class_docstr: A callback to fetch predictions during the training loop
class_docstr_tok: ["A","callback","to","fetch","predictions","during","the","training","loop"]
docstr: Fetch predictions from `Learner` without `self.cbs` and `remove_on_fetch` callbacks
docstr_tok: ["Fetch","predictions","from","`","Learner","`","without","`","self.cbs","`","and","`","remove_on_fetch","`","callbacks"]
code: def after_validate(self):
      "Fetch predictions from `Learner` without `self.cbs` and `remove_on_fetch` callbacks"
      to_rm = L(
          cb
          for cb in self.learn.cbs
          if getattr(cb, "remove_on_fetch", False)
      )
      with self.learn.removed_cbs(to_rm + self.cbs) as learn:
          self.preds = learn.get_preds(
              ds_idx=self.ds_idx,
              dl=self.dl,
              with_input=self.with_input,
              with_decoded=self.with_decoded,
              inner=True,
              reorder=self.reorder,
          )
  
imports: from __future__ import annotations
  from ..data.all import *
  from ..optimizer import *
  from ..losses import BaseLoss
label_desc: Use image node_id 2 for calling the FetchPredsCallback obj's underlying member method code with example usage: obj.after_validate() without return types