Fix(OpenVINO): Ensure numpy.prod passes tests and handles boolean inp…

.gitignore

@@ -19,4 +19,5 @@ examples/**/*.jpg
 .python-version
 .coverage
 *coverage.xml
-.ruff_cache
+.ruff_cache
+my_clean_keras_env_py310/

keras/src/backend/openvino/excluded_concrete_tests.txt

@@ -43,7 +43,6 @@ NumpyDtypeTest::test_meshgrid
 NumpyDtypeTest::test_minimum_python_types
 NumpyDtypeTest::test_multiply
 NumpyDtypeTest::test_power
-NumpyDtypeTest::test_prod
 NumpyDtypeTest::test_quantile
 NumpyDtypeTest::test_repeat
 NumpyDtypeTest::test_roll
@@ -104,7 +103,6 @@ NumpyOneInputOpsCorrectnessTest::test_pad_int16_constant_2
 NumpyOneInputOpsCorrectnessTest::test_pad_int8_constant_2
 NumpyOneInputOpsCorrectnessTest::test_pad_uint8_constant_2
 NumpyOneInputOpsCorrectnessTest::test_pad_int32_constant_2
-NumpyOneInputOpsCorrectnessTest::test_prod
 NumpyOneInputOpsCorrectnessTest::test_real
 NumpyOneInputOpsCorrectnessTest::test_repeat
 NumpyOneInputOpsCorrectnessTest::test_reshape

keras/src/backend/openvino/numpy.py

@@ -1262,8 +1262,52 @@ def pad(x, pad_width, mode="constant", constant_values=None):
 
 
 def prod(x, axis=None, keepdims=False, dtype=None):
-    raise NotImplementedError("`prod` is not supported with openvino backend")
+    if axis == () or axis == []:
+        return x
+
+    x = get_ov_output(x)
+
+    if axis is None:
+        flatten_shape = ov_opset.constant([-1], Type.i32).output(0)
+        x = ov_opset.reshape(x, flatten_shape, False).output(0)
+        axis = 0
+    elif isinstance(axis, tuple):
+        axis = list(axis)
+
+    axis = ov_opset.constant(axis, Type.i32).output(0)
+
+    x_type = x.get_element_type()
+
+    promotion_map = {
+        Type.bf16: Type.bf16,
+        Type.f16: Type.f16,
+        Type.f32: Type.f32,
+        Type.f64: Type.f64,
+        Type.i8: Type.i32,
+        Type.i16: Type.i32,
+        Type.i32: Type.i32,
+        Type.i64: Type.i64,
+        Type.u8: Type.u32,
+        Type.u16: Type.u32,
+        Type.u32: Type.u32,
+        Type.u64: Type.u64,
+    }
+
+    if x_type == Type.boolean:
+        result_node = ov_opset.reduce_logical_and(x, axis, keepdims).output(0)
+        final_result = ov_opset.convert(result_node, Type.i32).output(0)
+        return OpenVINOKerasTensor(final_result)
+
+    target_type = None
+    if dtype is None:
+        target_type = promotion_map.get(x_type, x_type)
+    else:
+        dtype_string = standardize_dtype(dtype)
+        target_type = OPENVINO_DTYPES[dtype_string]
 
+    temporary_result = ov_opset.reduce_prod(x, axis, keepdims).output(0)
+    final_result = ov_opset.convert(temporary_result, target_type).output(0)
+    return OpenVINOKerasTensor(final_result)
 
 def quantile(x, q, axis=None, method="linear", keepdims=False):
     raise NotImplementedError(