mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

    analyze programmatically. By using aliases here, we would need to handle
    potentially aliased go_binary targets and dereference to the effective
    target.
  
    The comment references an issue with `pure = select(...)` which appears
    to be resolved considering this now builds.
  
  - make kube::util::find-binary not dependent on bazel-out/ structure