Add a design topic page on lazy vs. eager implementations

Follow-up to data-apisgh-652, which added notes to the specifications for
`__bool__` & co on this topic.

spec/draft/design_topics/index.rst

@@ -7,6 +7,7 @@ Design topics & constraints
 
    copies_views_and_mutation
    data_dependent_output_shapes
+   lazy_eager
    data_interchange
    device_support
    static_typing

spec/draft/design_topics/lazy_eager.rst

@@ -0,0 +1,23 @@
+.. _lazy-eager:
+
+Lazy vs. eager execution
+========================
+
+While the execution model for implementations is out of scope of this standard, there are a few aspects of lazy (or graph-based) execution as contrasted to eager execution that may have an impact on the prescribed semantics of individual APIs, and will therefore show up in the API specification.
+
+One important difference is data-dependent or value-dependent behavior, as described in :ref:`data-dependent-output-shapes`. Because such behavior is hard to implement, implementers may choose to omit such APIs from their library.
+
+Another difference is when the Python language itself prescribes that a specific type *must* be returned. For those cases, it is not possible to return a lazy/delayed kind of object to avoid computing a value. This is the case for five dunder methods: `__bool__`, `__int__`, `__float__`, `__complex__` and `__index__`. Each implementation has only two choices when one of these methods is called:
+
+1. Compute a value of the required type (a Python scalar of type `bool`, `int`, `float` or `complex`), or
+2. Raise an exception.
+
+When an implementation is 100% lazy, for example when it serializes a computation graph, computing the value is not possible and hence such an implementation has no choice but to raise an exception. For a "mostly lazy" implementation, it may make sense to trigger execution instead - but it is not required to, both choices are valid.
+
+A common code construct where this happens is conditional logic, e.g.::
+
+    vals = compute_something()
+    if all(vals):
+        # The if-statement will make Python call the __bool__ method
+        # on the result of `all(vals)`.
+        do_something_else()