Coverage for addmo/util/definitions.py: 60%

1import os 

2import glob 

3import json 

4from addmo.util.load_save_utils import create_or_clean_directory, root_dir 

5from addmo.s2_data_tuning.config.data_tuning_config import DataTuningFixedConfig 

6from addmo.s3_model_tuning.config.model_tuning_config import ModelTuningExperimentConfig 

7from addmo.s1_data_tuning_auto.config.data_tuning_auto_config import DataTuningAutoSetup 

8 

9 

10def raw_data_path(path: str = None): 

11 """ 

12 Returns the path to the raw input data file, using a default if none is provided. 

13 """ 

14 if path is None: 

15 # Use the default path 

16 return os.path.join(root_dir(), 'addmo_examples', 'raw_input_data', 'InputData.xlsx') 

17 elif os.path.isabs(path): 

18 # If the provided path is absolute, return it as is 

19 return path 

20 else: 

21 # If the provided path is relative, join it with the 'raw_input_data' directory 

22 return os.path.join(root_dir(), 'raw_input_data', path) 

23 

24 

25def results_dir(): 

26 """ 

27 Returns the path to the results directory. 

28 """ 

29 return os.path.join(root_dir(), 'addmo_examples', 'results') 

30 

31 

32def results_dir_wandb(): 

33 """ 

34 Returns the path to the results directory for wandb logging. 

35 """ 

36 return os.path.join(results_dir(), 'wandb') 

37 

38 

39def results_dir_data_tuning(config: DataTuningFixedConfig, user_input='y'): 

40 """ 

41 Returns the path to the results directory for data tuning based on config. 

42 """ 

43 path = os.path.join(results_dir(), config.name_of_raw_data, config.name_of_tuning) 

44 return create_or_clean_directory(path, user_input) 

45 

46 

47def results_dir_model_tuning(config: ModelTuningExperimentConfig,user_input='y', ): 

48 """ 

49 Returns the path to the results directory for model tuning based on config. 

50 """ 

51 path = os.path.join(results_dir(), config.name_of_raw_data, 

52 config.name_of_data_tuning_experiment, config.name_of_model_tuning_experiment) 

53 return create_or_clean_directory(path, user_input) 

54 

55 

56def ed_use_case_dir(): 

57 """ 

58 Returns the path to the use case directory. 

59 """ 

60 return os.path.join(root_dir(), 'aixtra_use_case') 

61 

62def return_results_dir_model_tuning( name_of_raw_data='test_raw_data',name_of_data_tuning_experiment='test_data_tuning', name_of_model_tuning_experiment='test_model_tuning'): 

63 """ 

64 Returns the path to the results directory for completed model tuning . 

65 """ 

66 path = os.path.join(results_dir(), name_of_raw_data, name_of_data_tuning_experiment, name_of_model_tuning_experiment) 

67 return path 

68 

69def return_best_model(dir, extensions=(".joblib", ".keras")): 

70 """ 

71 Returns the path to the model based on the directory path. 

72 """ 

73 for fname in sorted(os.listdir(dir)): 

74 if fname.endswith(extensions): 

75 full_path = os.path.join(dir, fname) 

76 if os.path.isfile(full_path): 

77 return full_path 

78 

79 raise FileNotFoundError( 

80 f"No model file with extensions {extensions} found in {dir!r}" 

81 ) 

82 

83def results_dir_data_tuning_auto(name_of_raw_data='test_raw_data', name_of_data_tuning_experiment='data_tuning_experiment_auto'): 

84 """ 

85 Returns the directory of tuned data based on config's name of raw_data. 

86 """ 

87 if name_of_raw_data is None: 

88 config = DataTuningAutoSetup() 

89 name_of_raw_data = config.name_of_raw_data 

90 dir = os.path.join(results_dir(), name_of_raw_data, name_of_data_tuning_experiment) 

91 return dir 

92 

93def results_dir_data_tuning_fixed(name_of_raw_data='test_raw_data'): 

94 """ 

95 Returns the path to the folder in results directory of tuned data based on config. 

96 """ 

97 if name_of_raw_data is None: 

98 config = DataTuningFixedConfig() 

99 name_of_raw_data = config.name_of_raw_data 

100 dir = os.path.join(results_dir(), name_of_raw_data, 'data_tuning_experiment_fixed') 

101 return dir 

102 

103 

104def results_model_streamlit_testing(name_tuning_exp, user_input='y'): 

105 """ 

106 Returns the path to the results directory for model tuning based on config. 

107 """ 

108 path = os.path.join(results_dir(), 'model_streamlit_test', name_tuning_exp) 

109 return create_or_clean_directory(path, user_input) 

110 

111 

112def load_model_config(dir): 

113 """ 

114 Returns the path to the model configuration file. 

115 """ 

116 config_path = os.path.join(dir, "config.json") 

117 with open(config_path, 'r') as f: 

118 model_config = json.load(f) 

119 return model_config