mlir/include/mlir/Dialect/LoopOps/LoopOps.td - llvm-project - Git at Google

 //===- Ops.td - Loop operation definitions ---------------*- tablegen -*-===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 //
 // Defines MLIR loop operations.
 //
 //===----------------------------------------------------------------------===//

 #ifndef LOOP_OPS
 #define LOOP_OPS

 include "mlir/Interfaces/LoopLikeInterface.td"
 include "mlir/Interfaces/SideEffects.td"

 def LoopOps_Dialect : Dialect {
   let name = "loop";
   let cppNamespace = "";
 }

 // Base class for Loop dialect ops.
 class Loop_Op<string mnemonic, list<OpTrait> traits = []> :
     Op<LoopOps_Dialect, mnemonic, traits> {
   // For every standard op, there needs to be a:
   //   * void print(OpAsmPrinter &p, ${C++ class of Op} op)
   //   * LogicalResult verify(${C++ class of Op} op)
   //   * ParseResult parse${C++ class of Op}(OpAsmParser &parser,
   //                                         OperationState &result)
   // functions.
   let printer = [{ return ::print(p, *this); }];
   let verifier = [{ return ::verify(*this); }];
   let parser = [{ return ::parse$cppClass(parser, result); }];
 }

 def ForOp : Loop_Op<"for",
       [DeclareOpInterfaceMethods<LoopLikeOpInterface>,
        SingleBlockImplicitTerminator<"YieldOp">,
        RecursiveSideEffects]> {
   let summary = "for operation";
   let description = [{
     The "loop.for" operation represents a loop taking 3 SSA value as operands
     that represent the lower bound, upper bound and step respectively.  The
     operation defines an SSA value for its induction variable. It has one
     region capturing the loop body. The induction variable is represented as an
     argument of this region. This SSA value always has type index, which is the
     size of the machine word. The step is a value of type index, required to be
     positive.
     The lower and upper bounds specify a half-open range: the range includes
     the lower bound but does not include the upper bound.

     The body region must contain exactly one block that terminates with
     "loop.yield".  Calling ForOp::build will create such a region and insert
     the terminator implicitly if none is defined, so will the parsing even in
     cases when it is absent from the custom format. For example:

     ```mlir
     loop.for %iv = %lb to %ub step %step {
       ... // body
     }
     ```

     `loop.for` can also operate on loop-carried variables and returns the final
     values after loop termination. The initial values of the variables are
     passed as additional SSA operands to the "loop.for" following the 3 loop
     control SSA values mentioned above (lower bound, upper bound and step). The
     operation region has equivalent arguments for each variable representing
     the value of the variable at the current iteration.

     The region must terminate with a "loop.yield" that passes all the current
     iteration variables to the next iteration, or to the "loop.for" result, if
     at the last iteration.  "loop.for" results hold the final values after the
     last iteration.

     For example, to sum-reduce a memref:

     ```mlir
     func @reduce(%buffer: memref<1024xf32>, %lb: index,
                  %ub: index, %step: index) -> (f32) {
       // Initial sum set to 0.
       %sum_0 = constant 0.0 : f32
       // iter_args binds initial values to the loop's region arguments.
       %sum = loop.for %iv = %lb to %ub step %step
           iter_args(%sum_iter = %sum_0) -> (f32) {
         %t = load %buffer[%iv] : memref<1024xf32>
         %sum_next = addf %sum_iter, %t : f32
         // Yield current iteration sum to next iteration %sum_iter or to %sum
         // if final iteration.
         loop.yield %sum_next : f32
       }
       return %sum : f32
     }
     ```

     If the "loop.for" defines any values, a yield must be explicitly present.
     The number and types of the "loop.for" results must match the initial
     values in the "iter_args" binding and the yield operands.

