# cupy.testing.numpy_cupy_array_max_ulp¶

cupy.testing.numpy_cupy_array_max_ulp(maxulp=1, dtype=None, name='xp', type_check=True, accept_error=False, sp_name=None, scipy_name=None)[source]

Decorator that checks results of NumPy and CuPy ones are equal w.r.t. ulp.

Parameters: maxulp (int) – The maximum number of units in the last place that elements of resulting two arrays can differ. dtype (numpy.dtype) – Data-type to convert the resulting two array to if given. name (str) – Argument name whose value is either numpy or cupy module. type_check (bool) – If True, consistency of dtype is also checked. accept_error (bool, Exception or tuple of Exception) – Specify acceptable errors. When both NumPy test and CuPy test raises the same type of errors, and the type of the errors is specified with this argument, the errors are ignored and not raised. If it is True all error types are acceptable. If it is False no error is acceptable. sp_name (str or None) – Argument name whose value is either scipy.sparse or cupyx.scipy.sparse module. If None, no argument is given for the modules. scipy_name (str or None) – Argument name whose value is either scipy or cupyx.scipy module. If None, no argument is given for the modules.

Decorated test fixture is required to return the same arrays in the sense of assert_array_max_ulp() (except the type of array module) even if xp is numpy or cupy.