deep_mlp_model.py 文件源码

def _input_dropout(self,inputs):
    # This implementation of dropout dropouts an entire feature along the time dim
    random_tensor = self._keep_prob
    random_tensor += random_ops.random_uniform([self._batch_size,self._num_inputs],
                                               dtype=inputs.dtype)
    random_tensor = tf.tile(random_tensor,[1,self._num_unrollings])
    binary_tensor = math_ops.floor(random_tensor)

    ret = math_ops.div(inputs, self._keep_prob) * binary_tensor
    ret.set_shape(inputs.get_shape())
    return ret