     Another example with a nested "loop.if" (see "loop.if" for details) to
     perform conditional reduction:

     ```mlir
     func @conditional_reduce(%buffer: memref<1024xf32>, %lb: index,
                              %ub: index, %step: index) -> (f32) {
       %sum_0 = constant 0.0 : f32
       %c0 = constant 0.0 : f32
       %sum = loop.for %iv = %lb to %ub step %step
           iter_args(%sum_iter = %sum_0) -> (f32) {
         %t = load %buffer[%iv] : memref<1024xf32>
         %cond = cmpf "ugt", %t, %c0 : f32
         %sum_next = loop.if %cond -> (f32) {
           %new_sum = addf %sum_iter, %t : f32
           loop.yield %new_sum : f32
         } else {
           loop.yield %sum_iter : f32
         }
         loop.yield %sum_next : f32
       }
       return %sum : f32
     }
     ```
   }];
   let arguments = (ins Index:$lowerBound,
                        Index:$upperBound,
                        Index:$step,
                        Variadic<AnyType>:$initArgs);
   let results = (outs Variadic<AnyType>:$results);
   let regions = (region SizedRegion<1>:$region);

   let skipDefaultBuilders = 1;
   let builders = [
     OpBuilder<"Builder *builder, OperationState &result, "
               "Value lowerBound, Value upperBound, Value step, "
               "ValueRange iterArgs = llvm::None">
   ];

   let extraClassDeclaration = [{
     Block *getBody() { return &region().front(); }
     Value getInductionVar() { return getBody()->getArgument(0); }
     OpBuilder getBodyBuilder() {
       return OpBuilder(getBody(), std::prev(getBody()->end()));
     }
     Block::BlockArgListType getRegionIterArgs() {
       return getBody()->getArguments().drop_front();
     }
     Operation::operand_range getIterOperands() {
       return getOperands().drop_front(getNumControlOperands());
     }

     void setLowerBound(Value bound) { getOperation()->setOperand(0, bound); }
     void setUpperBound(Value bound) { getOperation()->setOperand(1, bound); }
     void setStep(Value step) { getOperation()->setOperand(2, step); }

     /// Number of region arguments for loop-carried values
     unsigned getNumRegionIterArgs() {
       return getBody()->getNumArguments() - 1;
     }
     /// Number of operands controlling the loop: lb, ub, step
     unsigned getNumControlOperands() { return 3; }
     /// Does the operation hold operands for loop-carried values
     bool hasIterOperands() {
       return getOperation()->getNumOperands() > getNumControlOperands();
     }
     /// Get Number of loop-carried values
     unsigned getNumIterOperands() {
       return getOperation()->getNumOperands() - getNumControlOperands();
     }
   }];
 }

 def IfOp : Loop_Op<"if",
       [SingleBlockImplicitTerminator<"YieldOp">, RecursiveSideEffects]> {
   let summary = "if-then-else operation";
   let description = [{
     The `loop.if` operation represents an if-then-else construct for
     conditionally executing two regions of code. The operand to an if operation
     is a boolean value. For example:

     ```mlir
     loop.if %b  {
       ...
     } else {
       ...
     }
     ```

     `loop.if` may also return results that are defined in its regions. The
     values defined are determined by which execution path is taken.

     Example:

     ```mlir
     %x, %y = loop.if %b -> (f32, f32) {
       %x_true = ...
       %y_true = ...
       loop.yield %x_true, %y_true : f32, f32
     } else {
       %x_false = ...
       %y_false = ...
       loop.yield %x_false, %y_false : f32, f32
     }
     ```

     `loop.if` regions are always terminated with "loop.yield". If "loop.if"
     defines no values, the "loop.yield" can be left out, and will be inserted
     implicitly. Otherwise, it must be explicit.
     Also, if "loop.if" defines one or more values, the 'else' block cannot be
     omitted.

     Example:

     ```mlir
     loop.if %b  {
       ...
     }
     ```
   }];
   let arguments = (ins I1:$condition);
   let results = (outs Variadic<AnyType>:$results);
   let regions = (region SizedRegion<1>:$thenRegion, AnyRegion:$elseRegion);

   let skipDefaultBuilders = 1;
   let builders = [
     OpBuilder<"Builder *builder, OperationState &result, "
               "Value cond, bool withElseRegion">,
     OpBuilder<"Builder *builder, OperationState &result, "
               "TypeRange resultTypes, Value cond, bool withElseRegion">
   ];

