crop_yield_train_c3d.py [88:115]:
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                                       X_dir=X_dir,
                                       X_train_indices=(train_indices[0], train_indices[-1]),
                                       y_train=y_train,
                                       X_valid_indices=(valid_indices[0], valid_indices[-1]),
                                       y_valid=y_valid,
                                       X_test_indices=(test_indices[0], test_indices[-1]),
                                       y_test=y_test,
                                       n_tsteps=n_tsteps,
                                       max_index=max_index,
                                       n_triplets_per_file=n_triplets_per_file,
                                       patience=patience,
                                       optimizer=optimizer,
                                       batch_size=batch_size,
                                       test_batch_size=test_batch_size,
                                       n_epochs=epochs,
                                       out_dir=param_model_out_dir,
                                       year=year,
                                       exp_idx=i,
                                       log_file='{}/{}.txt'.format(log_out_dir, params))

            test_prediction, rmse, r2, corr = eval_test(X_dir,
                                                        X_test_indices=(test_indices[0], test_indices[-1]),
                                                        y_test=y_test,
                                                        n_tsteps=n_tsteps,
                                                        max_index=max_index,
                                                        n_triplets_per_file=n_triplets_per_file,
                                                        batch_size=test_batch_size,
                                                        model_dir=param_model_out_dir,
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crop_yield_train_cnn_lstm.py [93:120]:
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                                            X_dir=X_dir,
                                            X_train_indices=(train_indices[0], train_indices[-1]),
                                            y_train=y_train,
                                            X_valid_indices=(valid_indices[0], valid_indices[-1]),
                                            y_valid=y_valid,
                                            X_test_indices=(test_indices[0], test_indices[-1]),
                                            y_test=y_test,
                                            n_tsteps=n_tsteps,
                                            max_index=max_index,
                                            n_triplets_per_file=n_triplets_per_file,
                                            patience=patience,
                                            optimizer=optimizer,
                                            batch_size=batch_size,
                                            test_batch_size=test_batch_size,
                                            n_epochs=epochs,
                                            out_dir=param_model_out_dir,
                                            year=year,
                                            exp_idx=i,
                                            log_file='{}/{}.txt'.format(log_out_dir, params))

            test_prediction, rmse, r2, corr = eval_test(X_dir,
                                                        X_test_indices=(test_indices[0], test_indices[-1]),
                                                        y_test=y_test,
                                                        n_tsteps=n_tsteps,
                                                        max_index=max_index,
                                                        n_triplets_per_file=n_triplets_per_file,
                                                        batch_size=test_batch_size,
                                                        model_dir=param_model_out_dir,
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