// RUN: odml-to-stablehlo-opt %s --tf-stablehlo=skip-partitioned-calls=true | FileCheck %s --check-prefix=CHECK-SKIP
// RUN: odml-to-stablehlo-opt %s --tf-stablehlo=skip-partitioned-calls=false | FileCheck %s --check-prefix=CHECK-NOSKIP

module {
  func.func @partitioned_call(%arg0: tensor<1x2x2x3xf32>) -> (tensor<1x2x2x3xf32>) {
    %0 = "tf.StatefulPartitionedCall"(%arg0) <{
      config = "", config_proto = "", executor_type = "", f = @some_func
    }> {

The new [Cookie.Partitioned] field identifies cookies with the Partitioned attribute....

        "tf.StatefulPartitionedCall"(%arg0) <{config = "", config_proto = "", executor_type = "", f = @partitioned}> : (tensor<*x!tf_type.resource>) -> ()
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    return
  }

  Option<bool> skip_resize_{
      *this, "skip-resize",
      ::llvm::cl::desc("Skip tf.ResizeBilinear and tf.ResizeNearestNeighbor")};

  Option<bool> skip_partitioned_calls_{
      *this, "skip-partitioned-calls",
      ::llvm::cl::desc(
          "Skip tf.StatefulPartitionedCall and tf.PartitionedCall")};
};

void TFToMhloPass::runOnOperation() {
  auto func = getOperation();

	})
}

var (
	requestTotal = compbasemetrics.NewCounterVec(
		&compbasemetrics.CounterOpts{
			Name:           "apiserver_delegated_authz_request_total",
			Help:           "Number of HTTP requests partitioned by status code.",
			StabilityLevel: compbasemetrics.ALPHA,
		},
		[]string{"code"},
	)

	requestLatency = compbasemetrics.NewHistogramVec(
		&compbasemetrics.HistogramOpts{

//   Executor Dialect or TF Functional Dialect. Will convert to TF Functional.
//   is_supported_by_replicated_brige - If the graph targets the replicated
//   bridge. Set it to true for replicated/partitioned graphs. e.g. replicated
//   and single-core TPU graphs. Set this to false if the graph is not
//   replicated, e.g. CPU/GPU graphs. is_in_fallback_enabled_mode - Whether this

limitations under the License.
==============================================================================*/

// This transformation pass converts stateful and stateless partitioned calls
// with _xla_compile_device_type attribute to XLA launch ops.

#include <stack>

#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"

    Arg<TF_StrTensor, [{shape {N}.  The slice specs of the tensors to be restored.
Empty strings indicate that they are non-partitioned tensors.}]>:$shape_and_slices,
    // VarHandles for restored tensors.
    Variadic<TF_Tensor>:$var_handles,
    // Data types for restored tensor.
    TypeArrayAttr: $restored_dtypes,

  // Operation along with its respective operands and result Values(s).
  // The semantic of `Operation::clone` is copying given entity *into* this
  // entity. The new FuncOp body is populated by cloning partitioned ops into
  // it. Cloning Operation(s) will create cloned Value(s) for the results of a
  // cloned op, but it needs a reference to the new operand Value(s) which are

pkg net/http, func ParseCookie(string) ([]*Cookie, error) #66008
pkg net/http, func ParseSetCookie(string) (*Cookie, error) #66008
pkg net/http, method (*Request) CookiesNamed(string) []*Cookie #61472
pkg net/http, type Cookie struct, Partitioned bool #62490
pkg net/http, type Cookie struct, Quoted bool #46443
pkg net/http, type Request struct, Pattern string #66405