   let extraClassDeclaration = [{
     OpBuilder getThenBodyBuilder() {
       assert(!thenRegion().empty() && "Unexpected empty 'then' region.");
       Block &body = thenRegion().front();
       return OpBuilder(&body,
                        results().empty() ? std::prev(body.end()) : body.end());
     }
     OpBuilder getElseBodyBuilder() {
       assert(!elseRegion().empty() && "Unexpected empty 'else' region.");
       Block &body = elseRegion().front();
       return OpBuilder(&body,
                        results().empty() ? std::prev(body.end()) : body.end());
     }
   }];
 }

 def ParallelOp : Loop_Op<"parallel",
     [AttrSizedOperandSegments,
      DeclareOpInterfaceMethods<LoopLikeOpInterface>,
      SingleBlockImplicitTerminator<"YieldOp">]> {
   let summary = "parallel for operation";
   let description = [{
     The "loop.parallel" operation represents a loop nest taking 4 groups of SSA
     values as operands that represent the lower bounds, upper bounds, steps and
     initial values, respectively. The operation defines a variadic number of
     SSA values for its induction variables. It has one region capturing the
     loop body. The induction variables are represented as an argument of this
     region. These SSA values always have type index, which is the size of the
     machine word. The steps are values of type index, required to be positive.
     The lower and upper bounds specify a half-open range: the range includes
     the lower bound but does not include the upper bound. The initial values
     have the same types as results of "loop.parallel". If there are no results,
     the keyword `init` can be omitted.

     Semantically we require that the iteration space can be iterated in any
     order, and the loop body can be executed in parallel. If there are data
     races, the behavior is undefined.

     The parallel loop operation supports reduction of values produced by
     individual iterations into a single result. This is modeled using the
     loop.reduce operation (see loop.reduce for details). Each result of a
     loop.parallel operation is associated with an initial value operand and
     reduce operation that is an immediate child. Reductions are matched to
     result and initial values in order of their appearance in the body.
     Consequently, we require that the body region has the same number of
     results and initial values as it has reduce operations.

     The body region must contain exactly one block that terminates with
     "loop.yield" without operands. Parsing ParallelOp will create such a region
     and insert the terminator when it is absent from the custom format.

     Example:

     ```mlir
     loop.parallel (%iv) = (%lb) to (%ub) step (%step) -> f32 {
       %zero = constant 0.0 : f32
       loop.reduce(%zero) : f32 {
         ^bb0(%lhs : f32, %rhs: f32):
           %res = addf %lhs, %rhs : f32
           loop.reduce.return %res : f32
       }
     }
     ```
   }];

   let arguments = (ins Variadic<Index>:$lowerBound,
                        Variadic<Index>:$upperBound,
                        Variadic<Index>:$step,
                        Variadic<AnyType>:$initVals);
   let results = (outs Variadic<AnyType>:$results);
   let regions = (region SizedRegion<1>:$region);

   let skipDefaultBuilders = 1;
   let builders = [
     OpBuilder<"Builder *builder, OperationState &result, "
               "ValueRange lowerBounds, ValueRange upperBounds, "
               "ValueRange steps, ValueRange initVals = {}">,
   ];

   let extraClassDeclaration = [{
     Block *getBody() { return &region().front(); }
     unsigned getNumInductionVars() {
       return getBody()->getNumArguments();
     }
     Block::BlockArgListType getInductionVars() {
       return getBody()->getArguments();
     }
     unsigned getNumLoops() { return step().size(); }
     unsigned getNumReductions() { return initVals().size(); }
   }];
 }

 def ReduceOp : Loop_Op<"reduce", [HasParent<"ParallelOp">]> {
   let summary = "reduce operation for parallel for";
   let description = [{
     "loop.reduce" is an operation occurring inside "loop.parallel" operations.
     It consists of one block with two arguments which have the same type as the
     operand of "loop.reduce".

     "loop.reduce" is used to model the value for reduction computations of a
     "loop.parallel" operation. It has to appear as an immediate child of a
     "loop.parallel" and is associated with a result value of its parent
     operation.

     Association is in the order of appearance in the body where the first
     result of a parallel loop operation corresponds to the first "loop.reduce"
     in the operation's body region. The reduce operation takes a single
     operand, which is the value to be used in the reduction.

     The reduce operation contains a region whose entry block expects two
     arguments of the same type as the operand. As the iteration order of the
     parallel loop and hence reduction order is unspecified, the result of
     reduction may be non-deterministic unless the operation is associative and
     commutative.

