`tf.function`-local variable: during each execution of the
        `tf.function`, the variable will be created and then disposed, similar
        to a local (i.e. stack-allocated) variable in C/C++. Currently
        `experimental_enable_variable_lifting=False` only works on non-XLA
        devices (e.g. under `@tf.function(jit_compile=False)`).

*   TF SavedModel:

     * comment: Online help key for related query.
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getOnlineHelpNameRelatedquery();

    /**
     * Get the value for the key 'online.help.name.relatedcontent'. <br>
     * The value is, e.g. relatedcontent <br>
     * comment: Online help key for related content.

the size of m and overwritten. // //go:norace func (x *Nat) montgomeryMul(a *Nat, b *Nat, m *Modulus) *Nat { n := len(m.nat.limbs) mLimbs := m.nat.limbs[:n] aLimbs := a.limbs[:n] bLimbs := b.limbs[:n] switch n { default: // Attempt to use a stack-allocated backing array. T := make([]uint, 0, preallocLimbs*2) if cap(T) < n*2 { T = make([]uint, 0, n*2) } T = T[:n*2] // This loop implements Word-by-Word Montgomery Multiplication, as // described in Algorithm 4 (Fig. 3) of "Efficient Software // Implementations...