models/dense_net.py
def dropout(self, _input):
        """
        If the given keep_prob is not 1 AND if the graph is being trained,
        performs a random dropout operation on a given input (_input).
        The dropout probability is the keep_prob parameter.

        Args:
            _input: tensor, the operation's input.
        """
        if self.keep_prob < 1:
            output = tf.cond(
                self.is_training,
                lambda: tf.nn.dropout(_input, self.keep_prob),
                lambda: _input
            )
        else:
            output = _input
        return output

        If the given keep_prob is not 1 AND if the graph is being trained,
        performs a random dropout operation on a given input (_input).
        The dropout probability is the keep_prob parameter.

        Args:
            _input: tensor, the operation's input.
        
If the given keep_prob is not 1 AND if the graph is being trained,
performs a random dropout operation on a given input (_input).
The dropout probability is the keep_prob parameter.
If the given keep_prob is not 1 AND if the graph is being trained performs a random dropout operation on a given input ( _input ) . The dropout probability is the keep_prob parameter .
def dropout(self, _input):
        if self.keep_prob < 1:
            output = tf.cond(
                self.is_training,
                lambda: tf.nn.dropout(_input, self.keep_prob),
                lambda: _input
            )
        else:
            output = _input
        return output
def dropout ( self , _input ) : if self . keep_prob < 1 : output = tf . cond ( self . is_training , lambda : tf . nn . dropout ( _input , self . keep_prob ) , lambda : _input ) else : output = _input return output
If the given keep_prob is not 1 AND if the graph is being trained,
performs a random dropout operation on a given input (_input).
If the given keep_prob is not 1 AND if the graph is being trained performs a random dropout operation on a given input ( _input ) .
"""
        If the given keep_prob is not 1 AND if the graph is being trained,
        performs a random dropout operation on a given input (_input).
        The dropout probability is the keep_prob parameter.

        Args:
            _input: tensor, the operation's input.
        """
self
_input
tensor, the operation's input.
tensor the operation ' s input .