     The result of the reduce operation's body must have the same type as the
     operands and associated result value of the parallel loop operation.
     Example:

     ```mlir
     %operand = constant 1.0 : f32
     loop.reduce(%operand) : f32 {
       ^bb0(%lhs : f32, %rhs: f32):
         %res = addf %lhs, %rhs : f32
         loop.reduce.return %res : f32
     }
     ```
   }];

   let skipDefaultBuilders = 1;
   let builders = [
     OpBuilder<"Builder *builder, OperationState &result, "
               "Value operand">
   ];

   let arguments = (ins AnyType:$operand);
   let regions = (region SizedRegion<1>:$reductionOperator);
 }

 def ReduceReturnOp :
     Loop_Op<"reduce.return", [HasParent<"ReduceOp">, NoSideEffect,
                               Terminator]> {
   let summary = "terminator for reduce operation";
   let description = [{
     "loop.reduce.return" is a special terminator operation for the block inside
     "loop.reduce". It terminates the region. It should have the same type as
     the operand of "loop.reduce". Example for the custom format:

     ```mlir
     loop.reduce.return %res : f32
     ```
   }];

   let arguments = (ins AnyType:$result);
   let assemblyFormat = "$result attr-dict `:` type($result)";
 }

 def YieldOp : Loop_Op<"yield", [NoSideEffect, Terminator]> {
   let summary = "loop yield and termination operation";
   let description = [{
     "loop.yield" yields an SSA value from a loop dialect op region and
     terminates the regions. The semantics of how the values are yielded is
     defined by the parent operation.
     If "loop.yield" has any operands, the operands must match the parent
     operation's results.
     If the parent operation defines no values, then the "loop.yield" may be
     left out in the custom syntax and the builders will insert one implicitly.
     Otherwise, it has to be present in the syntax to indicate which values are
     yielded.
   }];

   let arguments = (ins Variadic<AnyType>:$results);
   let builders = [
     OpBuilder<"Builder *builder, OperationState &result",
               [{ /* nothing to do */ }]>
   ];
 }
 #endif // LOOP_OPS
	//===- Ops.td - Loop operation definitions ---------------- tablegen --===//
	//
	// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
	// See https://llvm.org/LICENSE.txt for license information.
	// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
	//
	//===----------------------------------------------------------------------===//
	//
	// Defines MLIR loop operations.
	//
	//===----------------------------------------------------------------------===//

	#ifndef LOOP_OPS
	#define LOOP_OPS

	include "mlir/Interfaces/LoopLikeInterface.td"
	include "mlir/Interfaces/SideEffects.td"

	def LoopOps_Dialect : Dialect {
	let name = "loop";
	let cppNamespace = "";
	}

	// Base class for Loop dialect ops.
	class Loop_Op<string mnemonic, list<OpTrait> traits = []> :
	Op<LoopOps_Dialect, mnemonic, traits> {
	// For every standard op, there needs to be a:
	// * void print(OpAsmPrinter &p, ${C++ class of Op} op)
	// * LogicalResult verify(${C++ class of Op} op)
	// * ParseResult parse${C++ class of Op}(OpAsmParser &parser,
	// OperationState &result)
	// functions.
	let printer = [{ return ::print(p, *this); }];
	let verifier = [{ return ::verify(*this); }];
	let parser = [{ return ::parse$cppClass(parser, result); }];
	}

	def ForOp : Loop_Op<"for",
	[DeclareOpInterfaceMethods<LoopLikeOpInterface>,
	SingleBlockImplicitTerminator<"YieldOp">,
	RecursiveSideEffects]> {
	let summary = "for operation";
	let description = [{
	The "loop.for" operation represents a loop taking 3 SSA value as operands
	that represent the lower bound, upper bound and step respectively. The
	operation defines an SSA value for its induction variable. It has one
	region capturing the loop body. The induction variable is represented as an
	argument of this region. This SSA value always has type index, which is the
	size of the machine word. The step is a value of type index, required to be
	positive.
	The lower and upper bounds specify a half-open range: the range includes
	the lower bound but does not include the upper bound.

