code: def get_scipy_batch_logpdf(self, idx):
      if not self.scipy_arg_fn:
          return
      dist_params = self.get_dist_params(idx, wrap_tensor=False)
      dist_params_wrapped = self.get_dist_params(idx)
      dist_params = self._convert_logits_to_ps(dist_params)
      test_data = self.get_test_data(idx, wrap_tensor=False)
      test_data_wrapped = self.get_test_data(idx)
      shape = broadcast_shape(
          self.pyro_dist(**dist_params_wrapped).shape(),
          test_data_wrapped.size(),
      )
      log_prob = []
      for i in range(len(test_data)):
          batch_params = {}
          for k in dist_params:
              param = np.broadcast_to(dist_params[k], shape)
              batch_params[k] = param[i]
          args, kwargs = self.scipy_arg_fn(**batch_params)
          if self.is_discrete:
              log_prob.append(
                  self.scipy_dist.logpmf(test_data[i], *args, **kwargs)
              )
          else:
              log_prob.append(
                  self.scipy_dist.logpdf(test_data[i], *args, **kwargs)
              )
      return log_prob
  
imports: import math
  import numpy
  import torch
  from torch.distributions.utils import logits_to_probs
  from pyro.distributions.util import broadcast_shape
label_desc: Use image node_id 12 for calling the Fixture obj's underlying member method code with example usage: obj.get_scipy_batch_logpdf(idx) and returns: log_prob