from sklearn.pipeline import Pipeline from sklearn.preprocessing import OneHotEncoder, StandardScaler from bedrock_client.bedrock.analyzer import ModelTypes from bedrock_client.bedrock.analyzer.model_analyzer import ModelAnalyzer from bedrock_client.bedrock.api import BedrockApi from bedrock_client.bedrock.metrics.collector import ( BaselineMetricCollector, FeatureHistogramCollector, InferenceHistogramCollector) from bedrock_client.bedrock.metrics.encoder import MetricEncoder env = Env() OUTPUT_MODEL_PATH = env("OUTPUT_MODEL_PATH") TRAIN_DATA_PATH = env("TRAIN_DATA_PATH") TEST_DATA_PATH = env("TEST_DATA_PATH") C = env.float("C") CONFIG_FAI = { "large_rings": { "privileged_attribute_values": [1], # privileged group name corresponding to values=[1] "privileged_group_name": "Large", "unprivileged_attribute_values": [0], # unprivileged group name corresponding to values=[0] "unprivileged_group_name": "Small", } } def load_dataset(filepath: str, target: str) -> Tuple[pd.core.frame.DataFrame, np.ndarray]:
# "tomato": 10 classes of tomato # "11": 11 classes of different leaf # "MNIST": MNIST dataset # "Plant_Pathtology": Plant_Pathtology dataset with 21 classes # "4": 4 classes # """ 'DATA_DIR': env('DATA_DIR', 'color'), 'EPOCHS': env.int('EPOCHS', 100), 'EMBEDDING_SIZE': env.int('EMBEDDING_SIZE', 50), 'BATCH_SIZE': env.int('BATCH_SIZE', 32), 'INPUT_SHAPE': env.int('INPUT_SHAPE', 50), 'STEP': env.int('STEP', 20), 'MODEL_VERSION': env.int('MODEL_VERSION', 1), 'MODEL_EXPORT_DIR': env('MODEL_EXPORT_DIR', "data/face"), 'JSON_PREDICT': env('JSON_PREDICT', 'data/data.json'), 'GPU_MEMORY_LIMIT': env.float('GPU_MEMORY_LIMIT', 0.7), 'MODEL_SAVE': env('MODEL_SAVE', 'data/models/'), 'PAIR': env.int('PAIR', 10) } class Settings(): def __init__(self, default_settings): self.__load_default_settings(default_settings) def __load_default_settings(self, default_settings): for setting_name, setting_value in six.iteritems(default_settings): setattr(self, setting_name, setting_value) def __getattribute__(self, attr): return super(Settings, self).__getattribute__(attr)