description: Path to access on the HTTP server.
                        type: string
                      port:
                        description: Port on which the endpoint lives.
                        maximum: 4294967295
                        minimum: 0
                        type: integer
                      scheme:
                        type: string

                        description: Path to access on the HTTP server.
                        type: string
                      port:
                        description: Port on which the endpoint lives.
                        maximum: 4294967295
                        minimum: 0
                        type: integer
                      scheme:
                        type: string

[..., sizeof(`type`)/sizeof(`T`)] to [...].

tf.bitcast() and tf.cast() work differently when real dtype is casted as a complex dtype
(e.g. tf.complex64 or tf.complex128) as tf.cast() make imaginary part 0 while tf.bitcast()
gives module error.
For example,

Example 1:

>>> a = [1., 2., 3.]
>>> equality_bitcast = tf.bitcast(a, tf.complex128)
Traceback (most recent call last):
...

        [Revisiting ResNets: Improved Training and Scaling Strategies](https://arxiv.org/pdf/2103.07579.pdf)
    *   Added `tf.keras.optimizers.experimental.Optimizer`. The reworked
        optimizer gives more control over different phases of optimizer calls,
        and is easier to customize. We provide Adam, SGD, Adadelta, AdaGrad and
        RMSprop optimizers based on

            "type": "string"
          },
          "reason": {
            "description": "reason is a unique, this should be a short, machine understandable string that gives the reason for condition's last transition. If it reports \"Resizing\" that means the underlying persistent volume is being resized.",
            "type": "string"
          },
          "status": {