code: def __call__(self, inputs, scalars=None, **kwargs):
      if scalars is not None:
          assert len(inputs) == 3
          # We need to distribute each scalar to the regular func and it needs
          # special consideration as it is a keyword only argument to the
          # regular func. (Strangely, it is not a keyword only argument to the
          # foreach func)
          return [
              self.func(*i, value=scalars[idx], **kwargs)
              for idx, i in enumerate(zip(*inputs))
          ]
      if len(inputs) == 2 and isinstance(
          inputs[1], (Number, torch.Tensor)
      ):
          # binary op with tensorlist and scalar.
          inputs[1] = [inputs[1] for _ in range(len(inputs[0]))]
      return [self.func(*i, **kwargs) for i in zip(*inputs)]
  
imports: from contextlib import nullcontext
  from numbers import Number
  import random
  import re
  import torch
  import unittest
  import itertools
  import weakref
  from torch.testing import make_tensor
  from torch.testing._comparison import default_tolerances
  from torch.testing._internal.common_cuda import TEST_MULTIGPU
  from torch.testing._internal.common_utils import TestCase, run_tests, TEST_WITH_ROCM, skipIfTorchDynamo, parametrize, gradcheck
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes, onlyCUDA, ops, OpDTypes
  from torch.testing._internal.common_methods_invocations import foreach_unary_op_db, foreach_binary_op_db, foreach_pointwise_op_db, foreach_reduce_op_db, foreach_other_op_db
  from torch.testing._internal.common_dtype import all_types_and_complex_and, floating_types_and, floating_types, integral_types_and
label_desc: Use image node_id 2 for calling the RegularFuncWrapper obj's underlying member method code with example usage: obj.__call__(inputs, scalars) and returns: unknown, unknown