code: def _infer_dtype(dtype: torch.dtype) -> torch.dtype:
      default_dtype = ivy.infer_default_dtype(dtype)
      if default_dtype in ivy.valid_dtypes:
          if ivy.dtype_bits(dtype) < ivy.dtype_bits(default_dtype):
              return ivy.as_native_dtype(default_dtype)
      return ivy.as_native_dtype(dtype)
  
file_path: ivy/ivy/functional/backends/torch/statistical.py
imports: from typing import Union, Optional, Sequence
  import torch
  import ivy
  from ivy.functional.ivy.statistical import _get_promoted_type_of_operands
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
label_desc: Use image node_id 4 for calling a global function with example usage: _infer_dtype(dtype) and returns: ivy, ivy