*   Added Adafactor optimizer `tf.keras.optimizers.Adafactor`.
    *   Added `warmstart_embedding_matrix` to `tf.keras.utils`.
        This utility can be used to warmstart an embeddings matrix so you
        reuse previously-learned word embeddings when working with a new set
        of words which may include previously unseen words (the embedding
        vectors for unseen words will be randomly initialized).

*   `tf.Variable`:

mean to be reused in gradient computation. When is_training is
False, a 1D Tensor for the population mean to be reused in both
1st and 2nd order gradient computation.}]>:$reserve_space_1,
    Arg<TF_Float32Tensor, [{When is_training is True, a 1D Tensor for the computed batch
variance (inverted variance in the cuDNN case) to be reused in
gradient computation. When is_training is False, a 1D Tensor

		{"DNSStartInfo", Type, 7},
		{"DNSStartInfo.Host", Field, 7},
		{"GotConnInfo", Type, 7},
		{"GotConnInfo.Conn", Field, 7},
		{"GotConnInfo.IdleTime", Field, 7},
		{"GotConnInfo.Reused", Field, 7},
		{"GotConnInfo.WasIdle", Field, 7},
		{"WithClientTrace", Func, 7},
		{"WroteRequestInfo", Type, 7},
		{"WroteRequestInfo.Err", Field, 7},
	},
	"net/http/httputil": {

	updatedEndpoint := newNodeNameEndpoint("kubernetes-changed-nodename")
	// Check that NodeName can be changed during update, this is to accommodate the case where nodeIP or PodCIDR is reused.
	// The same ip will now have a different nodeName.
	errList := ValidateEndpoints(updatedEndpoint)
	errList = append(errList, ValidateEndpointsUpdate(updatedEndpoint, oldEndpoint)...)
	if len(errList) != 0 {