	The body region must contain exactly one block that terminates with
	"loop.yield". Calling ForOp::build will create such a region and insert
	the terminator implicitly if none is defined, so will the parsing even in
	cases when it is absent from the custom format. For example:

	```mlir
	loop.for %iv = %lb to %ub step %step {
	... // body
	}
	```

	`loop.for` can also operate on loop-carried variables and returns the final
	values after loop termination. The initial values of the variables are
	passed as additional SSA operands to the "loop.for" following the 3 loop
	control SSA values mentioned above (lower bound, upper bound and step). The
	operation region has equivalent arguments for each variable representing
	the value of the variable at the current iteration.

	The region must terminate with a "loop.yield" that passes all the current
	iteration variables to the next iteration, or to the "loop.for" result, if
	at the last iteration. "loop.for" results hold the final values after the
	last iteration.

	For example, to sum-reduce a memref:

	```mlir
	func @reduce(%buffer: memref<1024xf32>, %lb: index,
	%ub: index, %step: index) -> (f32) {
	// Initial sum set to 0.
	%sum_0 = constant 0.0 : f32
	// iter_args binds initial values to the loop's region arguments.
	%sum = loop.for %iv = %lb to %ub step %step
	iter_args(%sum_iter = %sum_0) -> (f32) {
	%t = load %buffer[%iv] : memref<1024xf32>
	%sum_next = addf %sum_iter, %t : f32
	// Yield current iteration sum to next iteration %sum_iter or to %sum
	// if final iteration.
	loop.yield %sum_next : f32
	}
	return %sum : f32
	}
	```

	If the "loop.for" defines any values, a yield must be explicitly present.
	The number and types of the "loop.for" results must match the initial
	values in the "iter_args" binding and the yield operands.

	Another example with a nested "loop.if" (see "loop.if" for details) to
	perform conditional reduction:

	```mlir
	func @conditional_reduce(%buffer: memref<1024xf32>, %lb: index,
	%ub: index, %step: index) -> (f32) {
	%sum_0 = constant 0.0 : f32
	%c0 = constant 0.0 : f32
	%sum = loop.for %iv = %lb to %ub step %step
	iter_args(%sum_iter = %sum_0) -> (f32) {
	%t = load %buffer[%iv] : memref<1024xf32>
	%cond = cmpf "ugt", %t, %c0 : f32
	%sum_next = loop.if %cond -> (f32) {
	%new_sum = addf %sum_iter, %t : f32
	loop.yield %new_sum : f32
	} else {
	loop.yield %sum_iter : f32
	}
	loop.yield %sum_next : f32
	}
	return %sum : f32
	}
	```
	}];
	let arguments = (ins Index:$lowerBound,
	Index:$upperBound,
	Index:$step,
	Variadic<AnyType>:$initArgs);
	let results = (outs Variadic<AnyType>:$results);
	let regions = (region SizedRegion<1>:$region);

	let skipDefaultBuilders = 1;
	let builders = [
	OpBuilder<"Builder *builder, OperationState &result, "
	"Value lowerBound, Value upperBound, Value step, "
	"ValueRange iterArgs = llvm::None">
	];

	let extraClassDeclaration = [{
	Block *getBody() { return &region().front(); }
	Value getInductionVar() { return getBody()->getArgument(0); }
	OpBuilder getBodyBuilder() {
	return OpBuilder(getBody(), std::prev(getBody()->end()));
	}
	Block::BlockArgListType getRegionIterArgs() {
	return getBody()->getArguments().drop_front();
	}
	Operation::operand_range getIterOperands() {
	return getOperands().drop_front(getNumControlOperands());
	}

	void setLowerBound(Value bound) { getOperation()->setOperand(0, bound); }
	void setUpperBound(Value bound) { getOperation()->setOperand(1, bound); }
	void setStep(Value step) { getOperation()->setOperand(2, step); }

