MCPcopy Create free account
hub / github.com/CompVis/diff2flow / betas_for_alpha_bar

Function betas_for_alpha_bar

diff2flow/ddpm.py:42–58  ·  view source on GitHub ↗

Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of (1-beta) over time from t = [0,1]. :param num_diffusion_timesteps: the number of betas to produce. :param alpha_bar: a lambda that takes an argument t from 0 to 1 and

(num_diffusion_timesteps, alpha_bar, max_beta=0.999)

Source from the content-addressed store, hash-verified

40
41
42def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.999):
43 """
44 Create a beta schedule that discretizes the given alpha_t_bar function,
45 which defines the cumulative product of (1-beta) over time from t = [0,1].
46 :param num_diffusion_timesteps: the number of betas to produce.
47 :param alpha_bar: a lambda that takes an argument t from 0 to 1 and
48 produces the cumulative product of (1-beta) up to that
49 part of the diffusion process.
50 :param max_beta: the maximum beta to use; use values lower than 1 to
51 prevent singularities.
52 """
53 betas = []
54 for i in range(num_diffusion_timesteps):
55 t1 = i / num_diffusion_timesteps
56 t2 = (i + 1) / num_diffusion_timesteps
57 betas.append(min(1 - alpha_bar(t2) / alpha_bar(t1), max_beta))
58 return np.array(betas)
59
60
61def enforce_zero_terminal_snr(betas):

Callers 1

make_beta_scheduleFunction · 0.70

Calls

no outgoing calls

Tested by

no test coverage detected