code: def bincount(
      x: torch.Tensor,
      /,
      *,
      weights: Optional[torch.Tensor] = None,
      minlength: int = 0,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if weights is None:
          ret = torch.bincount(x, minlength=minlength)
          ret = ret.to(x.dtype)
      else:
          ret = torch.bincount(x, weights=weights, minlength=minlength)
          ret = ret.to(weights.dtype)
      return ret
  
imports: from typing import Optional, Union, Tuple, Sequence
  import torch
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  import ivy
  from ..statistical import _infer_dtype
  from copy import deepcopy
label_desc: Use image node_id 15 for calling a global function with example usage: bincount() and returns: ret