pytorch: can't load CNN model and do prediction TypeError: 'collections.OrderedDict' object is not callable
Solution 1
Indeed, you are loading a state_dict rather than the model itself.
Saving the model is as follows:
torch.save(model.state_dict(), 'model_state.pth')
Whereas to load the model state you first need to init the model and then load the state
model = Model()
model.load_state_dict(torch.load('model_state.pth'))
If you trained your model on GPU but would like to load the model on a laptop which doesn't have CUDA, then you would need to add one more argument
model.load_state_dict(torch.load('model_state.pth', map_location='cpu'))
Solution 2
I'm pretty sure score_detector.pkl
is actually a state_dict and not the model itself. You will need to instantiate the model first and then load the state_dict, so your first line should be replaced by something like this:
cnn = MyModel()
cnn.load_state_dict("/usr/prakt/w153/Desktop/score_detector.pkl")
and then the rest should work. See this link for more information.
Yingqiang Gao
Updated on June 24, 2022Comments
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Yingqiang Gao almost 2 years
I trained a CNN model using MNIST dataset and now want to predict a classification of the image, which contains a number 3.
But when I tried to use this CNN to predict, pytorch gives me this error:
TypeError: 'collections.OrderedDict' object is not callable
And here's what I write:
cnn = torch.load("/usr/prakt/w153/Desktop/score_detector.pkl") img = scipy.ndimage.imread("/usr/prakt/w153/Desktop/resize_num_three.png") test_x = Variable(torch.unsqueeze(torch.FloatTensor(img), dim=1), volatile=True).type(torch.FloatTensor).cuda() test_output, last_layer = cnn(test_x) pred = torch.max(test_output, 1)[1].cuda().data.squeeze() print(pred)
here's some explaination:
img
is the to be predicted image with size 28*28score_detector.pkl
is the trained CNN modelany help will be appreciated!