deep_bottleneck.datasets package¶
Submodules¶
deep_bottleneck.datasets.fashion_mnist module¶
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deep_bottleneck.datasets.fashion_mnist.
load
()[source]¶ Load the Fashion-MNIST dataset
The output follows the following naming convention:
- X is the data
- y is class, with numbers from 0 to 9
- Y is class, but coded as a 10-dim vector with one entry set to 1 at the column index corresponding to the class
Returns: Returns two namedtuples, the first one containing training and the second one containing test data respectively. Both come with fields X, y and Y:
deep_bottleneck.datasets.harmonics module¶
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deep_bottleneck.datasets.harmonics.
import_IB_data_from_mat
(name_ID, nb_dir='')[source]¶ Writes a .npy file to disk containing the harmonics dataset used by Tishby
Parameters: name_ID – Identifier which is going to be part of the output filename Returns: None
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deep_bottleneck.datasets.harmonics.
load
(nb_dir='')[source]¶ Load the Information Bottleneck harmonics dataset
The output follows the following naming convention:
- X is the data
- y is class, with numbers from 0 to 9
- Y is class, but coded as a 10-dim vector with one entry set to 1 at the column index corresponding to the class
Returns: Returns two namedtuples, the first one containing training and the second one containing test data respectively. Both come with fields X, y and Y:
deep_bottleneck.datasets.mnist module¶
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deep_bottleneck.datasets.mnist.
load
()[source]¶ Load the MNIST handwritten digits dataset
The output follows the following naming convention:
- X is the data
- y is class, with numbers from 0 to 9
- Y is class, but coded as a 10-dim vector with one entry set to 1 at the column index corresponding to the class
Returns: Returns two namedtuples, the first one containing training and the second one containing test data respectively. Both come with fields X, y and Y:
deep_bottleneck.datasets.mushroom module¶
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deep_bottleneck.datasets.mushroom.
load
()[source]¶ Load the mushroom dataset.
Mushrooms are to be classified as either edible or poisonous. The output follows the following naming convention:
- X is the data
- y is class, with numbers from 0 to 9
- Y is class, but coded as a 10-dim vector with one entry set to 1 at the column index corresponding to the class
Returns: Returns two namedtuples, the first one containing training and the second one containing test data respectively. Both come with fields X, y and Y: