kirad.constants

kirad.constants

Global constants: sample rate, score ranges, label cutoffs, batch field names.

Stage: utils (used by data, model, loss and metrics). Cutoffs and MAX_SCORE define the ordinal tasks; change them if a new questionnaire or threshold is used.

EXPECTED_SAMPLE_RATE = 16000 module-attribute

DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu') module-attribute

CPU_DEVICE = torch.device('cpu') module-attribute

MAX_FINITE_FLOAT32 = float(np.finfo(np.float32).max) module-attribute

DEFAULT_VAD_MIN_SILENCE_DURATION_MS = 100 module-attribute

DEFAULT_VAD_MIN_SPEECH_DURATION_MS = 250 module-attribute

VAD_PARAMS = {'prompt': {'min_silence_duration_ms': 100, 'min_speech_duration_ms': 250}, 'conversational': {'min_silence_duration_ms': 1000, 'min_speech_duration_ms': 5000}, 'inference': {'min_silence_duration_ms': DEFAULT_VAD_MIN_SILENCE_DURATION_MS, 'min_speech_duration_ms': DEFAULT_VAD_MIN_SPEECH_DURATION_MS}} module-attribute

MAX_SCORE = {'phq9': 27, 'phq2': 6, 'scid': 1, 'gad7': 21, 'gad2': 6} module-attribute

METRIC_TARGET_CUTOFFS = {'depression': (9, 14), 'anxiety': (4, 9, 14), 'real': (0,)} module-attribute

LOSS_TARGET_CUTOFFS = {'real': {'exact2': (0,)}, 'depression': {'LvMH': (METRIC_TARGET_CUTOFFS['depression'][0],), 'LMvH': (METRIC_TARGET_CUTOFFS['depression'][1],), 'LvMvH': METRIC_TARGET_CUTOFFS['depression'], 'exact28': range(MAX_SCORE['phq9'])}, 'anxiety': {'{2,3}_vs_{0,1}': (METRIC_TARGET_CUTOFFS['anxiety'][1],), '{0}_vs_{1}_vs_{2}_vs_{3}': METRIC_TARGET_CUTOFFS['anxiety'], 'exact22': range(MAX_SCORE['gad7'])}} module-attribute

DatasetVersion = Literal['v1', 'v1.0.1', 'v2.0', 'v2.0.1', 'v2.1', 'v2.1.1', 'v2.2', 'v2.2.1', 'v2.3.1', 'v2.4.1', 'v2.5.1', 'v2.6.1', 'v2.7.1', 'v2.8.1', 'v2.9.1', 'v2.9.2', 'v2.9.3', 'v2.9.4', 'v2.9.5', 'v2.10.1', 'v2.10.4', 'v2.11.1', 'v2.11.4'] module-attribute

DataSource = Literal['phonic', 'sonar', 'sonar_general_pop', 'sonar_senior_pop', 'sonar_elderly_and_latino_pop', 'general_pop', 'fda', 'app', 'all'] module-attribute

DatasetSplit = Literal['train', 'val', 'test', 'all'] module-attribute

FeatureStoreBucket = Literal['raw', 'resampled', 'resampled_and_cut_audio_with_conversational_vad_params', 'resampled_and_trimmed_audio_with_conversational_vad_params', 'resampled_and_cut_audio_with_prompt_vad_params', 'resampled_and_trimmed_audio_with_prompt_vad_params'] module-attribute

