add checking for input values in GANHead constructor

tensorflow/contrib/gan/python/estimator/python/head_impl.py

@@ -25,6 +25,7 @@ from tensorflow.contrib.gan.python import train as tfgan_train
 from tensorflow.python.estimator import model_fn as model_fn_lib
 from tensorflow.python.estimator.canned import head
 from tensorflow.python.framework import ops
+from tensorflow.python.training import optimizer
 
 __all__ = [
     'GANHead',
@@ -90,9 +91,24 @@ class GANHead(head._Head):  # pylint: disable=protected-access
       name: name of the head. If provided, summary and metrics keys will be
         suffixed by `"/" + name`.
     """
+
+    if not callable(generator_loss_fn):
+      raise TypeError('generator_loss_fn must be callable.')
+    if not callable(discriminator_loss_fn):
+      raise TypeError('discriminator_loss_fn must be callable.')
+    if not isinstance(generator_optimizer, optimizer.Optimizer):
+      raise TypeError('generator_optimizer must be Optimizer.')
+    if not isinstance(discriminator_optimizer, optimizer.Optimizer):
+      raise TypeError('discriminator_optimizer must be Optimizer.')
+    if not use_loss_summaries in [True, False, None]:
+      raise ValueError('use_loss_summaries must be True, False or None.')
+    if get_hooks_fn is not None and not callable(get_hooks_fn):
+      raise TypeError('get_hooks_fn must be callable.')
+    if name is not None and not isinstance(name, str):
+      raise TypeError('name must be string.')
+
     if get_hooks_fn is None:
       get_hooks_fn = tfgan_train.get_sequential_train_hooks()
-    # TODO(joelshor): Validate inputs.
 
     if use_loss_summaries in [True, False]:
       generator_loss_fn = functools.partial(