1919from torch .autograd import Function
2020from torch .nn import Module
2121from torch .optim import Optimizer
22- from torch .utils .data import DataLoader , Dataset
22+ from torch .utils .data import Dataset
2323
24- # from monai.transforms.transform import Transform
2524from monai .utils import ensure_tuple , optional_import
2625
2726_nvtx , _ = optional_import ("torch._C._nvtx" , descriptor = "NVTX is not installed. Are you sure you have a CUDA build?" )
@@ -40,7 +39,7 @@ class Range:
4039 methods: (only when used as decorator) the name of a method (or a list of the name of the methods)
4140 to be wrapped by NVTX range.
4241 If None (default), the method(s) will be inferred based on the object's type for various MONAI components,
43- such as Networks, Losses, Optimizers, Functions, Transforms, Datasets, and Dataloaders .
42+ such as Networks, Losses, Functions, Transforms, and Datasets .
4443 Otherwise, it look up predefined methods: "forward", "__call__", "__next__", "__getitem__"
4544 append_method_name: if append the name of the methods to be decorated to the range's name
4645 If None (default), it appends the method's name only if we are annotating more than one method.
@@ -114,15 +113,13 @@ def range_wrapper(*args, **kwargs):
114113
115114 def _get_method (self , obj : Any ) -> tuple :
116115 if isinstance (obj , Module ):
117- method_list = ["forward" , "__call__" ]
116+ method_list = ["forward" ]
118117 elif isinstance (obj , Optimizer ):
119118 method_list = ["step" ]
120119 elif isinstance (obj , Function ):
121120 method_list = ["forward" , "backward" ]
122121 elif isinstance (obj , Dataset ):
123122 method_list = ["__getitem__" ]
124- elif isinstance (obj , DataLoader ):
125- method_list = ["_next_data" ]
126123 else :
127124 default_methods = ["forward" , "__call__" , "__next__" , "__getitem__" ]
128125 method_list = []
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