Maximum

ivy/functional/frontends/paddle/tensor/tensor.py

@@ -459,6 +459,10 @@ def equal_all(self, y, name=None):
             ivy.array_equal(self._ivy_array, _to_ivy_array(y))
         )
 
+    @with_supported_dtypes({"2.5.0 and below": ("float32", "float64")}, "paddle")
+    def maximum(self, other, name=None):
+        return ivy.maximum(self._ivy_array, other)
+
     @with_unsupported_dtypes({"2.5.0 and below": "bfloat16"}, "paddle")
     def fmax(self, y, name=None):
         return paddle_frontend.Tensor(ivy.fmax(self._ivy_array, _to_ivy_array(y)))

ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py

@@ -1,8 +1,6 @@
+# flake8: noqa
 # global
 import numpy as np
-from hypothesis import assume, given
-from hypothesis import strategies as st
-
 import ivy
 
 # local
@@ -2721,6 +2719,41 @@ def test_paddle_instance_min(
     )
 
 
+# maximum
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="maximum",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+)
+def test_paddle_instance_maximum(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={"other": x[1]},
+        frontend=frontend,
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        on_device=on_device,
+    )
+
+
 # std
 @handle_frontend_method(
     class_tree=CLASS_TREE,