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| import os | |
| REPO_PATH = '/'.join(os.path.abspath(__file__).split('/')[:-3]) + '/' | |
| # QUADRUPLETS_PATH = REPO_PATH + 'checkpoints/cocktail_representation/quadruplets.pickle' | |
| INGREDIENTS_LIST_PATH = REPO_PATH + 'checkpoints/cocktail_representation/ingredient_list.csv' | |
| # ING_MATCH_SCORE_Q_PATH = REPO_PATH + 'checkpoints/cocktail_representation/ingredient_match_score_q.txt' | |
| # ING_MATCH_SCORE_COUNT_PATH = REPO_PATH + 'checkpoints/cocktail_representation/ingredient_match_score_count.txt' | |
| # COCKTAIL_DATA_FOLDER_PATH = REPO_PATH + 'checkpoints/cocktail_representation/' | |
| COCKTAILS_CSV_DATA = REPO_PATH + 'checkpoints/cocktail_representation/cocktails_data.csv' | |
| # COCKTAILS_PKL_DATA = REPO_PATH + 'checkpoints/cocktail_representation/cocktails_data.pkl' | |
| # COCKTAILS_URL_DATA = REPO_PATH + 'checkpoints/cocktail_representation/cocktails_names_urls.pkl' | |
| EXPERIMENT_PATH = REPO_PATH + 'experiments/cocktails/representation_learning/' | |
| # ANALYSIS_PATH = REPO_PATH + 'experiments/cocktails/representation_analysis/' | |
| # REPRESENTATIONS_PATH = REPO_PATH + 'experiments/cocktails/learned_representations/' | |
| FULL_COCKTAIL_REP_PATH = REPO_PATH + "/checkpoints/cocktail_representation/handcoded_reps/cocktail_handcoded_reps_minmax_norm-1_1_dim13_customkeys.txt" | |
| RECIPE2FEATURES_PATH = REPO_PATH + "/checkpoints/cocktail_representation/" # get this by running run_without_vae | |
| COCKTAIL_REP_CHKPT_PATH = REPO_PATH + "/checkpoints/cocktail_representation/handcoded_reps/" | |
| # FULL_COCKTAIL_REP_PATH = REPO_PATH + "experiments/cocktails/representation_analysis/affective_mapping/clustered_representations/all_cocktail_reps_norm-1_1_custom_keys_dim13.txt' | |
| COCKTAIL_NN_PATH = REPO_PATH + "/checkpoints/cocktail_representation/handcoded_reps/nn_model.pickle" |