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import numpy as np
def fid(reals, fakes):
"""FID score calculation.
Args:
reals (numpy.array): Real images.
fakes (numpy.array): Fake images.
"""
print(reals.shape, fakes.shape)
reals = reals.reshape(reals.shape[0], -1)
fakes = fakes.reshape(fakes.shape[0], -1)
mu_real = np.mean(reals, axis=0)
mu_fake = np.mean(fakes, axis=0)
sigma_real = np.cov(reals, rowvar=False)
sigma_fake = np.cov(fakes, rowvar=False)
diff = mu_real - mu_fake
covmean = np.dot(sigma_real, sigma_fake.T)
covmean = np.sqrt(covmean * (covmean > 0))
print(np.trace(covmean))
return diff @ diff + np.trace(sigma_real) + np.trace(sigma_fake) - 2 * np.trace(covmean)
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