Fix and update GQA tests

keras/src/layers/attention/grouped_query_attention_test.py

@@ -232,14 +232,25 @@ def test_initializer(self):
     )
     def test_query_mask_propagation(self):
         """Test automatic propagation of the query's mask."""
-        layer = layers.GroupedQueryAttention(
-            num_query_heads=2, num_key_value_heads=2, head_dim=2
-        )
-        self.assertTrue(layer.supports_masking)
-        query = np.array([[1, 2, 3, 0, 0], [3, 3, 1, 1, 2], [1, 0, 0, 0, 0]])
-        masked_query = layers.Embedding(4, 8, mask_zero=True)(query)
-        value = np.random.normal(size=(3, 3, 8))
-        output = layer(query=masked_query, value=value)
+        try:
+            layer = layers.GroupedQueryAttention(
+                num_query_heads=2, num_key_value_heads=2, head_dim=2
+            )
+            self.assertTrue(layer.supports_masking)
+            query = np.array(
+                [[1, 2, 3, 0, 0], [3, 3, 1, 1, 2], [1, 0, 0, 0, 0]]
+            )
+            masked_query = layers.Embedding(4, 8, mask_zero=True)(query)
+            value = np.random.normal(size=(3, 3, 8))
+            output = layer(query=masked_query, value=value)
+        except RuntimeError as e:
+            if e.args[0].startswith(
+                "(*bias): last dimension must be contiguous"
+            ):
+                self.skipTest(
+                    "PyTorch errors out on GPU: issue to track bug is here "
+                    "https://github.com/keras-team/keras/issues/20459"
+                )
         self.assertAllClose(masked_query._keras_mask, output._keras_mask)
 
     @parameterized.named_parameters(("causal", True), ("not_causal", 0))
@@ -278,8 +289,7 @@ def test_masking(self, use_causal_mask):
         self.assertAllClose(output, output_with_manual_mask)
 
     @parameterized.named_parameters(
-        ("disable_flash_attention", False),
-        ("enable_flash_attention", True),
+        ("disable_flash_attention", False), ("enable_flash_attention", True)
     )
     def test_correctness(self, flash_attention):
         if flash_attention:
@@ -348,3 +358,41 @@ def test_correctness(self, flash_attention):
             )
             self.assertAllClose(output, expected_output, atol=1e-2)
             self.assertAllClose(scores, expected_score, atol=1e-2)
+
+    def test_flash_attention_with_errors(self):
+        if backend.backend() in ("numpy", "tensorflow"):
+            pytest.skip(
+                reason=(
+                    "Flash attention is not supported on tensorflow and numpy."
+                )
+            )
+        # Check `flash_attention=True` and `dropout=0.1`
+        with self.assertRaisesRegex(
+            ValueError,
+            "Dropout is not supported when flash attention is enabled.",
+        ):
+            layer = layers.GroupedQueryAttention(
+                head_dim=2,
+                num_query_heads=2,
+                num_key_value_heads=2,
+                flash_attention=True,
+                dropout=0.1,
+            )
+
+        # Check `flash_attention=True` and `return_attention_scores=True`
+        layer = layers.GroupedQueryAttention(
+            head_dim=2,
+            num_query_heads=2,
+            num_key_value_heads=2,
+            flash_attention=True,
+        )
+        self.assertTrue(layer._flash_attention)
+        query = np.random.random((2, 4, 8))
+        value = np.random.random((2, 4, 8))
+        with self.assertRaisesRegex(
+            ValueError,
+            "Returning attention scores is not supported when flash "
+            "attention is enabled. Please disable flash attention to access"
+            " attention scores.",
+        ):
+            layer(query=query, value=value, return_attention_scores=True)