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Dependency tracking tutorial #3197

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merged 3 commits into from
Apr 20, 2023
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Dependency tracking tutorial #3197

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18aaee5
Dependency tracking tutorial
ordabayevy Apr 16, 2023
379838a
fix typo
ordabayevy Apr 16, 2023
6df67fd
concenpt -> concept; equals to -> equals
ordabayevy Apr 17, 2023
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concenpt -> concept; equals to -> equals
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@ordabayevy
ordabayevy committed Apr 17, 2023
commit 6df67fd7da24135b9b7a038fcd52b6142a45261b
4 changes: 2 additions & 2 deletions tutorial/source/svi_part_iii.ipynb
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Expand Up @@ -148,7 +148,7 @@
"source": [
"### Aside: Dependency tracking in Pyro\n",
"\n",
"Finally, a word about dependency tracking. Pyro uses the concenpt of provenance for tracking dependency within a stochastic function that includes arbitrary Python code (see reference [5]). In the programming language theory, the provenance of a variable refers to the history of variables or computations that contributed to its value. The simple example below demonstrates how provenance is tracked through PyTorch ops in Pyro, where provenance is a user-defined frozenset of objects:\n",
"Finally, a word about dependency tracking. Pyro uses the concept of provenance for tracking dependency within a stochastic function that includes arbitrary Python code (see reference [5]). In the programming language theory, the provenance of a variable refers to the history of variables or computations that contributed to its value. The simple example below demonstrates how provenance is tracked through PyTorch ops in Pyro, where provenance is a user-defined frozenset of objects:\n",
"\n",
"```python\n",
"from pyro.ops.provenance import get_provenance, track_provenance\n",
Expand All @@ -158,7 +158,7 @@
"c = torch.randn(3) # no provenance information\n",
"\n",
"# For a unary operation, the provenance of the output tensor\n",
"# equals to the provenace of the input tensor\n",
"# equals the provenace of the input tensor\n",
"assert get_provenance(a.exp()) == frozenset({\"a\"})\n",
"# In general, the provenance of the output tensors of any op\n",
"# is the union of provenances of input tensors.\n",
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