}]>:$output
   let verifier = [{ return Verify(*this); }];
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$tensor, "Value":$indices, "Value":$updates),
+    OpBuilder<(ins "Value":$tensor, "Value":$indices, "Value":$updates),
     [{build($_builder, $_state, tensor.getType(), tensor, indices, updates);}]>
   ];
 }
@@ -16999,7 +16999,7 @@ The output `y` has the same rank as `x`. The shapes of `x` and `y` satisfy:
   TF_DerivedOperandTypeAttr Tperm = TF_DerivedOperandTypeAttr<1>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$x, "Value":$perm)>
+    OpBuilder<(ins "Value":$x, "Value":$perm)>
   ];
 
   let verifier = [{
@@ -17670,7 +17670,7 @@ for binary operators.
 
   let extraClassDeclaration = [{
     // InferTypeOpInterface:
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return ArraysAreCastCompatible(l, r);
     }
   }];

tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td

@@ -579,8 +579,8 @@ def TF_IntTypeAttr : TypeAttrBase<"IntegerType", "integer type"> {
 // Mixin class defining a builder for binary ops supporting broadcast
 // behavior. The result type has the same element type as both operands.
 class WithBroadcastableBinOpBuilder {
-  list<OpBuilderDAG> builders = [
+  list<OpBuilder> builders = [
-    OpBuilderDAG<(ins "Value":$x, "Value":$y),
+    OpBuilder<(ins "Value":$x, "Value":$y),
     [{
   auto resultType =
       OpTrait::util::getBroadcastedType(x.getType(), y.getType());
@@ -593,8 +593,8 @@ class WithBroadcastableBinOpBuilder {
 // Mixin class defining a builder for comparison ops supporting broadcast
 // behavior. The result type has bool element type.
 class WithBroadcastableCmpOpBuilder {
-  list<OpBuilderDAG> builders = [
+  list<OpBuilder> builders = [
-    OpBuilderDAG<(ins "Value":$x, "Value":$y),
+    OpBuilder<(ins "Value":$x, "Value":$y),
     [{
   Type resultType;
   if (x.getType().isa<UnrankedTensorType>() ||

tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td

@@ -203,14 +203,14 @@ def TF_ConstOp : TF_Op<"Const", [ConstantLike, NoSideEffect,
   TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Attribute":$value)>,
+    OpBuilder<(ins "Attribute":$value)>,
-    OpBuilderDAG<(ins "Type":$type, "Attribute":$value)>,
+    OpBuilder<(ins "Type":$type, "Attribute":$value)>,
   ];
 
   let hasFolder = 1;
 
   let extraClassDeclaration = [{
-    static bool isCompatibleReturnTypes(ArrayRef<Type> l, ArrayRef<Type> r) {
+    static bool isCompatibleReturnTypes(TypeRange l, TypeRange r) {
       return BroadcastCompatible(l, r);
     }
   }];
@@ -410,7 +410,7 @@ else_branch: A region that computes the outputs of the op if cond = false.
   }];
 
   let builders = [
-    OpBuilderDAG<(ins "TypeRange":$resultTypes, "ValueRange":$operands,
+    OpBuilder<(ins "TypeRange":$resultTypes, "ValueRange":$operands,
       "llvm::ArrayRef<::mlir::NamedAttribute>":$attributes,
       "unsigned":$numRegions),
     [{
@@ -1213,7 +1213,7 @@ as true/false for a branch condition.
   TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
 
   let builders = [
-    OpBuilderDAG<(ins "Value":$value),
+    OpBuilder<(ins "Value":$value),
     [{
       build($_builder, $_state, RankedTensorType::get({}, $_builder.getI1Type()),
             value);

tensorflow/compiler/mlir/tensorflow/ir/tf_types.cc

@@ -198,7 +198,7 @@ ArrayRef<TensorType> TensorFlowTypeWithSubtype::GetSubtypes() {
 
