Fix keras.layers.ReLU docs #48646

tensorflow/python/keras/layers/advanced_activations.py

@@ -404,20 +404,21 @@ class ReLU(Layer):
     max_value: Float >= 0. Maximum activation value. Default to None, which
       means unlimited.
     negative_slope: Float >= 0. Negative slope coefficient. Default to 0.
-    threshold: Float. Threshold value for thresholded activation. Default to 0.
+    threshold: Float >= 0. Threshold value for thresholded activation. Default
+      to 0.
   """
 
   def __init__(self, max_value=None, negative_slope=0, threshold=0, **kwargs):
     super(ReLU, self).__init__(**kwargs)
     if max_value is not None and max_value < 0.:
-      raise ValueError('max_value of Relu layer '
-                       'cannot be negative value: ' + str(max_value))
-    if negative_slope < 0.:
-      raise ValueError('negative_slope of Relu layer '
-                       'cannot be negative value: ' + str(negative_slope))
-    if threshold is None:
-      raise ValueError('threshold of Relu layer '
-                       'cannot be None. Required a float')
+      raise ValueError('max_value of a ReLU layer cannot be a negative '
+                       'value. Got: %s' % max_value)
+    if negative_slope is None or negative_slope < 0.:
+      raise ValueError('negative_slope of a ReLU layer cannot be a negative '
+                       'value. Got: %s' % negative_slope)
+    if threshold is None or threshold < 0.:
+      raise ValueError('threshold of a ReLU layer cannot be a negative '
+                       'value. Got: %s' % threshold)
 
     self.supports_masking = True
     if max_value is not None:

tensorflow/python/keras/layers/advanced_activations_test.py

@@ -78,21 +78,53 @@ def test_relu(self):
       # Test that we use `relu6` when appropriate in graph mode.
       self.assertTrue('Relu6' in keras.layers.ReLU(max_value=6)(x).name)
 
-  def test_relu_with_invalid_arg(self):
+  def test_relu_with_invalid_max_value(self):
     with self.assertRaisesRegex(
-        ValueError, 'max_value of Relu layer cannot be negative value: -10'):
-      testing_utils.layer_test(keras.layers.ReLU,
-                               kwargs={'max_value': -10},
-                               input_shape=(2, 3, 4),
-                               supports_masking=True)
+        ValueError, 'max_value of a ReLU layer cannot be a negative '
+                    'value. Got: -10'):
+      testing_utils.layer_test(
+          keras.layers.ReLU,
+          kwargs={'max_value': -10},
+          input_shape=(2, 3, 4),
+          supports_masking=True)
+
+  def test_relu_with_invalid_negative_slope(self):
+    with self.assertRaisesRegex(
+        ValueError, 'negative_slope of a ReLU layer cannot be a negative '
+                    'value. Got: None'):
+      testing_utils.layer_test(
+          keras.layers.ReLU,
+          kwargs={'negative_slope': None},
+          input_shape=(2, 3, 4),
+          supports_masking=True)
+
+    with self.assertRaisesRegex(
+        ValueError, 'negative_slope of a ReLU layer cannot be a negative '
+                    'value. Got: -10'):
+      testing_utils.layer_test(
+          keras.layers.ReLU,
+          kwargs={'negative_slope': -10},
+          input_shape=(2, 3, 4),
+          supports_masking=True)
+
+  def test_relu_with_invalid_threshold(self):
+    with self.assertRaisesRegex(
+        ValueError, 'threshold of a ReLU layer cannot be a negative '
+                    'value. Got: None'):
+      testing_utils.layer_test(
+          keras.layers.ReLU,
+          kwargs={'threshold': None},
+          input_shape=(2, 3, 4),
+          supports_masking=True)
+
     with self.assertRaisesRegex(
-        ValueError,
-        'negative_slope of Relu layer cannot be negative value: -2'):
-      with self.cached_session():
-        testing_utils.layer_test(
-            keras.layers.ReLU,
-            kwargs={'negative_slope': -2},
-            input_shape=(2, 3, 4))
+        ValueError, 'threshold of a ReLU layer cannot be a negative '
+                    'value. Got: -10'):
+      testing_utils.layer_test(
+          keras.layers.ReLU,
+          kwargs={'threshold': -10},
+          input_shape=(2, 3, 4),
+          supports_masking=True)
 
   @keras_parameterized.run_with_all_model_types
   def test_layer_as_activation(self):
@@ -126,7 +158,7 @@ def test_leaky_elu_with_invalid_alpha(self):
           input_shape=(2, 3, 4),
           supports_masking=True)
 
-  def test_threshold_relu_with_invalid_alpha(self):
+  def test_threshold_relu_with_invalid_theta(self):
     with self.assertRaisesRegex(
         ValueError, 'Theta of a Thresholded ReLU layer cannot '
         'be None, requires a float. Got None'):