added lu factor to torch frontend and tested

ivy/functional/frontends/torch/linalg.py

@@ -280,3 +280,7 @@ def solve_ex(A, B, *, left=True, check_errors=False, out=None):
             info = ivy.ones(A.shape[:-2], dtype=ivy.int32)
 
             return result, info
+
+@to_ivy_arrays_and_back
+def lu(a, *, pivot=True, out=None):
+    return ivy.lu_factor(a, pivot=pivot, out=out)

ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py

@@ -1355,3 +1355,29 @@ def test_torch_solve_ex(
         B=other,
         check_errors=check,
     )
+
+@handle_frontend_test(
+    fn_tree="torch.linalg.lu_factor", input_dtype_and_input=_lu_factor_helper()
+)
+def test_torch_lu(*, input_dtype_and_input, on_device, fn_tree, frontend, test_flags):
+    dtype, input = input_dtype_and_input
+    ret, frontend_ret = helpers.test_frontend_function(
+        input_dtypes=dtype,
+        test_flags=test_flags,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        test_values=False,
+        A=input,
+    )
+    ret = [ivy.to_numpy(x) for x in ret]
+    frontend_ret = [np.asarray(x) for x in frontend_ret]
+
+    LU, pivot = ret
+    frontend_LU, frontend_pivot = frontend_ret
+
+    assert_all_close(
+        ret_np=[LU, pivot],
+        ret_from_gt_np=[frontend_LU, frontend_pivot],
+        ground_truth_backend=frontend,
+    )