xlogy_

ivy/functional/frontends/torch/tensor.py

@@ -1878,6 +1878,14 @@ def index_fill(self, dim, index, value):
     def cummax(self, dim):
         return torch_frontend.cummax(self, dim)
 
+    @with_unsupported_dtypes(
+        {"2.0.1 and below": ("bfloat16",)},
+        "torch",
+    )
+    def xlogy_(self, *, other, out=None):
+        self.ivy_array = torch_frontend.xlogy(self, other, out=out).ivy_array
+        return self
+
     def ne(self, other):
         return torch_frontend.ne(self, other)
 

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -12540,6 +12540,48 @@ def test_torch_tensor_where(
     )
 
 
+# xlogy_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="xlogy_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        num_arrays=2,
+        min_num_dims=1,
+        min_value=-100,
+        max_value=100,
+        shared_dtype=True,
+    ),
+)
+def test_torch_tensor_xlogy_(
+    dtype_and_x,
+    frontend,
+    backend_fw,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    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_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        on_device=on_device,
+    )
+
+
 # zero_ tests
 @handle_frontend_method(
     class_tree=CLASS_TREE,