Implement isposinf function in keras.ops (#21582)

shashaka · web-flow · commit 89a8676ca994 · 2025-08-16T17:55:37.000-07:00
* Add isposinf for keras.ops

* Update openvino numpy for isposinf

* Correct code by gemini assist
diff --git a/keras/api/_tf_keras/keras/ops/__init__.py b/keras/api/_tf_keras/keras/ops/__init__.py
@@ -204,6 +204,7 @@
 from keras.src.ops.numpy import isinf as isinf
 from keras.src.ops.numpy import isnan as isnan
 from keras.src.ops.numpy import isneginf as isneginf
+from keras.src.ops.numpy import isposinf as isposinf
 from keras.src.ops.numpy import kaiser as kaiser
 from keras.src.ops.numpy import left_shift as left_shift
 from keras.src.ops.numpy import less as less
diff --git a/keras/api/_tf_keras/keras/ops/numpy/__init__.py b/keras/api/_tf_keras/keras/ops/numpy/__init__.py
@@ -92,6 +92,7 @@
 from keras.src.ops.numpy import isinf as isinf
 from keras.src.ops.numpy import isnan as isnan
 from keras.src.ops.numpy import isneginf as isneginf
+from keras.src.ops.numpy import isposinf as isposinf
 from keras.src.ops.numpy import kaiser as kaiser
 from keras.src.ops.numpy import left_shift as left_shift
 from keras.src.ops.numpy import less as less
diff --git a/keras/api/ops/__init__.py b/keras/api/ops/__init__.py
@@ -204,6 +204,7 @@
 from keras.src.ops.numpy import isinf as isinf
 from keras.src.ops.numpy import isnan as isnan
 from keras.src.ops.numpy import isneginf as isneginf
+from keras.src.ops.numpy import isposinf as isposinf
 from keras.src.ops.numpy import kaiser as kaiser
 from keras.src.ops.numpy import left_shift as left_shift
 from keras.src.ops.numpy import less as less
diff --git a/keras/api/ops/numpy/__init__.py b/keras/api/ops/numpy/__init__.py
@@ -92,6 +92,7 @@
 from keras.src.ops.numpy import isinf as isinf
 from keras.src.ops.numpy import isnan as isnan
 from keras.src.ops.numpy import isneginf as isneginf
+from keras.src.ops.numpy import isposinf as isposinf
 from keras.src.ops.numpy import kaiser as kaiser
 from keras.src.ops.numpy import left_shift as left_shift
 from keras.src.ops.numpy import less as less
diff --git a/keras/src/backend/jax/numpy.py b/keras/src/backend/jax/numpy.py
@@ -792,6 +792,11 @@ def isneginf(x):
     return jnp.isneginf(x)
 
 
+def isposinf(x):
+    x = convert_to_tensor(x)
+    return jnp.isposinf(x)
+
+
 def less(x1, x2):
     x1 = convert_to_tensor(x1)
     x2 = convert_to_tensor(x2)
diff --git a/keras/src/backend/numpy/numpy.py b/keras/src/backend/numpy/numpy.py
@@ -701,6 +701,11 @@ def isneginf(x):
     return np.isneginf(x)
 
 
+def isposinf(x):
+    x = convert_to_tensor(x)
+    return np.isposinf(x)
+
+
 def less(x1, x2):
     return np.less(x1, x2)
 
diff --git a/keras/src/backend/openvino/excluded_concrete_tests.txt b/keras/src/backend/openvino/excluded_concrete_tests.txt
@@ -35,6 +35,7 @@ NumpyDtypeTest::test_isin
 NumpyDtypeTest::test_isinf
 NumpyDtypeTest::test_isnan
 NumpyDtypeTest::test_isneginf
+NumpyDtypeTest::test_isposinf
 NumpyDtypeTest::test_linspace
 NumpyDtypeTest::test_logaddexp
 NumpyDtypeTest::test_logspace
@@ -94,6 +95,7 @@ NumpyOneInputOpsCorrectnessTest::test_imag
 NumpyOneInputOpsCorrectnessTest::test_isfinite
 NumpyOneInputOpsCorrectnessTest::test_isinf
 NumpyOneInputOpsCorrectnessTest::test_isneginf
+NumpyOneInputOpsCorrectnessTest::test_isposinf
 NumpyOneInputOpsCorrectnessTest::test_logaddexp
 NumpyOneInputOpsCorrectnessTest::test_max
 NumpyOneInputOpsCorrectnessTest::test_mean
@@ -155,10 +157,12 @@ NumpyOneInputOpsDynamicShapeTest::test_corrcoef
 NumpyOneInputOpsDynamicShapeTest::test_hamming
 NumpyOneInputOpsDynamicShapeTest::test_hanning
 NumpyOneInputOpsDynamicShapeTest::test_isneginf
+NumpyOneInputOpsDynamicShapeTest::test_isposinf
 NumpyOneInputOpsDynamicShapeTest::test_kaiser
 NumpyOneInputOpsStaticShapeTest::test_angle
 NumpyOneInputOpsStaticShapeTest::test_cbrt
 NumpyOneInputOpsStaticShapeTest::test_isneginf
+NumpyOneInputOpsStaticShapeTest::test_isposinf
 NumpyTwoInputOpsDynamicShapeTest::test_heaviside
 NumpyTwoInputOpsDynamicShapeTest::test_isin
 NumpyTwoInputOpsStaticShapeTest::test_heaviside
diff --git a/keras/src/backend/openvino/numpy.py b/keras/src/backend/openvino/numpy.py
@@ -964,6 +964,12 @@ def isneginf(x):
     )
 
