问为什么tf.contrib.layers.instance_norm层包含StopGradient操作？

EN

x_m, x_v = tf.nn.moments(x, [1, 2], keep_dims=True)

# The dynamic range of fp16 is too limited to support the collection of
# sufficient statistics. As a workaround we simply perform the operations
# on 32-bit floats before converting the mean and variance back to fp16
y = math_ops.cast(x, dtypes.float32) if x.dtype == dtypes.float16 else x
# Compute true mean while keeping the dims for proper broadcasting.
mean = math_ops.reduce_mean(y, axes, keepdims=True, name="mean")
# sample variance, not unbiased variance
# Note: stop_gradient does not change the gradient that gets
#       backpropagated to the mean from the variance calculation,
#       because that gradient is zero
variance = math_ops.reduce_mean(
    math_ops.squared_difference(y, array_ops.stop_gradient(mean)),
    axes,
    keepdims=True,
    name="variance")