Added cholesky to torch frontend (#7694)

* add cholesky to torch frontend

* add blank line

* formatting

ivy/functional/frontends/torch/linalg.py

@@ -69,6 +69,11 @@ def matrix_rank(input, *, atol=None, rtol=None, hermitian=False, out=None):
     return ivy.astype(ivy.matrix_rank(input, atol=atol, rtol=rtol, out=out), ivy.int64)
 
 
+@to_ivy_arrays_and_back
+def cholesky(input, *, upper=False, out=None):
+    return ivy.cholesky(input, upper=upper, out=out)
+
+
 @to_ivy_arrays_and_back
 def svd(input, /, *, full_matrices=True):
     return ivy.svd(input, compute_uv=True, full_matrices=full_matrices)

ivy_tests/test_ivy/test_frontends/test_torch/test_linalg.py

@@ -311,8 +311,44 @@ def test_matrix_rank(
         rtol=rtol,
         atol=atol,
     )
+
+
+@handle_frontend_test(
+    fn_tree="torch.linalg.cholesky",
+    dtype_and_x=_get_dtype_and_square_matrix(),
+    upper=st.booleans(),
+)
+def test_torch_cholesky(
+    *,
+    dtype_and_x,
+    upper,
+    as_variable,
+    with_out,
+    num_positional_args,
+    native_array,
+    on_device,
+    fn_tree,
+    frontend,
+):
+    dtype, x = dtype_and_x
+    x = np.matmul(x.T, x) + np.identity(x.shape[0])  # make symmetric positive-definite
 
-
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        as_variable_flags=as_variable,
+        with_out=with_out,
+        all_aliases=["cholesky"],
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        rtol=1e-01,
+        input=x,
+        upper=upper,
+    )
+
+
 # svd
 @handle_frontend_test(
     fn_tree="torch.linalg.svd",