message: Modularized gaussian noises' dtype.
  Enforced the adjustment of gaussian noises' dtype with that of the inputs.
  This fixes issue
diff: @@ -65,7 +65,9 @@ class GaussianNoise(Layer):
  def noised():
  return inputs + K.random_normal(
  - shape=array_ops.shape(inputs), mean=0., stddev=self.stddev)
  + shape=array_ops.shape(inputs), mean=0., stddev=self.stddev,
  + dtype=inputs.dtype
  + )
  return K.in_train_phase(noised, inputs, training=training)
  @@ -115,7 +117,9 @@ class GaussianDropout(Layer):
  def noised():
  stddev = np.sqrt(self.rate / (1.0 - self.rate))
  return inputs * K.random_normal(
  - shape=array_ops.shape(inputs), mean=1.0, stddev=stddev)
  + shape=array_ops.shape(inputs), mean=1.0, stddev=stddev,
  + dtype=inputs.dtype
  + )
  return K.in_train_phase(noised, inputs, training=training)
  return inputs
  