 // TODO(jpienaar): BroadcastCompatible and HasCompatibleElementTypes have
 // similar structure that could be extracted into helper method.
-bool BroadcastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
+bool BroadcastCompatible(TypeRange lhs, TypeRange rhs) {
   if (lhs.size() != rhs.size()) return false;
   for (auto types : llvm::zip(lhs, rhs)) {
     // Drop ref types because they don't affect broadcast compatibility. E.g.,
@@ -349,7 +349,7 @@ bool HasCompatibleElementTypes(Type lhs, Type rhs,
   return GetCastCompatibleType(lhs, rhs, may_ignore_ref_type_lhs) != nullptr;
 }
 
-bool AreCastCompatible(ArrayRef<Type> types) {
+bool AreCastCompatible(TypeRange types) {
   Type common = types.front();
   for (auto type : types.drop_front()) {
     Type refined_type =
@@ -360,7 +360,7 @@ bool AreCastCompatible(ArrayRef<Type> types) {
   return true;
 }
 
-bool ArraysAreCastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs) {
+bool ArraysAreCastCompatible(TypeRange lhs, TypeRange rhs) {
   if (lhs.size() != rhs.size()) return false;
   for (auto pair : llvm::zip(lhs, rhs)) {
     auto lhs_i = std::get<0>(pair);

tensorflow/compiler/mlir/tensorflow/ir/tf_types.h

@@ -287,7 +287,7 @@ mlir::Type GetCastCompatibleType(mlir::Type a, mlir::Type b,
                                  bool may_ignore_ref_type_a);
 
 // Returns whether two arrays of Type are broadcast compatible.
-bool BroadcastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs);
+bool BroadcastCompatible(TypeRange lhs, TypeRange rhs);
 
 // Returns whether the two elemental types are compatible. Shapes are compatible
 // if:
@@ -305,11 +305,11 @@ bool HasCompatibleElementTypes(Type lhs, Type rhs,
 // another. In other words, a single run-time value is legal for both the types.
 // For example, tensor<*xf32>, tensor<?xf32> and tensor<3xf32> are cast
 // compatible.
-bool AreCastCompatible(ArrayRef<Type> types);
+bool AreCastCompatible(TypeRange types);
 
 // Returns true if corresponding elements of lhs and rhs AreCastCompatible and
 // lhs and rhs are the same length.
-bool ArraysAreCastCompatible(ArrayRef<Type> lhs, ArrayRef<Type> rhs);
+bool ArraysAreCastCompatible(TypeRange lhs, TypeRange rhs);
 
 // If `ty` is a tensor type and its element type has subtypes, then returns a
 // new type of same shape but dropped subtypes for the element type.

tensorflow/compiler/mlir/tensorflow/transforms/constant_fold.cc

@@ -80,7 +80,7 @@ LogicalResult ConstantFoldFallbackHook(
   // If any of the result types are variants, don't try to constant fold them.
   // This creates opaque variant constants which lose information and would
   // require "raising" later.
-  for (auto& type : inst->getResultTypes()) {
+  for (auto type : inst->getResultTypes()) {
     if (auto tensor_type = type.dyn_cast<TensorType>()) {
       if (tensor_type.getElementType().isa<VariantType>()) {
         return failure();

tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc

@@ -890,7 +890,7 @@ bool ShapeInference::RefineTypeForPassThroughOperands(Operation* op,
                                                       OperandRange operands,
                                                       ResultRange results) {
   bool changed = false;
-  for (auto entry : zip(operands, results)) {
+  for (auto entry : llvm::zip(operands, results)) {
     Type operand_type = std::get<0>(entry).getType();
     Value result = std::get<1>(entry);
     TensorType result_type = result.getType().cast<TensorType>();
@@ -925,7 +925,7 @@ bool ShapeInference::RefineShapeForPassThroughOps(Operation* op) {
   };
 
   bool changed = false;
-  for (auto entry : zip(op->getOperands(), op->getResults())) {
+  for (auto entry : llvm::zip(op->getOperands(), op->getResults())) {
     TensorType operand_type = std::get<0>(entry).getType().cast<TensorType>();
     Value result = std::get<1>(entry);
     TensorType result_type = result.getType().cast<TensorType>();

