diff --git a/predict_links.py b/predict_links.py index d4be50ff7ec2d4d7d814380e10174eb31042e587..8f637a4bc8bc3cb5952c8d1b3e1b0e7cfc00bfff 100644 --- a/predict_links.py +++ b/predict_links.py @@ -1,29 +1,25 @@ from NeuralProofNet.NeuralProofNet import NeuralProofNet from postprocessing import draw_sentence_output -# region data -a_s = ["( 1 ) parmi les huit \" partants \" acquis ou potentiels , MM. Lacombe , Koehler et Laroze ne sont pas membres du PCF ."] -tags_s = ['let', 'dr(0,s,s)', 'let', 'dr(0,dr(0,s,s),np)', 'dr(0,np,n)', 'dr(0,n,n)', 'let', 'n', 'let', 'dl(0,n,n)', - 'dr(0,dl(0,dl(0,n,n),dl(0,n,n)),dl(0,n,n))', 'dl(0,n,n)', 'let', 'dr(0,np,np)', 'np', 'dr(0,dl(0,np,np),np)', - 'np', 'dr(0,dl(0,np,np),np)', 'np', 'dr(0,dl(0,np,s),dl(0,np,s))', 'dr(0,dl(0,np,s),np)', 'dl(1,s,s)', 'np', - 'dr(0,dl(0,np,np),n)', 'n', 'dl(0,s,txt)'] -# endregion - - -# region model -model_tagger = "models/flaubert_super_98_V2_50e.pt" -neuralproofnet = NeuralProofNet(model_tagger) -model = "Output/linker.pt" -neuralproofnet.linker.load_weights(model) -# endregion +if __name__== '__main__': + # region data + a_s = ["( 1 ) parmi les huit \" partants \" acquis ou potentiels , MM. Lacombe , Koehler et Laroze ne sont pas membres du PCF ."] + tags_s = ['let', 'dr(0,s,s)', 'let', 'dr(0,dr(0,s,s),np)', 'dr(0,np,n)', 'dr(0,n,n)', 'let', 'n', 'let', 'dl(0,n,n)', + 'dr(0,dl(0,dl(0,n,n),dl(0,n,n)),dl(0,n,n))', 'dl(0,n,n)', 'let', 'dr(0,np,np)', 'np', 'dr(0,dl(0,np,np),np)', + 'np', 'dr(0,dl(0,np,np),np)', 'np', 'dr(0,dl(0,np,s),dl(0,np,s))', 'dr(0,dl(0,np,s),np)', 'dl(1,s,s)', 'np', + 'dr(0,dl(0,np,np),n)', 'n', 'dl(0,s,txt)'] + # endregion -# region prediction -linker = neuralproofnet.linker -categories, links = linker.predict_without_categories(a_s) -#links = linker.predict_with_categories(a_s, tags_s) -# endregion + # region model + model_tagger = "models/flaubert_super_98_V2_50e.pt" + neuralproofnet = NeuralProofNet(model_tagger) + model = "Output/linker.pt" + neuralproofnet.linker.load_weights(model) + # endregion -if __name__== '__main__': + linker = neuralproofnet.linker + categories, links = linker.predict_without_categories(a_s) + #links = linker.predict_with_categories(a_s, tags_s) idx=0 draw_sentence_output(a_s[idx].split(" "), categories[idx], links[:,idx,:].numpy()) \ No newline at end of file