 
+def isposinf(x):
+    raise NotImplementedError(
+        "`isposinf` is not supported with openvino backend"
+    )
+
+
 def less(x1, x2):
     element_type = None
     if isinstance(x1, OpenVINOKerasTensor):
diff --git a/keras/src/backend/tensorflow/numpy.py b/keras/src/backend/tensorflow/numpy.py
@@ -1640,10 +1640,18 @@ def isneginf(x):
     x = convert_to_tensor(x)
     dtype_as_dtype = tf.as_dtype(x.dtype)
     if dtype_as_dtype.is_integer or not dtype_as_dtype.is_numeric:
-        return tf.zeros(x.shape, tf.bool)
+        return tf.zeros_like(x, dtype=tf.bool)
     return tf.math.equal(x, -tf.constant(float("inf"), dtype=x.dtype))
 
 
+def isposinf(x):
+    x = convert_to_tensor(x)
+    dtype_as_dtype = tf.as_dtype(x.dtype)
+    if dtype_as_dtype.is_integer or not dtype_as_dtype.is_numeric:
+        return tf.zeros_like(x, dtype=tf.bool)
+    return tf.math.equal(x, tf.constant(float("inf"), dtype=x.dtype))
+
+
 def less(x1, x2):
     x1 = convert_to_tensor(x1)
     x2 = convert_to_tensor(x2)
diff --git a/keras/src/backend/torch/numpy.py b/keras/src/backend/torch/numpy.py
@@ -918,6 +918,11 @@ def isneginf(x):
     return torch.isneginf(x)
 
 
+def isposinf(x):
+    x = convert_to_tensor(x)
+    return torch.isposinf(x)
+
+
 def less(x1, x2):
     x1, x2 = convert_to_tensor(x1), convert_to_tensor(x2)
     return torch.less(x1, x2)
diff --git a/keras/src/ops/numpy.py b/keras/src/ops/numpy.py
@@ -3747,6 +3747,29 @@ def isneginf(x):
     return backend.numpy.isneginf(x)
 
 
+class Isposinf(Operation):
+    def call(self, x):
+        return backend.numpy.isposinf(x)
+
+    def compute_output_spec(self, x):
+        return KerasTensor(x.shape, dtype="bool")
+
+
+@keras_export(["keras.ops.isposinf", "keras.ops.numpy.isposinf"])
+def isposinf(x):
+    """Test element-wise for positive infinity.
+
+    Args:
+        x: Input tensor.
+
+    Returns:
+        Output boolean tensor.
+    """
+    if any_symbolic_tensors((x,)):
+        return Isposinf().symbolic_call(x)
+    return backend.numpy.isposinf(x)
+
+
 class Less(Operation):
     def call(self, x1, x2):
         return backend.numpy.less(x1, x2)
diff --git a/keras/src/ops/numpy_test.py b/keras/src/ops/numpy_test.py
@@ -1516,6 +1516,10 @@ def test_isneginf(self):
         x = KerasTensor((None, 3))
         self.assertEqual(knp.isneginf(x).shape, (None, 3))
 
+    def test_isposinf(self):
+        x = KerasTensor((None, 3))
+        self.assertEqual(knp.isposinf(x).shape, (None, 3))
+
     def test_log(self):
         x = KerasTensor((None, 3))
         self.assertEqual(knp.log(x).shape, (None, 3))
@@ -2113,6 +2117,10 @@ def test_isneginf(self):
         x = KerasTensor((2, 3))
         self.assertEqual(knp.isneginf(x).shape, (2, 3))
 
+    def test_isposinf(self):
+        x = KerasTensor((2, 3))
+        self.assertEqual(knp.isposinf(x).shape, (2, 3))
+
     def test_log(self):
         x = KerasTensor((2, 3))
         self.assertEqual(knp.log(x).shape, (2, 3))
@@ -4254,6 +4262,13 @@ def test_isneginf(self):
         self.assertAllClose(knp.isneginf(x), np.isneginf(x))
         self.assertAllClose(knp.Isneginf()(x), np.isneginf(x))
 
+    def test_isposinf(self):
+        x = np.array(
+            [[1, 2, np.inf, -np.inf], [np.nan, np.nan, np.nan, np.nan]]
+        )
+        self.assertAllClose(knp.isposinf(x), np.isposinf(x))
+        self.assertAllClose(knp.Isposinf()(x), np.isposinf(x))
+
     def test_log(self):
         x = np.array([[1, 2, 3], [3, 2, 1]])
         self.assertAllClose(knp.log(x), np.log(x))
@@ -7599,6 +7614,22 @@ def test_isneginf(self, dtype):
             expected_dtype,
         )
 
+    @parameterized.named_parameters(named_product(dtype=ALL_DTYPES))
+    def test_isposinf(self, dtype):
+        import jax.numpy as jnp
+
+        x = knp.ones((), dtype=dtype)
+        x_jax = jnp.ones((), dtype=dtype)
+        expected_dtype = standardize_dtype(jnp.isposinf(x_jax).dtype)
+
+        self.assertEqual(
+            standardize_dtype(knp.isposinf(x).dtype), expected_dtype
+        )
+        self.assertEqual(
+            standardize_dtype(knp.Isposinf().symbolic_call(x).dtype),
+            expected_dtype,
+        )
+
     @parameterized.named_parameters(
         named_product(dtypes=itertools.combinations(ALL_DTYPES, 2))
     )