tensorflow/compiler/mlir/tfr/ir/tfr_ops.td

@@ -267,7 +267,7 @@ def TFR_ConstOp : TFR_Op<"constant", [ConstantLike, NoSideEffect]> {
   let hasFolder = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "Attribute":$value),
+    OpBuilder<(ins "Attribute":$value),
     [{
       auto* ctx = value.getContext();
       $_state.addAttribute("value", value);
@@ -425,7 +425,7 @@ def TFR_TFRFuncOp : TFR_Op<"func", [HasParent<"ModuleOp">,
   let skipDefaultBuilders = 1;
 
   let builders = [
-    OpBuilderDAG<(ins "StringRef":$name, "FunctionType":$type,
+    OpBuilder<(ins "StringRef":$name, "FunctionType":$type,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>
   ];
 

tensorflow/compiler/mlir/tools/kernel_gen/BUILD

@@ -68,6 +68,7 @@ cc_library(
         "@llvm-project//mlir:GPUTransforms",
         "@llvm-project//mlir:IR",
         "@llvm-project//mlir:LLVMDialect",
+        "@llvm-project//mlir:LLVMToLLVMIRTranslation",
         "@llvm-project//mlir:LinalgOps",
         "@llvm-project//mlir:LinalgTransforms",
         "@llvm-project//mlir:NVVMDialect",
@@ -86,7 +87,7 @@ cc_library(
         "@llvm-project//mlir:StandardOps",
         "@llvm-project//mlir:StandardOpsTransforms",
         "@llvm-project//mlir:Support",
-        "@llvm-project//mlir:TargetLLVMIR",
+        "@llvm-project//mlir:ToLLVMIRTranslation",
         "@llvm-project//mlir:Transforms",
     ],
 )
@@ -117,8 +118,8 @@ tf_cc_binary(
         "@llvm-project//llvm:X86Disassembler",  # fixdeps: keep
         "@llvm-project//mlir:ExecutionEngineUtils",
         "@llvm-project//mlir:Pass",
-        "@llvm-project//mlir:TargetLLVMIR",
+        "@llvm-project//mlir:LLVMToLLVMIRTranslation",
-        "@llvm-project//mlir:TargetLLVMIRModuleTranslation",
+        "@llvm-project//mlir:ToLLVMIRTranslation",
     ] + if_llvm_system_z_available([
         "@llvm-project//llvm:SystemZCodeGen",  # fixdeps: keep
     ]) + if_llvm_aarch64_available([

tensorflow/compiler/mlir/tools/kernel_gen/ir/tf_framework_ops.td

@@ -80,12 +80,12 @@ def TFFramework_TFAllocOp : TFFramework_Op<"alloc",
   let results = (outs Res<AnyMemRef, "", [MemAlloc<DefaultResource>]>:$result);
 
   let builders = [
-    OpBuilderDAG<(ins "MemRefType":$memref_type, "Value":$ctx),
+    OpBuilder<(ins "MemRefType":$memref_type, "Value":$ctx),
     [{
       $_state.addOperands(ctx);
       $_state.types.push_back(memref_type);
     }]>,
-    OpBuilderDAG<(ins "MemRefType":$memref_type, "Value":$ctx,
+    OpBuilder<(ins "MemRefType":$memref_type, "Value":$ctx,
       "ValueRange":$dyn_sizes),
     [{
       build($_builder, $_state, memref_type, ctx);

