//   means BuildSingletonParallelExecuteOp will be used in one location, and
//   RemoveSingletonParallelExecuteOp can be removed.

// Wrap `cluster_func` in a `ParallelExecute` with only one child. This
// can be used to canonicalize IR, so there is always one `ParallelExecute`.
tf_device::ParallelExecuteOp BuildParallelExecuteOp(
    tf_device::ClusterFuncOp cluster_func, OpBuilder* builder);

// RUN: tf-tfrt-opt %s -tf-identity-propagation -canonicalize | FileCheck %s

// CHECK-LABEL: func @identity
// CHECK-SAME:    (%[[ARG0:.*]]: tensor<i32>)
func.func @identity(%arg0: tensor<i32>) -> tensor<i32> {
  // CHECK-NOT: "tf.Identity"
  %0 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>
  // CHECK: return %[[ARG0]]
  func.return %0 : tensor<i32>
}

// CHECK-LABEL: func @identity_terminator
// CHECK-SAME:    (%[[ARG0:.*]]: tensor<i32>)

		refs: make(map[string]obj.ABISet),
	}
}

// canonicalize returns the canonical name used for a linker symbol in
// s's maps. Symbols in this package may be written either as "".X or
// with the package's import path already in the symbol. This rewrites
// both to use the full path, which matches compiler-generated linker
// symbol names.
func (s *SymABIs) canonicalize(linksym string) string {
	if strings.HasPrefix(linksym, `"".`) {

                didWork = true;
            }
        }

        private void renameIfCaseChanged(File target) {
            if (target.exists()) {
                File canonicalizedTarget = FileUtils.canonicalize(target);
                if (!Objects.equals(target.getName(), canonicalizedTarget.getName())) {
                    canonicalizedTarget.renameTo(target);
                }
            }
        }
    }

// The resulting tag is canonicalized using the canonicalization type c.
func (c CanonType) Parse(s string) (t Tag, err error) {
	defer func() {
		if recover() != nil {
			t = Tag{}
			err = language.ErrSyntax
		}
	}()

	tt, err := language.Parse(s)
	if err != nil {
		return makeTag(tt), err
	}
	tt, changed := canonicalize(c, tt)
	if changed {
		tt.RemakeString()
	}

}

// AllowUnconditionalUpdate is the default update policy for CustomResourceDefinition objects.
func (strategy) AllowUnconditionalUpdate() bool {
	return false
}

// Canonicalize normalizes the object after validation.
func (strategy) Canonicalize(obj runtime.Object) {
}

// ValidateUpdate is the default update validation for an end user updating status.

        new_broadcast_shape);
    return success();
  }
};

#define GEN_PASS_DEF_TENSORFLOWOPTIMIZEPASS
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

// Canonicalize operations in functions.
struct TensorFlowOptimizePass
    : public impl::TensorFlowOptimizePassBase<TensorFlowOptimizePass> {
  LogicalResult initialize(MLIRContext *context) override {

		warnings = append(warnings, fmt.Sprintf("annotation %q is deprecated, please use 'spec.ingressClassName' instead", annotationIngressClass))
	}
	return warnings
}

// Canonicalize normalizes the object after validation.
func (ingressStrategy) Canonicalize(obj runtime.Object) {
}

// AllowCreateOnUpdate is false for Ingress; this means POST is needed to create one.
func (ingressStrategy) AllowCreateOnUpdate() bool {
	return false

func (flowSchemaStrategy) WarningsOnCreate(ctx context.Context, obj runtime.Object) []string {
	return nil
}

// Canonicalize normalizes the object after validation.
func (flowSchemaStrategy) Canonicalize(obj runtime.Object) {
}

func (flowSchemaStrategy) AllowUnconditionalUpdate() bool {
	return true
}

// Test to verify translation & export work as intended with runtime.

// RUN: tf-opt --mlir-print-debuginfo --canonicalize --tfl-while-loop-outline %s | mlir-tflite-runner --dump-interpreter-state 2>&1 | FileCheck %s

// Verify value computed:
// ----------------------
// CHECK: result: Tensor<type: FLOAT32, shape: 1, values: 96>
// CHECK: pconst: Tensor<type: INT32, shape: , values: 1>

// Verify tensors in interpreter state: