Fix noise_shape validation in keras.layers.Dropout (#21819)

* Fix noise_shape validation in keras.layers.Dropout

* updated dropout.py to validate str for noise_shape, added unit test for _vaidate_noise_shape

* Apply suggestion from @gemini-code-assist[bot]

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

* fix minor code format issue

---------

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Author: Abhinavexists

keras/src/layers/regularization/dropout.py

@@ -48,13 +48,55 @@ def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
             )
         self.rate = rate
         self.seed = seed
-        self.noise_shape = noise_shape
+        self.noise_shape = self._validate_noise_shape(noise_shape)
         if rate > 0:
             self.seed_generator = backend.random.SeedGenerator(seed)
         self.supports_masking = True
 
         self._build_at_init()
 
+    def _validate_noise_shape(self, noise_shape):
+        if noise_shape is None:
+            return None
+
+        if isinstance(noise_shape, str):
+            raise ValueError(
+                f"Invalid value received for argument `noise_shape`. "
+                f"Expected a tuple or list of integers. "
+                f"Received: noise_shape={noise_shape}"
+            )
+
+        if not isinstance(noise_shape, tuple):
+            try:
+                noise_shape = tuple(noise_shape)
+            except TypeError:
+                raise ValueError(
+                    f"Invalid value received for argument `noise_shape`. "
+                    f"Expected an iterable of integers "
+                    f"(e.g., a tuple or list). "
+                    f"Received: noise_shape={noise_shape}"
+                )
+
+        for i, dim in enumerate(noise_shape):
+            if dim is not None:
+                if not isinstance(dim, int):
+                    raise ValueError(
+                        f"Invalid value received for argument `noise_shape`. "
+                        f"Expected all elements to be integers or None. "
+                        f"Received element at index {i}: {dim} "
+                        f"(type: {type(dim).__name__})"
+                    )
+
+                if dim <= 0:
+                    raise ValueError(
+                        f"Invalid value received for argument `noise_shape`. "
+                        f"Expected all dimensions to be positive integers "
+                        f"or None. "
+                        f"Received negative or zero value at index {i}: {dim}"
+                    )
+
+        return noise_shape
+
     def call(self, inputs, training=False):
         if training and self.rate > 0:
             return backend.random.dropout(

keras/src/layers/regularization/dropout_test.py

@@ -60,3 +60,52 @@ def test_dropout_rate_greater_than_one(self):
             "Expected a float value between 0 and 1.",
         ):
             _ = layers.Dropout(rate=1.5)
+
+    def test_validate_noise_shape_none(self):
+        layer = layers.Dropout(0.5, noise_shape=None)
+        self.assertIsNone(layer.noise_shape)
+
+    def test_validate_noise_shape_integer_tuple(self):
+        layer = layers.Dropout(0.5, noise_shape=(20, 1, 10))
+        self.assertEqual(layer.noise_shape, (20, 1, 10))
+
+    def test_validate_noise_shape_none_values(self):
+        layer = layers.Dropout(0.5, noise_shape=(None, 1, None))
+        self.assertEqual(layer.noise_shape, (None, 1, None))
+
+    def test_validate_noise_shape_cast_to_a_tuple(self):
+        layer = layers.Dropout(0.5, noise_shape=[20, 1, 10])
+        self.assertEqual(layer.noise_shape, (20, 1, 10))
+        self.assertIsInstance(layer.noise_shape, tuple)
+
+    def test_validate_noise_shape_non_iterable(self):
+        with self.assertRaisesRegex(
+            ValueError,
+            "Invalid value received for argument `noise_shape`. "
+            "Expected a tuple or list of integers.",
+        ):
+            layers.Dropout(0.5, noise_shape="Invalid")
+
+    def test_validate_noise_shape_invalid_type(self):
+        with self.assertRaisesRegex(
+            ValueError,
+            "Invalid value received for argument `noise_shape`. "
+            "Expected all elements to be integers or None.",
+        ):
+            layers.Dropout(0.5, noise_shape=(20, 1.5, 10))
+
+    def test_validate_noise_shape_negative_value(self):
+        with self.assertRaisesRegex(
+            ValueError,
+            "Invalid value received for argument `noise_shape`. "
+            "Expected all dimensions to be positive integers or None.",
+        ):
+            layers.Dropout(0.5, noise_shape=(20, -1, 10))
+
+    def test_validate_noise_shape_zero_value(self):
+        with self.assertRaisesRegex(
+            ValueError,
+            "Invalid value received for argument `noise_shape`. "
+            "Expected all dimensions to be positive integers or None.",
+        ):
+            layers.Dropout(0.5, noise_shape=(20, 0, 10))