tensorflow/compiler/mlir/tools/kernel_gen/kernel_creator.cc

@@ -31,8 +31,6 @@ limitations under the License.
 #include "mlir/Dialect/GPU/ParallelLoopMapper.h"  // from @llvm-project
 #include "mlir/Dialect/GPU/Passes.h"  // from @llvm-project
 #include "mlir/Dialect/LLVMIR/LLVMDialect.h"  // from @llvm-project
-#include "mlir/Dialect/LLVMIR/NVVMDialect.h"  // from @llvm-project
-#include "mlir/Dialect/LLVMIR/ROCDLDialect.h"  // from @llvm-project
 #include "mlir/Dialect/Linalg/Passes.h"  // from @llvm-project
 #include "mlir/Dialect/Linalg/Transforms/Transforms.h"  // from @llvm-project
 #include "mlir/Dialect/SCF/Passes.h"  // from @llvm-project
@@ -46,7 +44,7 @@ limitations under the License.
 #include "mlir/Parser.h"  // from @llvm-project
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Pass/PassManager.h"  // from @llvm-project
-#include "mlir/Target/LLVMIR.h"  // from @llvm-project
+#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h"  // from @llvm-project
 #include "mlir/Target/LLVMIR/Dialect/NVVM/NVVMToLLVMIRTranslation.h"  // from @llvm-project
 #include "mlir/Target/LLVMIR/Dialect/ROCDL/ROCDLToLLVMIRTranslation.h"  // from @llvm-project
 #include "mlir/Transforms/Bufferize.h"  // from @llvm-project
@@ -435,12 +433,9 @@ StatusOr<mlir::OwningModuleRef> GenerateKernelForTfCode(
   mlir::DialectRegistry registry;
   mlir::RegisterAllTensorFlowDialects(registry);
   registry.insert<mlir::chlo::HloClientDialect, mlir::mhlo::MhloDialect>();
-  registry.insert<mlir::NVVM::NVVMDialect, mlir::ROCDL::ROCDLDialect>();
-  registry.addDialectInterface<mlir::NVVM::NVVMDialect,
-                               mlir::NVVMDialectLLVMIRTranslationInterface>();
-  registry.addDialectInterface<mlir::ROCDL::ROCDLDialect,
-                               mlir::ROCDLDialectLLVMIRTranslationInterface>();
   mlir::registerLLVMDialectTranslation(registry);
+  mlir::registerNVVMDialectTranslation(registry);
+  mlir::registerROCDLDialectTranslation(registry);
   context.appendDialectRegistry(registry);
   mlir::OwningModuleRef module = mlir::parseSourceString(tf_code, &context);
 

tensorflow/compiler/mlir/tools/kernel_gen/tf_to_kernel.cc

@@ -34,7 +34,7 @@
 #include "llvm/Target/TargetMachine.h"
 #include "mlir/ExecutionEngine/OptUtils.h"  // from @llvm-project
 #include "mlir/Pass/PassManager.h"  // from @llvm-project
-#include "mlir/Target/LLVMIR.h"  // from @llvm-project
+#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h"  // from @llvm-project
 #include "mlir/Target/LLVMIR/Export.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/init_mlir.h"
 #include "tensorflow/compiler/mlir/tools/kernel_gen/kernel_creator.h"

tensorflow/compiler/mlir/tools/kernel_gen/transforms/BUILD

@@ -126,8 +126,10 @@ cc_library(
         "@llvm-project//mlir:StandardOps",
         "@llvm-project//mlir:StandardOpsTransforms",
         "@llvm-project//mlir:Support",
-        "@llvm-project//mlir:TargetLLVMIR",
+        "@llvm-project//mlir:LLVMToLLVMIRTranslation",
-        "@llvm-project//mlir:TargetLLVMIRModuleTranslation",
+        "@llvm-project//mlir:NVVMToLLVMIRTranslation",
+        "@llvm-project//mlir:ROCDLToLLVMIRTranslation",
+        "@llvm-project//mlir:ToLLVMIRTranslation",
         "@llvm-project//mlir:TensorDialect",
         "@llvm-project//mlir:TensorTransforms",
         "@llvm-project//mlir:Transforms",

tensorflow/compiler/mlir/tools/kernel_gen/transforms/gpu_kernel_to_blob_pass.cc

@@ -15,7 +15,6 @@ limitations under the License.
 
