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Simplify the Function class #955

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Simplify the Function class #955

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1da9599
Deleted output_subset kwargs
HangenYuu Jul 25, 2024
f08eedf
Removed unused param in construct_pfunc_ins_and_outs
HangenYuu Jul 25, 2024
0f89e28
Added trust_input
HangenYuu Jul 26, 2024
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37 changes: 7 additions & 30 deletions pytensor/compile/function/types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -792,18 +792,14 @@ def __call__(self, *args, **kwargs):
The function inputs can be passed as keyword argument. For this, use
the name of the input or the input instance as the key.

Keyword argument ``output_subset`` is a list of either indices of the
function's outputs or the keys belonging to the `output_keys` dict
and represent outputs that are requested to be calculated. Regardless
of the presence of ``output_subset``, the updates are always calculated
and processed. To disable the updates, you should use the ``copy``
The updates are always calculated and processed.
To disable the updates, you should use the ``copy``
method with ``delete_updates=True``.

Returns
-------
list
List of outputs on indices/keys from ``output_subset`` or all of them,
if ``output_subset`` is not passed.
List of outputs.
"""

def restore_defaults():
Expand All @@ -816,10 +812,6 @@ def restore_defaults():
profile = self.profile
t0 = time.perf_counter()

output_subset = kwargs.pop("output_subset", None)
if output_subset is not None and self.output_keys is not None:
output_subset = [self.output_keys.index(key) for key in output_subset]

# Reinitialize each container's 'provided' counter
if self.trust_input:
i = 0
Expand Down Expand Up @@ -955,11 +947,7 @@ def restore_defaults():
# Do the actual work
t0_fn = time.perf_counter()
try:
outputs = (
self.vm()
if output_subset is None
else self.vm(output_subset=output_subset)
)
outputs = self.vm()
except Exception:
restore_defaults()
if hasattr(self.vm, "position_of_error"):
Expand Down Expand Up @@ -1040,24 +1028,13 @@ def restore_defaults():
profile.ignore_first_call = False
if self.return_none:
return None
elif self.unpack_single and len(outputs) == 1 and output_subset is None:
elif self.unpack_single and len(outputs) == 1:
return outputs[0]
else:
if self.output_keys is not None:
assert len(self.output_keys) == len(outputs)

if output_subset is None:
return dict(zip(self.output_keys, outputs))
else:
return {
self.output_keys[index]: outputs[index]
for index in output_subset
}

if output_subset is None:
return outputs
else:
return [outputs[i] for i in output_subset]
return dict(zip(self.output_keys, outputs))
return outputs

value = property(
lambda self: self._value,
Expand Down
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