}
				condStmt = p.simpleStmt(nil, 0 /* range not permitted */)
			}
			p.want(_Semi)
			if p.tok != _Lbrace {
				post = p.simpleStmt(nil, 0 /* range not permitted */)
				if a, _ := post.(*AssignStmt); a != nil && a.Op == Def {
					p.syntaxErrorAt(a.Pos(), "cannot declare in post statement of for loop")
				}
			}
		} else if p.tok != _Lbrace {
			condStmt = p.simpleStmt(nil, keyword)
		}
	} else {

	}
}

// Handle children
func (po *poset) setchl(i uint32, l posetEdge) { po.nodes[i].l = l }
func (po *poset) setchr(i uint32, r posetEdge) { po.nodes[i].r = r }
func (po *poset) chl(i uint32) uint32          { return po.nodes[i].l.Target() }
func (po *poset) chr(i uint32) uint32          { return po.nodes[i].r.Target() }
func (po *poset) children(i uint32) (posetEdge, posetEdge) {
	return po.nodes[i].l, po.nodes[i].r

apiVersion: batch/v1
kind: Job
metadata:
  name: {{ template "minio.fullname" . }}-post-job
  labels:
    app: {{ template "minio.name" . }}-post-job
    chart: {{ template "minio.chart" . }}
    release: {{ .Release.Name }}
    heritage: {{ .Release.Service }}
  annotations:
    "helm.sh/hook": post-install,post-upgrade
    "helm.sh/hook-delete-policy": hook-succeeded,before-hook-creation

	for i := range parts {
		if errs[i] == nil {
			if parts[i].Name == objectName+"/upload.txt" {
				t.Errorf("Test %s: Failed to stop post policy handler from writing to minioMetaBucket", instanceType)
			}
		}
	}
}

// Wrapper for calling TestPostPolicyBucketHandler tests for both Erasure multiple disks and single node setup.

apiVersion: release-notes/v2
kind: feature
area: istioctl
issue:
  - 29153

releaseNotes:
  - |

// RUN: tf-opt %s -tfl-post-quantize | FileCheck %s
// RUN: tf-opt %s -tfl-post-quantize-remove-qdq | FileCheck --check-prefix=QDQ %s

// CHECK-LABEL: RemoveUnused
// QDQ-LABEL: RemoveUnused
func.func @RemoveUnused(%arg0: tensor<4xf32>, %arg1: tensor<i32>) -> (tensor<2xf32>,tensor<2xf32>) {
  %0 = "tfl.quantize"(%arg0) {qtype = tensor<4x!quant.uniform<u8:f32, 1.0>>} : (tensor<4xf32>) -> tensor<4x!quant.uniform<u8:f32, 1.0>>

// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range -tfl-quantize="enable-dynamic-range-quantization=true" -tfl-post-quantize  | FileCheck %s
// RUN: tf-opt %s -tfl-prepare-quantize-dynamic-range="enable-custom-op-quantization=CustomTestOp=1" -tfl-quantize="enable-dynamic-range-quantization=true enable-custom-op-weight-only=CustomTestOp=false" -tfl-post-quantize="enable-no-side-effect=CustomTestOp=false" | FileCheck --check-prefix=NotPrune %s

// RUN: tf-opt -tf-to-hlo-pipeline %s | FileCheck %s

// Verifies that constants generated post shape inference are propagated.
// get_shape result in this test.
module attributes {tf.versions = {producer = 179 : i32}} {

  // CHECK-LABEL: func @main
  func.func @main(%arg0: tensor<10x19xf32>, %arg1: tensor<19x10xf32> {mhlo.is_same_data_across_replicas = true}) -> tensor<?xi64> {
    %0 = "tf.Shape"(%arg0) : (tensor<10x19xf32>) -> tensor<2xi64>

// RUN: tf-opt %s -tfl-prepare-quantize="quantize-signed=true post-training-quantize=true" -cse | FileCheck %s
// RUN: tf-opt %s -tfl-prepare-quantize="quantize-signed=true post-training-quantize=true legacy-float-scale=true" -cse| FileCheck --check-prefix=Legacy %s

// CHECK-LABEL: QuantizeLstmCellInput
func.func @QuantizeLstmCellInput(%arg0: tensor<1x28x28xf32>) -> tensor<1x28x20xf32> {
    %cst_2 = "tfl.no_value"() {value = unit} : () -> none

// RUN: tf-opt %s -tfl-prepare-quantize="quantize-signed=true post-training-quantize=true activation-number-of-bits=16" -cse | FileCheck %s

// CHECK-LABEL: QuantizeUnidirectionalLstmFullPerTensor
func.func @QuantizeUnidirectionalLstmFullPerTensor(%arg0: tensor<1x2x3xf32>) -> (tensor<1x2x3xf32>) {
  %input = "quantfork.stats"(%arg0) {layerStats = dense<[0.0, 1.0]> : tensor<2xf32>} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf32>