30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
import matplotlib.pyplot as plt
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import functions as aux
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eff_df = aux.load_pickle("efficiency_data.pkl")
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# bayes_cifar_entropy = aux.load_pickle("bayes_data_cifar_ne.pkl")
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# lenet_mnist_entropy = aux.load_pickle("lenet_data_mnist_ne.pkl")
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entropy_data = aux.load_pickle("entropy_data.pkl")
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bayes_keys = ['conv1.W_mu', 'conv1.W_rho', 'conv1.bias_mu', 'conv1.bias_rho',
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'conv2.W_mu', 'conv2.W_rho', 'conv2.bias_mu', 'conv2.bias_rho',
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'fc1.W_mu', 'fc1.W_rho', 'fc1.bias_mu', 'fc1.bias_rho',
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'fc2.W_mu', 'fc2.W_rho', 'fc2.bias_mu', 'fc2.bias_rho',
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'fc3.W_mu', 'fc3.W_rho', 'fc3.bias_mu', 'fc3.bias_rho']
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lenet_keys = ['conv1.weight', 'conv1.bias', 'conv2.weight', 'conv2.bias',
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'fc1.weight', 'fc1.bias', 'fc2.weight', 'fc2.bias', 'fc3.weight',
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'fc3.bias']
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for size in range(1, 8):
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if size != 8:
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plt.plot(eff_df['CIFAR']['BCNN'][size],
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label='Efficiency size {}'.format(size))
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plt.plot(entropy_data['CIFAR']['BCNN'][size],
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label='Entropy size {}'.format(size))
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# plt.legend(loc='upper right')
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plt.legend(loc='lower right')
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plt.show()
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