synthetic_aia_mia.predictor package¶
Submodules¶
synthetic_aia_mia.predictor.adult module¶
Define structures to manage and interface a fully connected neural network for adult.
- class synthetic_aia_mia.predictor.adult.AdultDataset(data)[source]¶
Bases:
Dataset
Pytorch dataset to handle adult data.
- class synthetic_aia_mia.predictor.adult.AdultNN[source]¶
Bases:
object
Wrapper arround pytorch neural network. Interfare for hyper parameter optimisation using raytune.
- fit(dadata)[source]¶
Train and tune hyper parameters.
- Parameters:
data – Dataset the will be split for training and hyper parameter tuning. Dataset must contain a column called “PINCP” used as training label.
- predict(dadata)[source]¶
Use a trained TabularNN to predict label of dataset.
- Parameters:
dadata (fetch_data.Dataset) – Dataset to evaluate.
- Returns:
Input dataset completed with hard labels, soft labels and loss.
- Return type:
synthetic_aia_mia.predictor.utk module¶
Define structures to manage and interface a fully connected neural network for UTKfaces.
- class synthetic_aia_mia.predictor.utk.CNN(input_size, c, l1, l2, output_size)[source]¶
Bases:
Module
Pytorch convulutional neural network for UTKfaces.
- class synthetic_aia_mia.predictor.utk.UtkDataset(data)[source]¶
Bases:
Dataset
Pytorch dataset to handle adult data.
- class synthetic_aia_mia.predictor.utk.UtkNN[source]¶
Bases:
object
Wrapper arround pytorch neural network. Interfare for hyper parameter optimisation using raytune.