labels map[string]*syntax.LabeledStmt // allocated lazily
}

// insert records a new label declaration for the current block.
// The label must not have been declared before in any block.
func (b *block) insert(s *syntax.LabeledStmt) {
	name := s.Label.Value
	if debug {
		assert(b.gotoTarget(name) == nil)
	}
	labels := b.labels
	if labels == nil {

                // matrix of a fully connected layer on a trivial FC mnist
                // model:
                // - `model.layer-1.kernel` (this is the "best" name)
                // - `model.keras_api.layers.1.kernel`
                // - `model.variables.0`
                // - `model.keras_api.layers.1.keras_api.trainable_variables.0`

This pass implements automated pipelining for TPU embeddings defined using
the TF2 Embedding API. This is designed for applications that have an
embedding lookup on the SparseCore, followed by one or more dense layers on
TensorCores, optionally followed by a backward pass (training update) with
more ops on the SparseCore. Ops are broken up into:
  1. SC forward pass
  2. TC forward/backward pass
  3. SC backward pass

			markDelete = false
		}
		if opts.VersionPurgeStatus() == Complete {
			markDelete = false
		}
		// now, since VersionPurgeStatus() is already set, we can let the
		// lower layers decide this. This fixes a regression that was introduced
		// in PR #14555 where !VersionPurgeStatus.Empty() is automatically
		// considered as Delete marker true to avoid listing such objects by

dataView.object=this.layer_.args;return dataView;},get title(){return this.layer_.objectInstance.typeName;},findEquivalent(lthi){const layer=lthi.activeTree.findLayerWithId(this.layer_.layerId)||lthi.pendingTree.findLayerWithId(this.layer_.layerId);if(!layer)return undefined;return new LayerSelection(layer);}};function TileSelection(tile,opt_data){this.tile_=tile;this.data_=opt_data||{};}...

$containers $container.Name }}{{end}}{{- end}} metadata: labels: service.istio.io/canonical-name: {{ index .ObjectMeta.Labels `service.istio.io/canonical-name` | default (index .ObjectMeta.Labels `app.kubernetes.io/name`) | default (index .ObjectMeta.Labels `app`) | default .DeploymentMeta.Name | quote }} service.istio.io/canonical-revision: {{ index .ObjectMeta.Labels `service.istio.io/canonical-revision` | default (index .ObjectMeta.Labels `app.kubernetes.io/version`) | default (index .ObjectMeta.Labels...

          medium: Memory
        name: istio-envoy
      - emptyDir: {}
        name: istio-data
      - downwardAPI:
          items:
          - fieldRef:
              fieldPath: metadata.labels
            path: labels
          - fieldRef:
              fieldPath: metadata.annotations
            path: annotations
        name: istio-podinfo
      - name: istio-token
        projected:
          sources:

zirain <******@****.***> 1718030161 +0800

                        Host header of the request. * HTTPS: The Listener Hostname
                        SHOULD match at both the TLS and HTTP protocol layers as described
                        above. If an implementation does not ensure that both the
                        SNI and Host header match the Listener hostname, it MUST clearly

      // Duplicate composite function and op of quantizable layer for creating
      // unquantized layer.
      StringAttr new_ref_func_name = DuplicateFunction(op, f_attr);
      Operation *new_op = DuplicateOp(op, rewriter, new_ref_func_name);

      // Attach second DumpTensorOp to its output unquantized layer.
      SmallVector<NamedAttribute> dump_attributes = CreateDumpAttributes(