In the Preferences window, click Show In-Game Assistant.
Make sure you have correctly set the game's Documents folder in MacAssistant RT's Preferences: Guide.
To enable IGA, make sure you follow these steps: The IGA has lets you see a player's hidden attributes right inside the game, without the need to switch back and forth between MacAssistant RT17 and the game. They are more powerful and get it right, from my experience SpaCy is a nice tool and quite fast, but not the most precise for NER.The In-Game Assistant (IGA from now on), is a new paid feature, available in the RT17 version. You can try some other models such as the one integrated in Flair: This difficulty of seeing the sentence context as something that would be followed up by a name as well as the fact that "Hagrid" is a kind of unusual name could be the reason. I could imagine that the grammar in last sentence is a bit too "fancy"/literature-like if the model was trained on news or web data and might be throwing the model off. Well, Neural Network Models are basically a black box, so there is no way to know this for sure. RuntimeError: unexpected EOF, expected 32606425 more bytes. Return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)įile "C:\Users\User\AppData\Roaming\Python\Python39\site-packages\torch\serialization.py", line 938, in _legacy_load Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\ResMaskNet_Z_resmasking_dropout1_rot30.pthįile "C:\Users\User\Desktop\DetectFEXFromVideos\main.py", line 7, in ĭetector = Detector(face_model=face_model, landmark_model=landmark_model, au_model=au_model,įile "C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\detector.py", line 227, in _init_įile "C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\emo_detectors\ResMaskNet\resmasknet_test.py", line 748, in _init_įile "C:\Users\User\AppData\Roaming\Python\Python39\site-packages\torch\serialization.py", line 713, in load Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\RF_568.joblib Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\hog_scalar_aus.joblib Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\hog_pca_all_emotio.joblib Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\mobilenet_224_model_best_gdconv_ Using downloaded and verified file: C:\Users\User\AppData\Roaming\Python\Python39\site-packages\feat\resources\mobilenet0.25_Final.pth Please import from 'nilearn.maskers' instead. Importing from 'nilearn.input_data' will be possible at least until release 0.13.0. Net, losses = train(model=net, optimizer=optimizer, E=E, iteration=5000, x=X, y=y)Ĭ:\Users\User\AppData\Roaming\Python\Python39\site-packages\nilearn\input_data\_init_.py:27: FutureWarning: The import path 'nilearn.input_data' is deprecated in version 0.9. Optimizer = optim.RMSprop(net.parameters(), lr=0.01) # 最適化にRMSpropを設定 X2 = nn.functional.relu(self.linear2(x2))ĭef train(model, optimizer, E, iteration, x, y): X2 = nn.functional.relu(self.linear1(x2)) X1 = nn.functional.relu(self.linear2(x1)) X1 = nn.functional.relu(self.linear1(x1))