#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/IR/PatternMatch.h"  // from @llvm-project

namespace mlir {
namespace TF {

// Populates rewrite patterns that decompose composite resource operations into
// primitive ones like ReadVariableOp, AssignVariableOp and other computations
// to facilitate transformations like resource op lifting.

// except the tf ops, inside the function.
void populateCanonicalizationPatterns(func::FuncOp func,
                                      RewritePatternSet &patterns);

// Decompose ops.
std::unique_ptr<OperationPass<func::FuncOp>> CreateDecomposeTFOpsPass(
    std::optional<ModuleOp> tfr_module = std::nullopt);

// Rewrites quantized operands and results with their storage types.

   * a duration in order to call a legacy API which requires a {@code long, TimeUnit} pair.
   */
  @SuppressWarnings({
    // We use this method only for cases in which we need to decompose to primitives.
    "GoodTime-ApiWithNumericTimeUnit",
    "GoodTime-DecomposeToPrimitive",
    // We use this method only from within APIs that require a Duration.
    "Java7ApiChecker",
  })
  @IgnoreJRERequirement

#include "tensorflow/compiler/mlir/tfr/integration/tfr_decompose_ctx.h"
#include "tsl/platform/statusor.h"

namespace tensorflow {
namespace tfr {

// An optimization pass that decompose the composite ops in a module according
// to the decomposition library. Currently the decomposition library is loaded
// each time the pass runs. A special environment variable is set to locate the
// decomposition library.

	}
	return nil, fmt.Errorf("unsupported type %T, a %s", v, rv.Kind())
}

type decimalDecompose interface {
	// Decompose returns the internal decimal state into parts.
	// If the provided buf has sufficient capacity, buf may be returned as the coefficient with
	// the value set and length set as appropriate.
	Decompose(buf []byte) (form byte, negative bool, coefficient []byte, exponent int32)

					v.Aux = f.Config.Types.UInt64
					newInt64 = true
				default:
					v.Fatalf("bad float type with size %d", size)
				}
			}
		}
	}

	if newInt64 && f.Config.RegSize == 4 {
		// On 32bit arch, decompose Uint64 introduced in the switch above.
		decomposeBuiltIn(f)
		applyRewrite(f, rewriteBlockdec64, rewriteValuedec64, removeDeadValues)
	}

                       const std::vector<string> op_names)
    : output_path(output_dir), op_names(op_names) {
  api_dirs = str_util::Split(api_dir_list, ",", str_util::SkipEmpty());

  // Decompose the directory components given the output/source directories.
  //
  // Be flexible; accept any path string with a "tensorflow" directory name.
  // (It's hard to construct a location-agnostic include path string using the

   * a duration in order to call a legacy API which requires a {@code long, TimeUnit} pair.
   */
  @SuppressWarnings({
    // We use this method only for cases in which we need to decompose to primitives.
    "GoodTime-ApiWithNumericTimeUnit",
    "GoodTime-DecomposeToPrimitive",
    // We use this method only from within APIs that require a Duration.
    "Java7ApiChecker",
  })
  @IgnoreJRERequirement

limitations under the License.
*/

package genericclioptions

import (
	"github.com/spf13/cobra"

	"k8s.io/cli-runtime/pkg/printers"
)

// KubeTemplatePrintFlags composes print flags that provide both a JSONPath and a go-template printer.
// This is necessary if dealing with cases that require support both both printers, since both sets of flags
// require overlapping flags.

	ResourceName      string
}

// CompactRules combines rules that contain a single APIGroup/Resource, differ only by verb, and contain no other attributes.
// this is a fast check, and works well with the decomposed "missing rules" list from a Covers check.
func CompactRules(rules []rbacv1.PolicyRule) ([]rbacv1.PolicyRule, error) {
	compacted := make([]rbacv1.PolicyRule, 0, len(rules))