code: def _execute_reduce(cls, ctx, op: "TensorBinCount"):
      out = op.outputs[0]
      input_list = list(
          d
          for d in op.iter_mapper_data(ctx, skip_none=True)
          if d is not None
      )
      left_bound = op.chunk_size_limit * out.index[0]
      right_bound = min(
          left_bound + op.chunk_size_limit, op.tileable_right_bound
      )
      if not input_list:
          ctx[op.outputs[0].key] = np.zeros(right_bound - left_bound)
      else:
          res = functools.reduce(
              lambda a, b: a.add(b, fill_value=0), input_list
          ).astype(out.dtype)
          res = res.reindex(
              pd.RangeIndex(left_bound, right_bound), fill_value=0
          )
          ctx[op.outputs[0].key] = res.values
  
imports: import itertools
  import functools
  from typing import Optional
  import numpy
  import pandas
  from ...None import opcodes, options, get_context
  from ...core import recursive_tile, OutputType
  from ...core.operand import OperandStage
  from ...serialization.serializables import Int64Field, ReferenceField
  from ...utils import ceildiv, has_unknown_shape
  from ..datasource import tensor
  from ..operands import TensorOperandMixin, TensorMapReduceOperand
label_desc: Use image node_id 6 for calling the TensorBinCount obj's underlying member method code with example usage: obj._execute_reduce(cls, ctx, op) without return types