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)