 #include "llvm/Transforms/Utils/Cloning.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"  // from @llvm-project
-#include "mlir/Target/LLVMIR.h"  // from @llvm-project
 #include "mlir/Target/LLVMIR/Export.h"  // from @llvm-project
 #include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"

tensorflow/compiler/xla/service/cpu/BUILD

@@ -1162,10 +1162,10 @@ cc_library(
         "@llvm-project//llvm:Linker",
         "@llvm-project//mlir:CFGTransforms",
         "@llvm-project//mlir:IR",
+        "@llvm-project//mlir:LLVMToLLVMIRTranslation",
         "@llvm-project//mlir:LinalgTransforms",
         "@llvm-project//mlir:Pass",
-        "@llvm-project//mlir:TargetLLVMIR",
+        "@llvm-project//mlir:ToLLVMIRTranslation",
-        "@llvm-project//mlir:TargetLLVMIRModuleTranslation",
         "@llvm-project//mlir:Transforms",
         "@llvm-project//mlir:VectorToLLVM",
     ],

tensorflow/compiler/xla/service/cpu/mlir_emitter.cc

@@ -23,7 +23,6 @@ limitations under the License.
 #include "mlir/IR/BuiltinOps.h"  // from @llvm-project
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Pass/PassManager.h"  // from @llvm-project
-#include "mlir/Target/LLVMIR.h"  // from @llvm-project
 #include "mlir/Target/LLVMIR/Export.h"  // from @llvm-project
 #include "mlir/Transforms/Passes.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/xla/hlo_utils.h"

third_party/llvm/workspace.bzl

@@ -4,8 +4,8 @@ load("//third_party:repo.bzl", "tf_http_archive")
 
 def repo(name):
     """Imports LLVM."""
-    LLVM_COMMIT = "5d7e0a23c6f2051d4caf8f8c8821790c40b584be"
+    LLVM_COMMIT = "c907681b077c6acf95c3ddca6611639c29559e40"
-    LLVM_SHA256 = "dc100f5eddb35b694454ecc8cbf654b238f2e2684784d33d40536500297e9212"
+    LLVM_SHA256 = "2929f1730e9ba4fea489400d81e5da21a4e79c94fea9dd3fd12e042350ff19ea"
 
     tf_http_archive(
         name = name,

third_party/mlir/BUILD

@@ -201,6 +201,7 @@ cc_library(
         "include/mlir-c/BuiltinTypes.h",
         "include/mlir-c/Diagnostics.h",
         "include/mlir-c/Dialect/Standard.h",
+        "include/mlir-c/ExecutionEngine.h",
         "include/mlir-c/IR.h",
         "include/mlir-c/IntegerSet.h",
         "include/mlir-c/Pass.h",
@@ -219,6 +220,7 @@ cc_library(
     ],
     includes = ["include"],
     deps = [
+        ":ConversionPassIncGen",
         ":IR",
         ":InferTypeOpInterface",
         ":Parser",
@@ -229,6 +231,35 @@ cc_library(
     ],
 )
 
+cc_library(
+    name = "CAPIConversion",
+    srcs = ["lib/CAPI/Conversion/Passes.cpp"],
+    hdrs = ["include/mlir-c/Conversion.h"],
+    includes = ["include"],
+    deps = [
+        ":CAPIIR",
+        ":ConversionPassIncGen",
+        ":ConversionPasses",
+        ":Pass",
+    ],
+)
+
+cc_library(
+    name = "CAPIExecutionEngine",
+    srcs = ["lib/CAPI/ExecutionEngine/ExecutionEngine.cpp"],
+    hdrs = [
+        "include/mlir-c/ExecutionEngine.h",
+        "include/mlir/CAPI/ExecutionEngine.h",
+    ],
+    includes = ["include"],
+    deps = [
+        ":CAPIIR",
+        ":ExecutionEngine",
+        ":LLVMToLLVMIRTranslation",
+        "@llvm-project//llvm:Support",
+    ],
+)
+
 cc_library(
     name = "CAPITransforms",
     srcs = ["lib/CAPI/Transforms/Passes.cpp"],
@@ -259,6 +290,7 @@ cc_library(
     deps = [
         ":AllPassesAndDialectsNoRegistration",
         ":CAPIIR",
+        ":LLVMToLLVMIRTranslation",
     ],
 )
 
