20 lines
810 B
Python
20 lines
810 B
Python
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import numpy as np
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def get_2d_projection(activation_batch):
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# TBD: use pytorch batch svd implementation
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activation_batch[np.isnan(activation_batch)] = 0
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projections = []
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for activations in activation_batch:
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reshaped_activations = (activations).reshape(
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activations.shape[0], -1).transpose()
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# Centering before the SVD seems to be important here,
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# Otherwise the image returned is negative
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reshaped_activations = reshaped_activations - \
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reshaped_activations.mean(axis=0)
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U, S, VT = np.linalg.svd(reshaped_activations, full_matrices=True)
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projection = reshaped_activations @ VT[0, :]
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projection = projection.reshape(activations.shape[1:])
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projections.append(projection)
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return np.float32(projections)
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