	/// Number of region arguments for loop-carried values
	unsigned getNumRegionIterArgs() {
	return getBody()->getNumArguments() - 1;
	}
	/// Number of operands controlling the loop: lb, ub, step
	unsigned getNumControlOperands() { return 3; }
	/// Does the operation hold operands for loop-carried values
	bool hasIterOperands() {
	return getOperation()->getNumOperands() > getNumControlOperands();
	}
	/// Get Number of loop-carried values
	unsigned getNumIterOperands() {
	return getOperation()->getNumOperands() - getNumControlOperands();
	}
	}];
	}

	def IfOp : Loop_Op<"if",
	[SingleBlockImplicitTerminator<"YieldOp">, RecursiveSideEffects]> {
	let summary = "if-then-else operation";
	let description = [{
	The `loop.if` operation represents an if-then-else construct for
	conditionally executing two regions of code. The operand to an if operation
	is a boolean value. For example:

	```mlir
	loop.if %b {
	...
	} else {
	...
	}
	```

	`loop.if` may also return results that are defined in its regions. The
	values defined are determined by which execution path is taken.

	Example:

	```mlir
	%x, %y = loop.if %b -> (f32, f32) {
	%x_true = ...
	%y_true = ...
	loop.yield %x_true, %y_true : f32, f32
	} else {
	%x_false = ...
	%y_false = ...
	loop.yield %x_false, %y_false : f32, f32
	}
	```

	`loop.if` regions are always terminated with "loop.yield". If "loop.if"
	defines no values, the "loop.yield" can be left out, and will be inserted
	implicitly. Otherwise, it must be explicit.
	Also, if "loop.if" defines one or more values, the 'else' block cannot be
	omitted.

	Example:

	```mlir
	loop.if %b {
	...
	}
	```
	}];
	let arguments = (ins I1:$condition);
	let results = (outs Variadic<AnyType>:$results);
	let regions = (region SizedRegion<1>:$thenRegion, AnyRegion:$elseRegion);

	let skipDefaultBuilders = 1;
	let builders = [
	OpBuilder<"Builder *builder, OperationState &result, "
	"Value cond, bool withElseRegion">,
	OpBuilder<"Builder *builder, OperationState &result, "
	"TypeRange resultTypes, Value cond, bool withElseRegion">
	];

	let extraClassDeclaration = [{
	OpBuilder getThenBodyBuilder() {
	assert(!thenRegion().empty() && "Unexpected empty 'then' region.");
	Block &body = thenRegion().front();
	return OpBuilder(&body,
	results().empty() ? std::prev(body.end()) : body.end());
	}
	OpBuilder getElseBodyBuilder() {
	assert(!elseRegion().empty() && "Unexpected empty 'else' region.");
	Block &body = elseRegion().front();
	return OpBuilder(&body,
	results().empty() ? std::prev(body.end()) : body.end());
	}
	}];
	}

	def ParallelOp : Loop_Op<"parallel",
	[AttrSizedOperandSegments,
	DeclareOpInterfaceMethods<LoopLikeOpInterface>,
	SingleBlockImplicitTerminator<"YieldOp">]> {
	let summary = "parallel for operation";
	let description = [{
	The "loop.parallel" operation represents a loop nest taking 4 groups of SSA
	values as operands that represent the lower bounds, upper bounds, steps and
	initial values, respectively. The operation defines a variadic number of
	SSA values for its induction variables. It has one region capturing the
	loop body. The induction variables are represented as an argument of this
	region. These SSA values always have type index, which is the size of the
	machine word. The steps are values of type index, required to be positive.
	The lower and upper bounds specify a half-open range: the range includes
	the lower bound but does not include the upper bound. The initial values
	have the same types as results of "loop.parallel". If there are no results,
	the keyword `init` can be omitted.

	Semantically we require that the iteration space can be iterated in any
	order, and the loop body can be executed in parallel. If there are data
	races, the behavior is undefined.

	The parallel loop operation supports reduction of values produced by
	individual iterations into a single result. This is modeled using the
	loop.reduce operation (see loop.reduce for details). Each result of a
	loop.parallel operation is associated with an initial value operand and
	reduce operation that is an immediate child. Reductions are matched to
	result and initial values in order of their appearance in the body.
	Consequently, we require that the body region has the same number of
	results and initial values as it has reduce operations.

	The body region must contain exactly one block that terminates with
	"loop.yield" without operands. Parsing ParallelOp will create such a region
	and insert the terminator when it is absent from the custom format.

