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Create a case operation.
tf.case(
pred_fn_pairs,
default=None,
exclusive=False,
strict=False,
name='case'
)
See also tf.switch_case
.
The pred_fn_pairs
parameter is a list of pairs of size N.
Each pair contains a boolean scalar tensor and a python callable that
creates the tensors to be returned if the boolean evaluates to True.
default
is a callable generating a list of tensors. All the callables
in pred_fn_pairs
as well as default
(if provided) should return the same
number and types of tensors.
If exclusive==True
, all predicates are evaluated, and an exception is
thrown if more than one of the predicates evaluates to True
.
If exclusive==False
, execution stops at the first predicate which
evaluates to True, and the tensors generated by the corresponding function
are returned immediately. If none of the predicates evaluate to True, this
operation returns the tensors generated by default
.
tf.case
supports nested structures as implemented in
tf.nest
. All of the callables must return the same (possibly nested) value
structure of lists, tuples, and/or named tuples. Singleton lists and tuples
form the only exceptions to this: when returned by a callable, they are
implicitly unpacked to single values. This behavior is disabled by passing
strict=True
.
Example 1:
Pseudocode:
if (x < y) return 17;
else return 23;
Expressions:
f1 = lambda: tf.constant(17)
f2 = lambda: tf.constant(23)
r = tf.case([(tf.less(x, y), f1)], default=f2)
Example 2:
Pseudocode:
if (x < y && x > z) raise OpError("Only one predicate may evaluate to True");
if (x < y) return 17;
else if (x > z) return 23;
else return 1;
Expressions:
def f1(): return tf.constant(17)
def f2(): return tf.constant(23)
def f3(): return tf.constant(1)
r = tf.case([(tf.less(x, y), f1), (tf.greater(x, z), f2)],
default=f3, exclusive=True)
Returns  

The tensors returned by the first pair whose predicate evaluated to True, or
those returned by default if none does.

Raises  

TypeError

If pred_fn_pairs is not a list/tuple.

TypeError

If pred_fn_pairs is a list but does not contain 2tuples.

TypeError

If fns[i] is not callable for any i, or default is not
callable.

v2 compatibility
pred_fn_pairs
could be a dictionary in v1. However, tf.Tensor and
tf.Variable are no longer hashable in v2, so cannot be used as a key for a
dictionary. Please use a list or a tuple instead.