@@ -1130,6 +1162,14 @@ gentbl(
             "-gen-pass-decls -name Conversion",
             "include/mlir/Conversion/Passes.h.inc",
         ),
+        (
+            "-gen-pass-capi-header --prefix Conversion",
+            "include/mlir/Conversion/Passes.capi.h.inc",
+        ),
+        (
+            "-gen-pass-capi-impl --prefix Conversion",
+            "include/mlir/Conversion/Passes.capi.cpp.inc",
+        ),
     ],
     tblgen = ":mlir-tblgen",
     td_file = "include/mlir/Conversion/Passes.td",
@@ -3535,7 +3575,7 @@ cc_library(
 )
 
 cc_library(
-    name = "TargetLLVMIRModuleTranslation",
+    name = "ToLLVMIRTranslation",
     srcs = [
         "lib/Target/LLVMIR/DebugTranslation.cpp",
         "lib/Target/LLVMIR/DebugTranslation.h",
@@ -3573,7 +3613,7 @@ cc_library(
         ":LLVMAVX512",
         ":LLVMAVX512ConversionIncGen",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3590,7 +3630,7 @@ cc_library(
         ":LLVMArmNeonConversionIncGen",
         ":LLVMArmNeonIncGen",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3606,7 +3646,7 @@ cc_library(
         ":LLVMArmSVE",
         ":LLVMArmSVEConversionIncGen",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3622,7 +3662,7 @@ cc_library(
         ":NVVMConversionIncGen",
         ":NVVMDialect",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3638,7 +3678,7 @@ cc_library(
         ":ROCDLConversionIncGen",
         ":ROCDLDialect",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3654,7 +3694,7 @@ cc_library(
         ":LLVMConversionIncGen",
         ":LLVMDialect",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Support",
     ],
@@ -3669,7 +3709,7 @@ cc_library(
         ":IR",
         ":OpenMPDialect",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:FrontendOpenMP",
         "@llvm-project//llvm:Support",
@@ -3677,32 +3717,46 @@ cc_library(
 )
 
