added func and test

ivy/functional/frontends/torch/tensor.py

@@ -1833,6 +1833,24 @@ def char(self):
     def lcm(self, other, *, out=None):
         return torch_frontend.lcm(self, other, out=out)
 
+    @with_unsupported_dtypes(
+        {
+            "2.0.1 and below": (
+                "float16",
+                "bfloat16",
+                "float32",
+                "float64",
+                "complex",
+                "uint8",
+                "int8",
+            )
+        },
+        "torch",
+    )
+    def lcm_(self, other, *, out=None):
+        self.ivy_array = self.lcm(other, out=out).ivy_array
+        return self
+
     @with_unsupported_dtypes(
         {
             "2.0.1 and below": (

ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py

@@ -7851,6 +7851,51 @@ def test_torch_tensor_lcm(
     )
 
 
+# lcm_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="lcm_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("integer"),
+        num_arrays=2,
+        min_value=-100,
+        max_value=100,
+        min_num_dims=1,
+        max_num_dims=3,
+        min_dim_size=1,
+        max_dim_size=3,
+        shared_dtype=True,
+    ),
+)
+def test_torch_tensor_lcm_(
+    dtype_and_x,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        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,
+    )
+
+
 # less
 @handle_frontend_method(
     class_tree=CLASS_TREE,