{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"!pip install --upgrade Pillow\n!pip install --upgrade mxnet\n!pip install --upgrade autogluon","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from autogluon import ImageClassification as task","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dataset = task.Dataset('train_images', label_file='train.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_dataset = task.Dataset('test_images', train=False, scale_ratio_choice=[0.7, 0.8, 0.875])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# time_limits = 10 * 60 # 10mins\ntime_limits = 10 * 60 * 60 * 3\nclassifier = task.fit(dataset, time_limits=time_limits, verbose=True, epochs=3)\nprint('Top-1 val acc: %.3f' % classifier.results['best_reward'])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"inds, probs, probs_all = classifier.predict(test_dataset)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import autogluon as ag","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"ag.utils.generate_prob_csv(test_dataset, probs_all, custom='./submission.csv')","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}