import warnings
from functools import wraps
import numpy as np
from delira import get_backends
[docs]def dtype_func(class_object):
"""
Decorator to Check whether the first argument of the decorated function is
of a certain type
Parameters
----------
class_object : Any
type the first function argument should have
Returns
-------
Wrapped Function
Raises
------
AssertionError
First argument of decorated function is not of given type
"""
def instance_checker(func):
@wraps(func)
def func_wrapper(checked_object, *args, **kwargs):
assertion_str = "Argument 1 is not of type %s but of type %s" % \
(class_object.__name__,
checked_object.__class__.__name__)
assert isinstance(checked_object, class_object), assertion_str
return func(checked_object, *args, **kwargs)
return func_wrapper
return instance_checker
[docs]def classtype_func(class_object):
"""
Decorator to Check whether the first argument of the decorated function is
a subclass of a certain type
Parameters
----------
class_object : Any
type the first function argument should be subclassed from
Returns
-------
Wrapped Function
Raises
------
AssertionError
First argument of decorated function is not a subclass of given type
"""
def subclass_checker(func):
@wraps(func)
def func_wrapper(checked_object, *args, **kwargs):
assertion_str = "Argument 1 is not subclass of %s but of type %s" \
% (class_object.__name__, checked_object.__name__)
assert issubclass(checked_object, class_object), assertion_str
return func(checked_object, *args, **kwargs)
return func_wrapper
return subclass_checker
[docs]def make_deprecated(new_func):
"""
Decorator which raises a DeprecationWarning for the decorated object
Parameters
----------
new_func : Any
new function which should be used instead of the decorated one
Returns
-------
Wrapped Function
Raises
------
Deprecation Warning
"""
def deprecation(func):
@wraps(func)
def func_wrapper(*args, **kwargs):
if not isinstance(new_func, str):
new_func_name = new_func.__name__
else:
new_func_name = new_func
if func.__name__ == '__init__':
old_func_name = func.__class__.__name__
else:
old_func_name = func.__name__
warnings.warn(DeprecationWarning("%s is deprecated in favor of %s"
" and will be removed at next "
"release" % (old_func_name,
new_func_name)))
return func(*args, **kwargs)
return func_wrapper
return deprecation
numpy_array_func = dtype_func(np.ndarray)
if "TORCH" in get_backends():
import torch
torch_tensor_func = dtype_func(torch.Tensor)
torch_module_func = dtype_func(torch.nn.Module)