 cc_library(
-    name = "TargetLLVMIR",
+    name = "AllToLLVMIRTranslations",
+    hdrs = ["include/mlir/Target/LLVMIR/Dialect/All.h"],
+    includes = ["include"],
+    deps = [
+        ":LLVMAVX512ToLLVMIRTranslation",
+        ":LLVMArmNeonToLLVMIRTranslation",
+        ":LLVMArmSVEToLLVMIRTranslation",
+        ":LLVMToLLVMIRTranslation",
+        ":NVVMToLLVMIRTranslation",
+        ":OpenMPToLLVMIRTranslation",
+        ":ROCDLToLLVMIRTranslation",
+    ],
+)
+
+cc_library(
+    name = "ToLLVMIRTranslationRegistration",
+    srcs = ["lib/Target/LLVMIR/ConvertToLLVMIR.cpp"],
+    includes = ["include"],
+    deps = [
+        ":AllToLLVMIRTranslations",
+        ":IR",
+        ":ToLLVMIRTranslation",
+        ":Translation",
+        "@llvm-project//llvm:Core",
+        "@llvm-project//llvm:Support",
+    ],
+)
+
+cc_library(
+    name = "FromLLVMIRTranslation",
     srcs = [
         "lib/Target/LLVMIR/ConvertFromLLVMIR.cpp",
-        "lib/Target/LLVMIR/ConvertToLLVMIR.cpp",
     ],
     hdrs = ["include/mlir/Target/LLVMIR.h"],
     includes = ["include"],
     deps = [
         ":IR",
-        ":LLVMAVX512",
-        ":LLVMAVX512ToLLVMIRTranslation",
-        ":LLVMArmNeon",
-        ":LLVMArmNeonToLLVMIRTranslation",
-        ":LLVMArmSVE",
-        ":LLVMArmSVEToLLVMIRTranslation",
         ":LLVMConversionIncGen",
         ":LLVMDialect",
-        ":LLVMToLLVMIRTranslation",
-        ":NVVMDialect",
-        ":NVVMToLLVMIRTranslation",
-        ":OpenMPDialect",
-        ":OpenMPToLLVMIRTranslation",
-        ":ROCDLDialect",
-        ":ROCDLToLLVMIRTranslation",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
         ":Translation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:IRReader",
@@ -3722,11 +3776,11 @@ cc_library(
     ],
     includes = ["include"],
     deps = [
+        ":AllToLLVMIRTranslations",
         ":IR",
         ":LLVMDialect",
         ":Support",
-        ":TargetLLVMIR",
+        ":ToLLVMIRTranslation",
-        ":TargetLLVMIRModuleTranslation",
         ":Translation",
         "@llvm-project//llvm:BitReader",
         "@llvm-project//llvm:BitWriter",
@@ -3789,14 +3843,9 @@ cc_library(
     name = "AllTranslations",
     hdrs = ["include/mlir/InitAllTranslations.h"],
     deps = [
-        ":LLVMAVX512ToLLVMIRTranslation",
+        ":FromLLVMIRTranslation",
-        ":LLVMArmNeonToLLVMIRTranslation",
-        ":LLVMArmSVEToLLVMIRTranslation",
-        ":LLVMToLLVMIRTranslation",
-        ":NVVMToLLVMIRTranslation",
-        ":ROCDLToLLVMIRTranslation",
         ":SPIRVTranslateRegistration",
-        ":TargetLLVMIR",
+        ":ToLLVMIRTranslationRegistration",
     ],
 )
 
@@ -4011,13 +4060,14 @@ cc_binary(
     srcs = ["tools/mlir-cpu-runner/mlir-cpu-runner.cpp"],
     linkopts = ["-ldl"],
     deps = [
+        ":AllToLLVMIRTranslations",
         ":ExecutionEngineUtils",
         ":IR",
         ":LLVMDialect",
+        ":LLVMToLLVMIRTranslation",
         ":MlirJitRunner",
-        ":OpenMPDialect",
         ":OpenMPToLLVMIRTranslation",
-        ":TargetLLVMIR",
+        ":ToLLVMIRTranslation",
         "@llvm-project//llvm:AsmParser",
         "@llvm-project//llvm:Support",
         "@llvm-project//llvm:X86AsmParser",
@@ -4094,13 +4144,14 @@ cc_binary(
         ":GPUTransforms",
         ":IR",
         ":LLVMDialect",
+        ":LLVMToLLVMIRTranslation",
         ":MlirJitRunner",
         ":NVVMDialect",
         ":NVVMToLLVMIRTranslation",
         ":Pass",
         ":StandardOps",
-        ":TargetLLVMIR",
+        ":StandardToLLVM",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         ":Transforms",
         "//devtools/build/runtime:get_runfiles_dir",
         "//third_party/gpus/cuda:cuda_headers",
@@ -4120,6 +4171,7 @@ cc_binary(
         ":GPUToVulkanTransforms",
         ":GPUTransforms",
         ":LLVMDialect",
+        ":LLVMToLLVMIRTranslation",
         ":MlirJitRunner",
         ":Pass",
         ":SPIRVDialect",
@@ -4127,8 +4179,7 @@ cc_binary(
         ":StandardOps",
         ":StandardToLLVM",
         ":StandardToSPIRV",
-        ":TargetLLVMIR",
+        ":ToLLVMIRTranslation",
-        ":TargetLLVMIRModuleTranslation",
         "@llvm-project//llvm:Support",
     ],
 )
@@ -4143,6 +4194,7 @@ cc_binary(
         ":GPUTransforms",
         ":IR",
         ":LLVMDialect",
+        ":LLVMToLLVMIRTranslation",
         ":MlirJitRunner",
         ":Pass",
         ":SPIRVConversion",
@@ -4151,8 +4203,7 @@ cc_binary(
         ":SPIRVTransforms",
         ":StandardOps",
         ":StandardToLLVM",
-        ":TargetLLVMIR",
+        ":ToLLVMIRTranslation",
-        ":TargetLLVMIRModuleTranslation",
         "@llvm-project//llvm:Core",
         "@llvm-project//llvm:Linker",
         "@llvm-project//llvm:Support",
@@ -4940,7 +4991,7 @@ cc_library(
         ":StandardOps",
         ":StandardToLLVM",
         ":Support",
-        ":TargetLLVMIRModuleTranslation",
+        ":ToLLVMIRTranslation",
         ":Transforms",
         ":VectorOps",
         "@llvm-project//llvm:Core",

