Comments (2)
You just need to change the types for the environment as it is expecting you to use one of the dtypes it mentions in the index error.
I solved this by modifying the recurrent_net.py, dense_from_coo method in line 37 to this:
mat[torch.tensor(rows, dtype=torch.long), torch.tensor(cols, dtype=torch.long)] = [right hand side stays the same]
I did notice in there is an argument in each of the main.py files in the examples to put in the type (in the decorator). Right now it is set to an integer but might make sense to change it to float there, so as to not do the code modification I mentioned above. I havnt tested this yet though.
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This is the same error also and was solved in a similar manner.
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