Started implementation of random variables with PyTorch backend [WIP] #1075
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #1075 +/- ##
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Coverage 82.10% 82.10%
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Files 183 184 +1
Lines 47924 47970 +46
Branches 8632 8636 +4
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+ Hits 39348 39386 +38
- Misses 6410 6416 +6
- Partials 2166 2168 +2
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Ch0ronomato
reviewed
Nov 10, 2024
| static_shape = rv.type.shape | ||
| batch_ndim = op.batch_ndim(node) | ||
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| # Try to pass static size directly to JAX |
| # XXX replace | ||
| state_ = rng["pytorch_state"] | ||
| gen = torch.Generator().set_state(state_) | ||
| sample = torch.bernoulli(torch.expand_copy(p, size), generator=gen) |
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I actually don't mind this approach! Torch has a lot of wrapping and abstraction on top of it's random generation, so if we just keep a little bit of state around it feels a bit simpler.
| thunk_inputs = [] | ||
| for n in self.fgraph.inputs: | ||
| sinput = storage_map[n] | ||
| if isinstance(sinput[0], RandomState | Generator): | ||
| new_value = pytorch_typify( | ||
| sinput[0], dtype=getattr(sinput[0], "dtype", None) |
ricardoV94
reviewed
Nov 11, 2024
| static_shape = rv.type.shape | ||
| batch_ndim = op.batch_ndim(node) | ||
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| # Try to pass static size directly to JAX |
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This static size is a JAX limitation that shouldn't exist in PyTorch
ricardoV94
reviewed
Nov 11, 2024
| state_ = rng["pytorch_state"] | ||
| gen = torch.Generator().set_state(state_) | ||
| sample = torch.bernoulli(torch.expand_copy(p, size), generator=gen) | ||
| return (rng, sample) |
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It should return a new state, otherwise the draws will be the same the next time it's evaluated
ricardoV94
reviewed
Nov 11, 2024
| # XXX replace | ||
| state_ = rng["pytorch_state"] | ||
| gen = torch.Generator().set_state(state_) | ||
| sample = torch.bernoulli(torch.expand_copy(p, size), generator=gen) |
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Shouldn't it jut broadcast?, why copy?
Suggested change
| sample = torch.bernoulli(torch.expand_copy(p, size), generator=gen) | |
| sample = torch.bernoulli(torch.expand_copy(p, size), generator=gen) |
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📚 Documentation preview 📚: https://pytensor--1075.org.readthedocs.build/en/1075/