third_party/mlir/test.BUILD

@@ -124,6 +124,27 @@ gentbl(
     test = True,
 )
 
+gentbl(
+    name = "TestAttrDefsIncGen",
+    strip_include_prefix = "lib/Dialect/Test",
+    tbl_outs = [
+        (
+            "-gen-attrdef-decls",
+            "lib/Dialect/Test/TestAttrDefs.h.inc",
+        ),
+        (
+            "-gen-attrdef-defs",
+            "lib/Dialect/Test/TestAttrDefs.cpp.inc",
+        ),
+    ],
+    tblgen = "@llvm-project//mlir:mlir-tblgen",
+    td_file = "lib/Dialect/Test/TestAttrDefs.td",
+    td_srcs = [
+        ":TestOpTdFiles",
+    ],
+    test = True,
+)
+
 gentbl(
     name = "TestTypeDefsIncGen",
     strip_include_prefix = "lib/Dialect/Test",
@@ -148,6 +169,7 @@ gentbl(
 cc_library(
     name = "TestDialect",
     srcs = [
+        "lib/Dialect/Test/TestAttributes.cpp",
         "lib/Dialect/Test/TestDialect.cpp",
         "lib/Dialect/Test/TestInterfaces.cpp",
         "lib/Dialect/Test/TestPatterns.cpp",
@@ -155,6 +177,7 @@ cc_library(
         "lib/Dialect/Test/TestTypes.cpp",
     ],
     hdrs = [
+        "lib/Dialect/Test/TestAttributes.h",
         "lib/Dialect/Test/TestDialect.h",
         "lib/Dialect/Test/TestInterfaces.h",
         "lib/Dialect/Test/TestTypes.h",
@@ -163,6 +186,7 @@ cc_library(
         "lib/Dialect/Test",
     ],
     deps = [
+        ":TestAttrDefsIncGen",
         ":TestInterfacesIncGen",
         ":TestOpsIncGen",
         ":TestTypeDefsIncGen",
@@ -262,6 +286,7 @@ cc_library(
         "@llvm-project//mlir:GPUTransforms",
         "@llvm-project//mlir:IR",
         "@llvm-project//mlir:LLVMDialect",
+        "@llvm-project//mlir:LLVMToLLVMIRTranslation",
         "@llvm-project//mlir:LLVMTransforms",
         "@llvm-project//mlir:LinalgOps",
         "@llvm-project//mlir:LinalgTransforms",
@@ -277,8 +302,7 @@ cc_library(
         "@llvm-project//mlir:StandardOps",
         "@llvm-project//mlir:StandardOpsTransforms",
         "@llvm-project//mlir:Support",
-        "@llvm-project//mlir:TargetLLVMIR",
+        "@llvm-project//mlir:ToLLVMIRTranslation",
-        "@llvm-project//mlir:TargetLLVMIRModuleTranslation",
         "@llvm-project//mlir:TransformUtils",
         "@llvm-project//mlir:Transforms",
         "@llvm-project//mlir:VectorOps",