feature(zp): add dreamerv3 algorithm #652
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Codecov Report
@@ Coverage Diff @@
## main #652 +/- ##
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+ Coverage 82.06% 82.47% +0.41%
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Files 586 586
Lines 47515 48047 +532
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+ Hits 38991 39626 +635
+ Misses 8524 8421 -103
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ding/world_model/utils.py
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| return -loss | ||
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| class ContDist: |
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polish all the class name of distributions we implemented, unify their name format
ding/world_model/utils.py
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| class SymlogDist(): | ||
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| def __init__(self, mode, dist='mse', agg='sum', tol=1e-8, dim_to_reduce=[-1, -2, -3]): |
ding/world_model/utils.py
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| def mode(self): | ||
| _mode = torch.round(self._dist.mean) | ||
| return _mode.detach() + self._dist.mean - self._dist.mean.detach() |
ding/model/common/encoder.py
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| class Conv2dSame(torch.nn.Conv2d): | ||
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| def calc_same_pad(self, i, k, s, d): | ||
| return max((math.ceil(i / s) - 1) * s + (k - 1) * d + 1 - i, 0) |
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Add data type for i,k,s,d
Add function notation
ding/model/common/encoder.py
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| class DreamerLayerNorm(nn.Module): | ||
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| def __init__(self, ch, eps=1e-03): | ||
| super(DreamerLayerNorm, self).__init__() |
| import torch | ||
| from torch import nn | ||
| import torch.nn.functional as F | ||
| from torch import distributions as torchd |
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please do not use torchd as short module name. It's not a standard coding format.
It's better to from torch.distributions import XXXXX.
Import only what you need.
ding/world_model/utils.py
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| class TwoHotDistSymlog(): | ||
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| def __init__(self, logits=None, low=-20.0, high=20.0, device='cpu'): |
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device is set by default. It should not be explicitly set by some argument.
PaParaZz1
changed the title
Description
cartpole_balance:
walker_walk:
Related Issue
#669
TODO
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