(self, shape, name=None)
Takes input in uint8 format which is cast to float32 and divided by 255
        before passing it to the model.

        On GPU this ensures lower data transfer times.

        Parameters
        ----------
        shape: [int]
            shape of the tensor.
        name: str
            name of the underlying placeholder
Takes input in uint8 format which is cast to float32 and divided by 255
        before passing it to the model.
Takes input in uint8 format which is cast to float32 and divided by 255 before passing it to the model .
def __init__(self, shape, name=None):
        """Takes input in uint8 format which is cast to float32 and divided by 255
        before passing it to the model.

        On GPU this ensures lower data transfer times.

        Parameters
        ----------
        shape: [int]
            shape of the tensor.
        name: str
            name of the underlying placeholder
        """

        super().__init__(tf.placeholder(tf.uint8, [None] + list(shape), name=name))
        self._shape = shape
        self._output = tf.cast(super().get(), tf.float32) / 255.0
def __init__ ( self , shape , name = None ) : super ( ) . __init__ ( tf . placeholder ( tf . uint8 , [ None ] + list ( shape ) , name = name ) ) self . _shape = shape self . _output = tf . cast ( super ( ) . get ( ) , tf . float32 ) / 255.0