}
	// match: (Zero {t1} [n] p1 store:(Store {t2} (OffPtr [o2] p2) _ mem))
	// cond: isSamePtr(p1, p2) && store.Uses == 1 && n >= o2 + t2.Size() && clobber(store)
	// result: (Zero {t1} [n] p1 mem)
	for {
		n := auxIntToInt64(v.AuxInt)
		t1 := auxToType(v.Aux)
		p1 := v_0
		store := v_1
		if store.Op != OpStore {
			break
		}
		t2 := auxToType(store.Aux)
		mem := store.Args[2]

    Res<TensorOf<[TF_Float16, TF_Float32]>, [{A 1-D float tensor of shape `[M]` representing the corresponding
scores for each selected box, where `M <= max_output_size`.  Scores only differ
from corresponding input scores when using Soft NMS (i.e. when
`soft_nms_sigma>0`)}]>:$selected_scores,
    Res<TF_Int32Tensor, [{A 0-D integer tensor representing the number of valid elements in

		{"(*Int64).Load", Method, 19},
		{"(*Int64).Store", Method, 19},
		{"(*Int64).Swap", Method, 19},
		{"(*Pointer).CompareAndSwap", Method, 19},
		{"(*Pointer).Load", Method, 19},
		{"(*Pointer).Store", Method, 19},
		{"(*Pointer).Swap", Method, 19},
		{"(*Uint32).Add", Method, 19},
		{"(*Uint32).CompareAndSwap", Method, 19},
		{"(*Uint32).Load", Method, 19},
		{"(*Uint32).Store", Method, 19},

          },
          "structuredParameters": {

\n\nSo what happens? Decode first uses json or yaml to unmarshal the serialized data into your external MyAPIObject. That causes the raw JSON to be stored, but not unpacked. The next step is to copy (using pkg/conversion) into the internal struct. The runtime package's DefaultScheme has conversion functions installed which will unpack the JSON stored in RawExtension, turning it into the correct object type, and storing it in the Object. (TODO: In the case where the object is of an unknown type, a...

	v_0 := v.Args[0]
	// match: (Store {t} ptr val mem)
	// cond: t.Size() == 1
	// result: (MOVBstore ptr val mem)
	for {
		t := auxToType(v.Aux)
		ptr := v_0
		val := v_1
		mem := v_2
		if !(t.Size() == 1) {
			break
		}
		v.reset(OpARM64MOVBstore)
		v.AddArg3(ptr, val, mem)
		return true
	}
	// match: (Store {t} ptr val mem)
	// cond: t.Size() == 2

    arg is provided for better performance.
*   Adds a `save_traces` argument to `model.save`/ `tf.keras.models.save_model`
    which determines whether the SavedModel format stores the Keras model/layer
    call functions. The traced functions allow Keras to revive custom models and
    layers without the original class definition, but if this isn't required the

	}
	// match: (Store {t} ptr val mem)
	// cond: t.Size() == 8 && !t.IsFloat()
	// result: (MOVQstore ptr val mem)
	for {
		t := auxToType(v.Aux)
		ptr := v_0
		val := v_1
		mem := v_2
		if !(t.Size() == 8 && !t.IsFloat()) {
			break
		}
		v.reset(OpAMD64MOVQstore)
		v.AddArg3(ptr, val, mem)
		return true
	}
	// match: (Store {t} ptr val mem)

[seccomp-docs]: https://kubernetes.io/docs/tutorials/clusters/seccomp/


### Production images moved to community control

As of Kuberenetes v1.19, Kubernetes container images are stored on a community-controlled storage bucket, 
located at `{asia,eu,us}.gcr.io/k8s-artifacts-prod`. The `k8s.gcr.io` vanity domain has been updated 
to this new bucket. This brings production artifacts under community control.