	Example:

	```mlir
	loop.parallel (%iv) = (%lb) to (%ub) step (%step) -> f32 {
	%zero = constant 0.0 : f32
	loop.reduce(%zero) : f32 {
	^bb0(%lhs : f32, %rhs: f32):
	%res = addf %lhs, %rhs : f32
	loop.reduce.return %res : f32
	}
	}
	```
	}];

	let arguments = (ins Variadic<Index>:$lowerBound,
	Variadic<Index>:$upperBound,
	Variadic<Index>:$step,
	Variadic<AnyType>:$initVals);
	let results = (outs Variadic<AnyType>:$results);
	let regions = (region SizedRegion<1>:$region);

	let skipDefaultBuilders = 1;
	let builders = [
	OpBuilder<"Builder *builder, OperationState &result, "
	"ValueRange lowerBounds, ValueRange upperBounds, "
	"ValueRange steps, ValueRange initVals = {}">,
	];

	let extraClassDeclaration = [{
	Block *getBody() { return &region().front(); }
	unsigned getNumInductionVars() {
	return getBody()->getNumArguments();
	}
	Block::BlockArgListType getInductionVars() {
	return getBody()->getArguments();
	}
	unsigned getNumLoops() { return step().size(); }
	unsigned getNumReductions() { return initVals().size(); }
	}];
	}

	def ReduceOp : Loop_Op<"reduce", [HasParent<"ParallelOp">]> {
	let summary = "reduce operation for parallel for";
	let description = [{
	"loop.reduce" is an operation occurring inside "loop.parallel" operations.
	It consists of one block with two arguments which have the same type as the
	operand of "loop.reduce".

	"loop.reduce" is used to model the value for reduction computations of a
	"loop.parallel" operation. It has to appear as an immediate child of a
	"loop.parallel" and is associated with a result value of its parent
	operation.

	Association is in the order of appearance in the body where the first
	result of a parallel loop operation corresponds to the first "loop.reduce"
	in the operation's body region. The reduce operation takes a single
	operand, which is the value to be used in the reduction.

	The reduce operation contains a region whose entry block expects two
	arguments of the same type as the operand. As the iteration order of the
	parallel loop and hence reduction order is unspecified, the result of
	reduction may be non-deterministic unless the operation is associative and
	commutative.

	The result of the reduce operation's body must have the same type as the
	operands and associated result value of the parallel loop operation.
	Example:

	```mlir
	%operand = constant 1.0 : f32
	loop.reduce(%operand) : f32 {
	^bb0(%lhs : f32, %rhs: f32):
	%res = addf %lhs, %rhs : f32
	loop.reduce.return %res : f32
	}
	```
	}];

	let skipDefaultBuilders = 1;
	let builders = [
	OpBuilder<"Builder *builder, OperationState &result, "
	"Value operand">
	];

	let arguments = (ins AnyType:$operand);
	let regions = (region SizedRegion<1>:$reductionOperator);
	}

	def ReduceReturnOp :
	Loop_Op<"reduce.return", [HasParent<"ReduceOp">, NoSideEffect,
	Terminator]> {
	let summary = "terminator for reduce operation";
	let description = [{
	"loop.reduce.return" is a special terminator operation for the block inside
	"loop.reduce". It terminates the region. It should have the same type as
	the operand of "loop.reduce". Example for the custom format:

	```mlir
	loop.reduce.return %res : f32
	```
	}];

	let arguments = (ins AnyType:$result);
	let assemblyFormat = "$result attr-dict `:` type($result)";
	}

	def YieldOp : Loop_Op<"yield", [NoSideEffect, Terminator]> {
	let summary = "loop yield and termination operation";
	let description = [{
	"loop.yield" yields an SSA value from a loop dialect op region and
	terminates the regions. The semantics of how the values are yielded is
	defined by the parent operation.
	If "loop.yield" has any operands, the operands must match the parent
	operation's results.
	If the parent operation defines no values, then the "loop.yield" may be
	left out in the custom syntax and the builders will insert one implicitly.
	Otherwise, it has to be present in the syntax to indicate which values are
	yielded.
	}];

	let arguments = (ins Variadic<AnyType>:$results);
	let builders = [
	OpBuilder<"Builder *builder, OperationState &result",
	[{ /* nothing to do */ }]>
	];
	}
	#endif // LOOP_OPS