hongshaorou/dreamerv3-torch
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erased unnecessary code

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NM512 2023-04-27 07:42:08 +09:00
parent 432a359bcf
commit 2a8b44eb0c
1 changed files with 1 additions and 10 deletions
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11
models.py
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@ -366,11 +366,6 @@ class ImagBehavior(nn.Module):
return imag_feat, imag_state, imag_action, weights, metrics return imag_feat, imag_state, imag_action, weights, metrics
def _imagine(self, start, policy, horizon, repeats=None): def _imagine(self, start, policy, horizon, repeats=None):
# horizon: 15
# start = dict(stoch, deter, logit)
# start["stoch"] (16, 63, 32, 32)
# start["deter"] (16, 63, 512)
# start["logit"] (16, 63, 32, 32)
dynamics = self._world_model.dynamics dynamics = self._world_model.dynamics
if repeats: if repeats:
raise NotImplemented("repeats is not implemented in this version") raise NotImplemented("repeats is not implemented in this version")
@ -385,12 +380,8 @@ class ImagBehavior(nn.Module):
succ = dynamics.img_step(state, action, sample=self._config.imag_sample) succ = dynamics.img_step(state, action, sample=self._config.imag_sample)
return succ, feat, action return succ, feat, action
feat = 0 * dynamics.get_feat(start)
action = policy(feat).mode()
# Is this action deterministic or stochastic?
# action = policy(feat).sample()
succ, feats, actions = tools.static_scan( succ, feats, actions = tools.static_scan(
step, [torch.arange(horizon)], (start, feat, action) step, [torch.arange(horizon)], (start, None, None)
) )
states = {k: torch.cat([start[k][None], v[:-1]], 0) for k, v in succ.items()} states = {k: torch.cat([start[k][None], v[:-1]], 0) for k, v in succ.items()}
if repeats: if repeats: