main.py
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	import torch
	import numpy as np
	import random
	import matplotlib
	matplotlib.use('TkAgg')
	import matplotlib.pyplot as plt

	# own package
	from weightmatrices.utils import utils
	from weightmatrices.algos import pca

	n_h = 100 # replace by list of n_hs

	################################################################################

	data_loader = utils.load_data()

	W = pca.get_weightmatrices_pca(data_loader, n_h)

	plt.imshow(W[random.sample(range(0, n_h), 1)[0], :].reshape(28, 28), cmap = 'gray')
	plt.show()

	################################################################################

	import os
	if not os.path.exists('./results'):
	os.mkdir('./results')

	np.save('./results/pca_test.npy', W)

	# jump to interactive mode
	import code
	code.interact(local=locals())