Cast rounded input replacement to original discrete dtype in sample_smc #5887
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ricardoV94
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ricardoV94
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Jun 13, 2022
| float_var = at.TensorType("floatX", in_var.broadcastable)(in_var.name) | ||
| new_in_vars.append(float_var) | ||
| replace_int_input[in_var] = at.round(float_var) | ||
| replace_int_input[in_var] = at.round(float_var).astype(in_var.dtype) |
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We only had a test for unobserved bernoulli, but its logp does not care if the value is discrete or not. The categorical logp on the other hand requires it to be discrete as it does some indexing operation.
Codecov Report
@@ Coverage Diff @@
## main #5887 +/- ##
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Coverage 89.48% 89.48%
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Files 73 73
Lines 13228 13228
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Hits 11837 11837
Misses 1391 1391
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Solves the problem described in https://discourse.pymc.io/t/model-works-with-nuts-prior-predictive-but-not-with-smc/9585/4