Hi everyone,
I have a problem wih loading my model to continue the training.
I have a minimalistic example:
for epoch in range(...):
    train model
for k, data in enumerate(train_loader):
    preparing inputs
    output = model(input1.float(), input2.float())
    torch.save(model,'output/model_saved')
    break
model2 = torch.load('output/model_saved')
print('Get the parameters states values')
for key in model2.state_dict().keys():
    print(torch.equal(model.state_dict()[key],model2.state_dict()[key]))

print('Compare outputs')
print(torch.equal(output,model2(input1.float(), input2.float())))

The loaded state are the same.
The comparison of the outputs are different.
How can the outputs between model and model2 be  different if the model parameters and the inputs are the same?