class_docstr: RV whose logprob should be rescaled to match total_size
class_docstr_tok: ["RV","whose","logprob","should","be","rescaled","to","match","total_size"]
code: def perform(self, node, inputs, output_storage):
      output_storage[0][0] = inputs[0]
  
file_path: pymc/pymc/variational/minibatch_rv.py
imports: from typing import Any, Sequence, Union, cast
  import pytensor.tensor
  from pytensor import Variable, config
  from pytensor.graph import Apply, Op
  from pytensor.tensor import NoneConst, TensorVariable, as_tensor_variable
  from pymc.logprob.abstract import MeasurableVariable, _logprob, _logprob_helper
label_desc: Use image node_id 2 for calling the MinibatchRandomVariable obj's underlying member method code with example usage: obj.perform(node, inputs, output_storage) without return types