diff --git a/python/mxnet/test_utils.py b/python/mxnet/test_utils.py index f5d2979c3916..9a24b5fd7d51 100755 --- a/python/mxnet/test_utils.py +++ b/python/mxnet/test_utils.py @@ -1040,8 +1040,10 @@ def check_numeric_gradient(sym, location, aux_states=None, numeric_eps=1e-3, rto The auxiliary states required when generating the executor for the symbol. numeric_eps : float, optional Delta for the finite difference method that approximates the gradient. - check_eps : float, optional - relative error eps used when comparing numeric grad to symbolic grad. + rtol : None or float + The relative threshold. Default threshold will be used if set to ``None``. + atol : None or float + The absolute threshold. Default threshold will be used if set to ``None``. grad_nodes : None or list or tuple or dict, optional Names of the nodes to check gradient on use_forward_train : bool @@ -1182,8 +1184,10 @@ def check_symbolic_forward(sym, location, expected, rtol=1E-4, atol=None, Contains arrays corresponding to exe.outputs. - if type is dict of str to np.ndarray Contains mapping between sym.list_output() and exe.outputs. - check_eps : float, optional - Relative error to check to. + rtol : None or float + The relative threshold. Default threshold will be used if set to ``None``. + atol : None or float + The absolute threshold. Default threshold will be used if set to ``None``. aux_states : list of np.ndarray of dict, optional - if type is list of np.ndarray Contains all the NumPy arrays corresponding to sym.list_auxiliary_states @@ -1270,8 +1274,10 @@ def check_symbolic_backward(sym, location, out_grads, expected, rtol=1e-5, atol= Contains arrays corresponding to exe.grad_arrays - if type is dict of str to np.ndarray Contains mapping between ``sym.list_arguments()`` and exe.outputs. - check_eps: float, optional - Relative error to check to. + rtol : None or float + The relative threshold. Default threshold will be used if set to ``None``. + atol : None or float + The absolute threshold. Default threshold will be used if set to ``None``. aux_states : list of np.ndarray or dict of str to np.ndarray grad_req : str or list of str or dict of str to str, optional Gradient requirements. 'write', 'add' or 'null'.