keras/training.py: Improve error message.

Inspired by:
https://stackoverflow.com/questions/52428939/eager-mode-optimizers/

PiperOrigin-RevId: 213948133

1 files changed, 21 insertions, 17 deletions

diff --git a/tensorflow/python/keras/engine/training.py b/tensorflow/python/keras/engine/training.py
index 7df72d45b4..154c219dcc 100644
--- a/tensorflow/python/keras/engine/training.py
+++ b/tensorflow/python/keras/engine/training.py
@@ -383,27 +383,31 @@ class Model(Network):
     """
     # Validate that arguments passed by the user to `compile` are supported by
     # DistributionStrategy.
-    if distribute and not isinstance(
-        optimizer, (tf_optimizer_module.Optimizer, optimizers.TFOptimizer)):
-      raise NotImplementedError('Only TF native optimizers are supported with '
-                                'DistributionStrategy.')
-    if distribute and context.executing_eagerly():
-      raise NotImplementedError('DistributionStrategy is not supported in '
-                                'Eager mode.')
-    if distribute and sample_weight_mode:
-      raise NotImplementedError('sample_weight_mode is not supported with '
-                                'DistributionStrategy.')
-    if distribute and weighted_metrics:
-      raise NotImplementedError('weighted_metrics is not supported with '
-                                'DistributionStrategy.')
-    if distribute and target_tensors:
-      raise ValueError('target_tensors is not supported with '
-                       'DistributionStrategy.')
+    if distribute:
+      if not isinstance(
+          optimizer, (tf_optimizer_module.Optimizer, optimizers.TFOptimizer)):
+        raise NotImplementedError(
+            'optimizer must be an instance of '
+            'tf.train.Optimizer, not a %s' % type(optimizer))
+      if context.executing_eagerly():
+        raise NotImplementedError('DistributionStrategy is not supported '
+                                  'when eager execution is enabled.')
+      if sample_weight_mode:
+        raise NotImplementedError('sample_weight_mode is not supported with '
+                                  'DistributionStrategy.')
+      if weighted_metrics:
+        raise NotImplementedError('weighted_metrics is not supported with '
+                                  'DistributionStrategy.')
+      if target_tensors:
+        raise ValueError('target_tensors is not supported with '
+                         'DistributionStrategy.')
 
     loss = loss or {}
     if context.executing_eagerly() and not isinstance(
         optimizer, (tf_optimizer_module.Optimizer, optimizers.TFOptimizer)):
-      raise ValueError('Only TF native optimizers are supported in Eager mode.')
+      raise ValueError(
+          'optimizer must be an instance of tf.train.Optimizer, not '
+          'a %s' % type(optimizer))
 
     self.optimizer = optimizers.get(optimizer)
     # We've disabled automatic dependency tracking for this method, but do want