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cat horse winning ❗

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George Hotz
2022-09-05 16:05:14 -07:00
parent 1043fa067a
commit 16cb4290c4
1 changed files with 11 additions and 6 deletions
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17
examples/stable_diffusion.py
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@@ -583,14 +583,18 @@ if __name__ == "__main__":
e_t = unconditional_latent + unconditional_guidance_scale * (latent - unconditional_latent)
return e_t
alphas = [0.9983, 0.6722, 0.2750, 0.0557]
alphas_prev = [0.9991499781608582, 0.9982960224151611, 0.6721514463424683, 0.27499905228614807]
sigmas = [0,0,0,0]
sqrt_one_minus_alphas = [0.0413, 0.5726, 0.8515, 0.9717]
#alphas = [0.9983, 0.6722, 0.2750, 0.0557]
#alphas_prev = [0.9991499781608582, 0.9982960224151611, 0.6721514463424683, 0.27499905228614807]
alphas = [0.9983, 0.8930, 0.7521, 0.5888, 0.4229, 0.2750, 0.1598, 0.0819, 0.0365, 0.0140]
alphas_prev = [1.0, 0.9983, 0.8930, 0.7521, 0.5888, 0.4229, 0.2750, 0.1598, 0.0819, 0.0365]
def get_x_prev_and_pred_x0(x, e_t, index):
temperature = 1
a_t, a_prev, sigma_t, sqrt_one_minus_at = alphas[index], alphas_prev[index], sigmas[index], sqrt_one_minus_alphas[index]
a_t, a_prev = alphas[index], alphas_prev[index]
sigma_t = 0
sqrt_one_minus_at = math.sqrt(1-a_t)
pred_x0 = (x - sqrt_one_minus_at * e_t) / math.sqrt(a_t)
# direction pointing to x_t
@@ -604,7 +608,8 @@ if __name__ == "__main__":
latent = Tensor.randn(1,4,64,64)
# is this the diffusion?
for index, timestep in tqdm(list(enumerate([1, 251, 501, 751]))[::-1]):
#for index, timestep in tqdm(list(enumerate([1, 251, 501, 751]))[::-1]):
for index, timestep in tqdm(list(enumerate([1, 101, 201, 301, 401, 501, 601, 701, 801, 901]))[::-1]):
print(index, timestep)
e_t = get_model_output(latent, timestep)
#print(e_t.numpy())