stopCh := make(chan struct{})
	defer close(stopCh)

	informerFactory := informers.NewSharedInformerFactory(kubeClient, 0)

	// disable consumption of cpu unless there is a covering quota.
	// disable consumption of cpu unless there is a covering quota.
	config := &resourcequotaapi.Configuration{
		LimitedResources: []resourcequotaapi.LimitedResource{
			{
				Resource:      "pods",

		"urlquery": `http://www.foo.com/index.html?title=main`,
	}
	for _, test := range [...]struct {
		desc, input, output string
	}{
		// covering issue 20323
		{
			"field with predefined escaper name 1",
			`{{.html | print}}`,
			`<h1>Hi!</h1>`,
		},
		// covering issue 20323
		{
			"field with predefined escaper name 2",
			`{{.urlquery | print}}`,
			`http://www.foo.com/index.html?title=main`,
		},

		slid := len(rval.VarSlots)
		rval.VarSlots = append(rval.VarSlots, []SlotID{SlotID(slid)})
	}

	// Make an initial pass to populate the vars/slots for our return
	// value, covering first the input parameters and then (if needed)
	// the special ".closureptr" var for rangefunc bodies.
	params := []abi.ABIParamAssignment{}
	for _, inp := range pri.InParams() {
		if !isNamedRegParam(inp) {

def TF_StatefulUniformFullIntOp : TF_Op<"StatefulUniformFullInt", []> {
  let summary = "Outputs random integers from a uniform distribution.";

  let description = [{
The generated values are uniform integers covering the whole range of `dtype`.
  }];

  let arguments = (ins
    Arg<TF_ResourceTensor, "", [TF_VariableRead,TF_VariableWrite]>:$resource,
    TF_Int64Tensor:$algorithm,
    TF_I32OrI64Tensor:$shape
  );

(Neg64F ...) => (FNEG ...)

(Com64 ...) => (NOT ...)
(Com(32|16|8) ...) => (NOTW ...)
(NOT x) => (XOR (MOVDconst [-1]) x)
(NOTW x) => (XORWconst [-1] x)

// Lowering boolean ops
(AndB ...) => (ANDW ...)
(OrB ...) => (ORW ...)
(Not x) => (XORWconst [1] x)

// Lowering pointer arithmetic
(OffPtr [off] ptr:(SP)) => (MOVDaddr [int32(off)] ptr)
(OffPtr [off] ptr) && is32Bit(off) => (ADDconst [int32(off)] ptr)

        then:
        fixture.assertStateStored()
        outputContains("processing [a.jar]")
        outputContains("processing [b.jar]")
        outputContains("converting a.jar.green to red")
        outputContains("converting b.jar.green to red")
        outputContains("result = [a.jar.green.red, b.jar.green.red]")

        when:
        configurationCacheRun("resolveTransformed")

        then:

(Neg64F x) => (PXOR x (MOVSDconst <typ.Float64> [math.Copysign(0, -1)]))

// Lowering boolean ops
(AndB ...) => (ANDL ...)
(OrB ...) => (ORL ...)
(Not x) => (XORLconst [1] x)

// Lowering pointer arithmetic
(OffPtr [off] ptr) && is32Bit(off) => (ADDQconst [int32(off)] ptr)
(OffPtr [off] ptr) => (ADDQ (MOVQconst [off]) ptr)

// Lowering other arithmetic
(Ctz64 x)     && buildcfg.GOAMD64 >= 3 => (TZCNTQ x)

distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/

package apiserver

import (
	"fmt"
	"net/http"
	"sort"
	"strings"
	"sync"
	"sync/atomic"
	"time"

    return success();
  }
};

// This pass performs a manual conversion with FakeQuant, converting between
// floating point and quantized space. It is designed to reproduce TF's
// implementation, mirroring the previous XLA implementation.
//
// 1. Computing proper quantized bounds. This involves nudging the input bounds.
// 2. Converting the input bounds to quantized space, rounding values.
// 3. Convert back into floating point space.

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// This transformation pass prepares for legalization to the TFLite dialect by
// converting operations in TensorFlow dialect into operations that can be