as `tf.tpu.experimental.embedding.serving_embedding_lookup` which can
        take arbitrary rank of dense and sparse tensor. For ragged tensor,
        though the input tensor remains to be rank 2, the activations now can be
        rank 2 or above by specifying the output shape in the feature config or
        via the build method.

*   Add

fixed. g.startReady = true g.start = counter } counter -= g.start // Ensure the counter is strictly increasing. if counter == math.MaxUint64 { panic("crypto/cipher: counter exhausted") } if counter < g.next { panic("crypto/cipher: counter decreased or remained the same") } g.next = counter + 1 } fips140.RecordApproved() return g.g.sealAfterIndicator(dst, nonce, plaintext, data) } func (g *GCMWithCounterNonce) Open(dst, nonce, ciphertext, data []byte) ([]byte, error) { fips140.RecordApproved() return g.g.Open(dst,...