RuntimeError: Attempting to deserialize object on a CUDA device

Question

I encounter a RunTimeError while I am trying to run the code in my machine's CPU instead of GPU. The code is originally from this GitHub project - IBD: Interpretable Basis Decomposition for Visual Explanation. This is for a research project. I tried putting the CUDA as false and looked at other solutions on this website.

GPU = False               # running on GPU is highly suggested
CLEAN = False             # set to "True" if you want to clean the temporary large files after generating result
APP = "classification"    # Do not change! mode choide: "classification", "imagecap", "vqa". Currently "imagecap" and "vqa" are not supported.
CATAGORIES = ["object", "part"]   # Do not change! concept categories that are chosen to detect: "object", "part", "scene", "material", "texture", "color"

CAM_THRESHOLD = 0.5                 # the threshold used for CAM visualization
FONT_PATH = "components/font.ttc"   # font file path
FONT_SIZE = 26                      # font size
SEG_RESOLUTION = 7                  # the resolution of cam map
BASIS_NUM = 7                       # In decomposition, this is to decide how many concepts are used to interpret the weight vector of a class.

Here is the error:

Traceback (most recent call last):
  File "test.py", line 22, in <module>
    model = loadmodel()
  File "/home/joshuayun/Desktop/IBD/loader/model_loader.py", line 48, in loadmodel
    checkpoint = torch.load(settings.MODEL_FILE)
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 387, in load
    return _load(f, map_location, pickle_module, **pickle_load_args)
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 574, in _load
    result = unpickler.load()
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 537, in persistent_load
    deserialized_objects[root_key] = restore_location(obj, location)
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 119, in default_restore_location
    result = fn(storage, location)
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 95, in _cuda_deserialize
    device = validate_cuda_device(location)
  File "/home/joshuayun/.local/lib/python3.6/site-packages/torch/serialization.py", line 79, in validate_cuda_device
    raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but 
  torch.cuda.is_available() is False. If you are running on a CPU-only machine, 
  please use torch.load with map_location='cpu' to map your storages to the CPU.

Answer 1

Just giving a smaller answer. To solve this, you could change the parameters of the function named load() in the serialization.py file. This is stored in: ./site-package/torch/serialization.py

Write:

def load(f, map_location='cpu', pickle_module=pickle, **pickle_load_args):

instead of:

def load(f, map_location=None, pickle_module=pickle, **pickle_load_args):

Hope it helps.

Answer 2

If you don't have gpu then use map_location=torch.device('cpu') with load model.load()

my_model = net.load_state_dict(torch.load('classifier.pt', map_location=torch.device('cpu')))

Answer 3

"If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU."

model = torch.load('model/pytorch_resnet50.pth',map_location ='cpu')