Comments (3)
Hi! In the train_inst2vec script, the embedding matrix is one of the results of training: https://github.com/spcl/ncc/blob/master/train_inst2vec.py#L60
Evaluation on new codes just means to parse the LLVM IR files to their token representation, see function that converts a folder of LLVM IR files here: https://github.com/spcl/ncc/blob/master/task_utils.py#L262
Then, you could evaluate this folder with the trained (or pretrained) inst2vec embedding matrix (by multiplying the matrix with each token, you get the respective embeddings).
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Closing this due to inactivity. Hope I could help!
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Could you please help me write a piece of code? I have generated a folder named "folder_seq" using the code in task_utils.py, but I still don't know how to multiply them to get the code vectors.
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Related Issues (20)
- [train_task_classifyapp.py] GPU memory grows unlimitedly HOT 9
- loss and acc have large differences even though train and valid are set totally same HOT 4
- llvm ir of linux kernel HOT 1
- test
- Asm inline call handling HOT 1
- question about predict value p at train_task_classifyapp.py line 417 HOT 2
- Train task classifyapp on same data as for training the embedding HOT 2
- ValueError: GraphDef cannot be larger than 2GB. HOT 1
- Bug of Regular Express matching Report For Preprocessing LLVM IR HOT 1
- 'MultiDiGraph' object has no attribute 'node' HOT 3
- Confusion in inst2vec_preprocess.py when reading code HOT 6
- The original source code of the datasets HOT 3
- Expected combineable dataset HOT 1
- for classifyapp, vocubalary dictionary is not present. HOT 1
- the links to all the datasets did not work. HOT 3
- dictionary_pickle not available HOT 3
- [inst2vec_evaluate.py] IndexError : list index out of range in analogies HOT 1
- The link to the dataset is not working HOT 2
- Dataset download failed HOT 2
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