tensorflow_tutorials/mnist/mnist.py
def train_step(self):
        """
        The training step which minimizes the entropy
        using the gradient decent algorithm.
        """
        if self._train_step is not None:
            return self._train_step

        self._train_step = (
            (tf.train
             .GradientDescentOptimizer(self._config['learning_rate'])
             .minimize(self.entropy))
        )

        return self._train_step

        The training step which minimizes the entropy
        using the gradient decent algorithm.
        
The training step which minimizes the entropy
using the gradient decent algorithm.
The training step which minimizes the entropy using the gradient decent algorithm .
def train_step(self):
        if self._train_step is not None:
            return self._train_step
        self._train_step = (
            (tf.train
             .GradientDescentOptimizer(self._config['learning_rate'])
             .minimize(self.entropy))
        )
        return self._train_step
def train_step ( self ) : if self . _train_step is not None : return self . _train_step self . _train_step = ( ( tf . train . GradientDescentOptimizer ( self . _config [ 'learning_rate' ] ) . minimize ( self . entropy ) ) ) return self . _train_step
The training step which minimizes the entropy
using the gradient decent algorithm.
The training step which minimizes the entropy using the gradient decent algorithm .
"""
        The training step which minimizes the entropy
        using the gradient decent algorithm.
        """
self