[`tf.keras.layers.MultiHeadAttention`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MultiHeadAttention).
        *   Implicit masks for `query`, `key` and `value` inputs will
            automatically be used to compute a correct attention mask for the
            layer. These padding masks will be combined with any
            `attention_mask` passed in directly when calling the layer. This can
            be used with

		// In that case (handled below), we emit a bound check (and Spectre mask)
		// and then the prove pass will remove the bounds check.
		// In theory the prove pass could potentially remove certain
		// Spectre masks, but it's very delicate and probably better
		// to be conservative and leave them all in.
		return idx
	}

	bNext := s.f.NewBlock(ssa.BlockPlain)
	bPanic := s.f.NewBlock(ssa.BlockExit)

`end = begin + 1 = 2`. To disambiguate from the original spec `2:4` we
also set the appropriate bit in `shrink_axis_mask`.

2. `2:4` is contributes 2, 4, 1 to begin, end, and stride. All masks have
zero bits contributed.

3. None is a synonym for `tf.newaxis`. This means insert a dimension of size 1
dimension in the final shape. Dummy values are contributed to begin,