Fixes float64 type promotion issue (#21693)

Author: JyotinderSingh

keras/src/backend/common/dtypes.py

@@ -237,7 +237,7 @@ def _resolve_weak_type(dtype, precision="32"):
     # enable the int64 dtype for TF.
     "int64": "int64" if config.backend() == "tensorflow" else "int32",
     "uint64": "uint32",
-    "float64": "float32",
+    "float64": "float64" if config.backend() == "tensorflow" else "float32",
     "complex128": "complex64",
 }
 

keras/src/backend/common/dtypes_test.py

@@ -86,6 +86,33 @@ def test_result_type_with_int64(self, dtype):
         out = backend.result_type(x1.dtype, x2.dtype)
         self.assertEqual(out, "int64")
 
+    @parameterized.named_parameters(
+        named_product(
+            dtype=[
+                "float16",
+                "bfloat16",
+                "float32",
+                "float64",
+                "int8",
+                "int16",
+                "int32",
+                "int64",
+                "uint8",
+                "uint16",
+            ]
+        )
+    )
+    @pytest.mark.skipif(
+        backend.backend() != "tensorflow", reason="TensorFlow only"
+    )
+    def test_result_type_with_float64(self, dtype):
+        # Float types have a similar issue as int64 in TF.:
+        # https://github.com/keras-team/keras/issues/21677
+        x1 = ops.ones((1,), dtype="float64")
+        x2 = ops.ones((1,), dtype=dtype)
+        out = backend.result_type(x1.dtype, x2.dtype)
+        self.assertEqual(out, "float64")
+
     def test_result_type_with_none(self):
         import jax.numpy as jnp