// Executor Dialect for graph nodes and edges or be in TF Functional already.
// Individual Op inside a node should be the Tensorflow Functional Dialect. The
// output MLIR is in the TF Functional Dialect. Returns OkStatus if passed,
// otherwise an error.
//
// Inputs:
//   module - The MLIR Module that will be clustered. Expected to be in TF
//   Executor Dialect or TF Functional Dialect. Will convert to TF Functional.

#include "llvm/Support/FormatVariadic.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/Extensions/AllExtensions.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"  // from @llvm-project

#include <string>
#include <utility>

#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/Dialect/Tensor/IR/Tensor.h"  // from @llvm-project
#include "mlir/IR/Dialect.h"  // from @llvm-project
#include "mlir/IR/PatternMatch.h"  // from @llvm-project

#define TENSORFLOW_COMPILER_MLIR_TFR_IR_TFR_OPS_H_

#include "llvm/ADT/StringSet.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "mlir/IR/Dialect.h"  // from @llvm-project
#include "mlir/IR/DialectImplementation.h"  // from @llvm-project

struct TFReductionPatternInterface
    : public mlir::DialectReductionPatternInterface {
 public:
  explicit TFReductionPatternInterface(mlir::Dialect *dialect)
      : DialectReductionPatternInterface(dialect) {}

  void populateReductionPatterns(
      mlir::RewritePatternSet &patterns) const final {
    populateWithGenerated(patterns);
  }
};

}  // namespace

    bool prefer_tf2xla = false);

// Legalizes TF/XLA communication ops (TF dialect) to HLO dialect communication
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCommunicationPass();

// Legalizes TF/XLA collective ops (TF dialect) to HLO dialect collective
// ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateLegalizeTFCollectivePass();

            "QuantOps.cc.inc",
        ),
        (
            [
                "-gen-dialect-decls",
                "-dialect=quantfork",
            ],
            "QuantOpsDialect.h.inc",
        ),
        (
            [
                "-gen-dialect-defs",
                "-dialect=quantfork",
            ],
            "QuantOpsDialect.cc.inc",
        ),
    ],

            "QuantOps.cc.inc",
        ),
        (
            [
                "-gen-dialect-decls",
                "-dialect=quantization",
            ],
            "QuantOpsDialect.h.inc",
        ),
        (
            [
                "-gen-dialect-defs",
                "-dialect=quantization",
            ],
            "QuantOpsDialect.cc.inc",
        ),
    ],

// tf_executor dialect.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ConvertGraphdefToMlir(
    const GraphDef& graphdef, const GraphDebugInfo& debug_info,
    const GraphImportConfig& specs, mlir::MLIRContext* context);

// Given a Graph, returns a MLIR module containing the graph, expressed with
// tf_executor dialect.
absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ConvertGraphToMlir(

//===----------------------------------------------------------------------===//
// Runtime Fallback Dialect definitions
//===----------------------------------------------------------------------===//

def RuntimeFallback_Dialect : Dialect {
  let name = "tfd";

  let description = [{
    The Runtime Fallback dialect.

    This dialect contains operations to run existing TF kernels on TFRT by
    invoking TF Eager API.
  }];