} type HandshakeSecret struct { secret []byte hash func() hash.Hash } func (s *EarlySecret) HandshakeSecret(sharedSecret []byte) *HandshakeSecret { derived := deriveSecret(s.hash, s.secret, "derived", nil) return &HandshakeSecret{ secret: extract(s.hash, sharedSecret, derived), hash: s.hash, } } // ClientHandshakeTraff derives the client_handshake_traffic_secret from // the handshake secret and the transcript up to the ServerHello. func (s *HandshakeSecret) ClientHandshakeTraff(transcript hash.Hash)...

*MasterSecret { derived := deriveSecret(s.hash, s.secret, "derived", nil) return &MasterSecret{ secret: extract(s.hash, nil, derived), hash: s.hash, } } // ClientApplicationTra derives the client_application_traffic_secret_0 // from the master secret and the transcript up to the server Finished. func (s *MasterSecret) ClientApplicationTra(transcript fips140.Hash) []byte { return deriveSecret(s.hash, s.secret, clientApplicationTra, transcript) } // ServerApplicationTra derives the server_application_traffic_secret_0...

    of sometimes* get reflected in already-traced `tf.function` traces.
*   Add the `Conv1DTranspose` layer.
*   Refine the semantics of `SensitivitySpecificityBase` derived metrics. See
    the updated API docstrings for
    [`tf.keras.metrics.SensitivityAtSpecificity`](https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/metrics/SensitivityAtSpecificity)
    and