Deleted output_subset kwargs

Author: HangenYuu

pytensor/compile/function/types.py

@@ -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():
@@ -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
@@ -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"):
@@ -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,