Commit 9077c14f authored by Nishtha Jain's avatar Nishtha Jain
Browse files

print instance arguments

parent dd07b896
Make sure these directories are present
`mkdir datasets models plots_and_graphs predicted_datasets word_embeddings`
to add pretrained word embedding models, write in terminal:
......@@ -13,11 +14,17 @@ to get debiased version of pretrained word2Vec embedding, use the link: <br /> h
install requirements.txt - constants - contains constants - contains evaluation metrics - contains model descriptions and training and prediction modules - contains embeddings and preprocessing tasks - contains data extraction and sampling tasks - contains the runnable flow of the project
......@@ -9,7 +9,8 @@ from joblib import dump, load
def main(load_data_from_saved, embedding_train, model_train, predict, evaluate, class_group, sampling, embedding, model, test_size, masking):
print({'load_data_from_saved':load_data_from_saved, 'embedding_train':embedding_train, 'model_train':model_train, 'predict':predict, 'evaluate':evaluate, 'class_group':class_group, 'sampling':sampling, 'embedding':embedding, 'model':model, 'test_size':test_size, 'masking':masking})
print("\nprocessing train.main ...")
data = pd.DataFrame(load_data(class_group=class_group, from_saved=load_data_from_saved))
......@@ -67,11 +68,11 @@ if __name__ == "__main__":
main(load_data_from_saved = True,
embedding_train = False,
model_train = False,
predict = True,
predict = False,
evaluate = False,
class_group = 'trial',
sampling = 'balanced',
embedding = ''self_w2v'',
embedding = 'self_w2v',
model = 'svm',
test_size = 0.2,
masking = True)
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