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make subtb efficient #3

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make subtb efficient #3

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14 changes: 6 additions & 8 deletions energy_sampling/gflownet_losses.py
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Original file line number Diff line number Diff line change
Expand Up @@ -68,18 +68,16 @@ def subtb(initial_state, gfn, log_reward_fn, coef_matrix, exploration_std=None,

diff_logp = log_pfs - log_pbs
diff_logp_padded = torch.cat(
(torch.zeros((diff_logp.shape[0], 1)).to(diff_logp),
diff_logp.cumsum(dim=-1)),
dim=1)
(torch.zeros((diff_logp.shape[0], 1)).to(diff_logp), diff_logp.cumsum(dim=-1)),
dim=1,
)
A1 = diff_logp_padded.unsqueeze(1) - diff_logp_padded.unsqueeze(2)
A2 = log_fs[:, :, None] - log_fs[:, None, :] + A1
A2 = A2 ** 2
loss = torch.triu((A2 ** 2) * coef_matrix.unsqueeze(0), diagonal=1).sum((1, 2))
if return_exp:
return torch.stack([torch.triu(A2[i] * coef_matrix, diagonal=1).sum() for i in range(A2.shape[0])]).sum(), states, log_pfs, log_pbs, log_fs[:, -1]
return 0.5 * loss.mean(), states, log_pfs, log_pbs, log_fs[:, -1]
else:

return torch.stack([torch.triu(A2[i] * coef_matrix, diagonal=1).sum() for i in range(A2.shape[0])]).sum()

return 0.5 * loss.mean()


def bwd_mle(samples, gfn, log_reward_fn, exploration_std=None):
Expand Down