Track specific Elemwise Ops in logprob rewrites

pymc/logprob/censoring.py

@@ -44,7 +44,7 @@
 from pytensor.graph.rewriting.basic import node_rewriter
 from pytensor.scalar.basic import Ceil, Clip, Floor, RoundHalfToEven
 from pytensor.scalar.basic import clip as scalar_clip
-from pytensor.tensor.elemwise import Elemwise
+from pytensor.tensor.math import ceil, clip, floor, round_half_to_even
 from pytensor.tensor.var import TensorConstant
 
 from pymc.logprob.abstract import (
@@ -67,7 +67,7 @@ class MeasurableClip(MeasurableElemwise):
 measurable_clip = MeasurableClip(scalar_clip)
 
 
-@node_rewriter(tracks=[Elemwise])
+@node_rewriter(tracks=[clip])
 def find_measurable_clips(fgraph: FunctionGraph, node: Node) -> Optional[List[MeasurableClip]]:
     # TODO: Canonicalize x[x>ub] = ub -> clip(x, x, ub)
 
@@ -78,9 +78,6 @@ def find_measurable_clips(fgraph: FunctionGraph, node: Node) -> Optional[List[Me
     if isinstance(node.op, MeasurableClip):
         return None  # pragma: no cover
 
-    if not (isinstance(node.op, Elemwise) and isinstance(node.op.scalar_op, Clip)):
-        return None
-
     clipped_var = node.outputs[0]
     base_var, lower_bound, upper_bound = node.inputs
 
@@ -179,7 +176,7 @@ class MeasurableRound(MeasurableElemwise):
     valid_scalar_types = (RoundHalfToEven, Floor, Ceil)
 
 
-@node_rewriter(tracks=[Elemwise])
+@node_rewriter(tracks=[ceil, floor, round_half_to_even])
 def find_measurable_roundings(fgraph: FunctionGraph, node: Node) -> Optional[List[MeasurableRound]]:
 
     rv_map_feature = getattr(fgraph, "preserve_rv_mappings", None)
@@ -189,12 +186,6 @@ def find_measurable_roundings(fgraph: FunctionGraph, node: Node) -> Optional[Lis
     if isinstance(node.op, MeasurableRound):
         return None  # pragma: no cover
 
-    if not (
-        isinstance(node.op, Elemwise)
-        and isinstance(node.op.scalar_op, MeasurableRound.valid_scalar_types)
-    ):
-        return None
-
     (rounded_var,) = node.outputs
     (base_var,) = node.inputs
 

pymc/logprob/transforms.py

@@ -48,7 +48,7 @@
 from pytensor.graph.op import Op
 from pytensor.graph.rewriting.basic import GraphRewriter, in2out, node_rewriter
 from pytensor.scalar import Add, Exp, Log, Mul
-from pytensor.tensor.elemwise import Elemwise
+from pytensor.tensor.math import add, exp, log, mul
 from pytensor.tensor.rewriting.basic import (
     register_specialize,
     register_stabilize,
@@ -256,12 +256,9 @@ def measurable_transform_logprob(op: MeasurableTransform, values, *inputs, **kwa
     return input_logprob + jacobian
 
 
-@node_rewriter([Elemwise])
+@node_rewriter([exp, log, add, mul])
 def find_measurable_transforms(fgraph: FunctionGraph, node: Node) -> Optional[List[Node]]:
     """Find measurable transformations from Elemwise operators."""
-    scalar_op = node.op.scalar_op
-    if not isinstance(scalar_op, MeasurableTransform.valid_scalar_types):
-        return None
 
     # Node was already converted
     if isinstance(node.op, MeasurableVariable):
@@ -311,6 +308,7 @@ def find_measurable_transforms(fgraph: FunctionGraph, node: Node) -> Optional[Li
     # This seems to be the only thing preventing nested rewrites from being erased
     measurable_input = assign_custom_measurable_outputs(measurable_input.owner)
 
+    scalar_op = node.op.scalar_op
     measurable_input_idx = 0
     transform_inputs: Tuple[TensorVariable, ...] = (measurable_input,)
     transform: RVTransform