DATASET_VERSION_METADATA = {'v1': {'n_folds': 5, 'uri': None}, 'v1.0.1': {'n_folds': 5, 'uri': None}, 'v2.0': {'n_folds': 5, 'uri': None}, 'v2.0.1': {'n_folds': 5, 'uri': None}, 'v2.1': {'n_folds': 5, 'uri': None}, 'v2.1.1': {'n_folds': 5, 'uri': None}, 'v2.2': {'n_folds': 5, 'uri': None}, 'v2.2.1': {'n_folds': 5, 'uri': None}, 'v2.3.1': {'n_folds': 5, 'uri': None}, 'v2.4.1': {'n_folds': 5, 'uri': None}, 'v2.5.1': {'n_folds': 5, 'uri': None}, 'v2.6.1': {'n_folds': 5, 'uri': None}, 'v2.7.1': {'n_folds': 5, 'uri': None}, 'v2.8.1': {'n_folds': 5, 'uri': None}, 'v2.9.1': {'n_folds': 5, 'uri': None}, 'v2.9.2': {'n_folds': 5, 'uri': None}, 'v2.9.3': {'n_folds': 5, 'uri': None}, 'v2.9.4': {'n_folds': 5, 'uri': None}, 'v2.9.5': {'n_folds': 5, 'uri': None}, 'v2.10.1': {'n_folds': 5, 'uri': None}, 'v2.10.4': {'n_folds': 5, 'uri': None}, 'v2.11.1': {'n_folds': 5, 'uri': None}, 'v2.11.4': {'n_folds': 5, 'uri': None}} module-attribute

FEATURE_STORE_URI = None module-attribute

RAW_AUDIO_URI = None module-attribute

CACHE_DIR = Path.home() / '.kintsugi' module-attribute

AUDIO_DIR = CACHE_DIR / 'audio' module-attribute

METADATA_DIR = CACHE_DIR / 'metadata' module-attribute

USER_CACHE_DIR_KINTSUGI = Path.home() / '.cache' / 'kintsugi' module-attribute

IDEAL_LOGMEL_ENERGIES = np.array([0.34912264, 0.58558977, 0.7912451, 0.92767584, 0.98273695, 0.98439455, 0.9603633, 0.93906444, 0.9366281, 0.93200225, 0.916437, 0.8928787, 0.8637211, 0.83265126, 0.79977655, 0.7778334, 0.7561299, 0.72997606, 0.70391226, 0.6800474, 0.65755, 0.63536274, 0.61355984, 0.5923383, 0.5720056, 0.55244887, 0.53684795, 0.5221597, 0.5098636, 0.49923953, 0.48908615, 0.47840047, 0.46758702, 0.47343993, 0.46268672, 0.4475126, 0.46747103, 0.45131385, 0.4635319, 0.44889897, 0.45491976, 0.4373785, 0.43154317, 0.42194438, 0.41158468, 0.40096927, 0.3933149, 0.38795966, 0.38441542, 0.38454026, 0.3815766, 0.3768835, 0.3719921, 0.3654539, 0.35399568, 0.3425986, 0.32823247, 0.31404305, 0.30564603, 0.29617435, 0.29273877, 0.28560263, 0.27459458, 0.26876706, 0.25825337, 0.24759005, 0.24090728, 0.2344712, 0.22529823, 0.20880115, 0.193578, 0.18290243, 0.17621627, 0.17087021, 0.16641389, 0.15932252, 0.14312662, 0.11790597, 0.08030523, 0.03747071], dtype=np.float32) module-attribute

DatasetFields

Key names of a batch dict: uuid, features, label..primary/kd, length, loss.

Source code in kirad/constants.py

class DatasetFields:
    """Key names of a batch dict: uuid, features, label.<task>.primary/kd, length, loss."""

    UUID = "uuid"
    FEATURES = "features"
    LABEL = "label"
    LENGTH = "length"
    LOSS = "loss"

    class LabelFields:
        """Sub-keys under label.<task>: primary (label column) and kd (scores_<task> column)."""

        PRIMARY = "primary"
        KD = "kd"

UUID = 'uuid' class-attribute instance-attribute

FEATURES = 'features' class-attribute instance-attribute

LABEL = 'label' class-attribute instance-attribute

LENGTH = 'length' class-attribute instance-attribute

LOSS = 'loss' class-attribute instance-attribute

LabelFields

Sub-keys under label.: primary (label column) and kd (scores_ column).

Source code in kirad/constants.py

class LabelFields:
    """Sub-keys under label.<task>: primary (label column) and kd (scores_<task> column)."""

    PRIMARY = "primary"
    KD = "kd"

PRIMARY = 'primary' class-attribute instance-attribute

KD = 'kd' class-attribute instance-attribute