code: def nanprod(
      a: Union[tf.Tensor, tf.Variable],
      /,
      *,
      axis: Optional[Union[int, Sequence[int]]] = None,
      dtype: Optional[tf.DType] = None,
      keepdims: Optional[bool] = False,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
      initial: Optional[Union[int, float, complex]] = None,
      where: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      np_math_ops.enable_numpy_methods_on_tensor()
      dtype = ivy.as_native_dtype(dtype)
      if dtype is None:
          dtype = _infer_dtype(a.dtype)
      if initial is None:
          initial = 1
      axis = tuple(axis) if isinstance(axis, list) else axis
      return (
          tf.experimental.numpy.nanprod(
              a, axis=axis, keepdims=keepdims, dtype=dtype
          )
          * initial
      )
  
imports: from typing import Union, Optional, Tuple, Sequence
  import tensorflow
  from tensorflow.python.ops.numpy_ops import np_math_ops
  import ivy
  from ivy import with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dtypes
  from ..None import backend_version
  from copy import deepcopy
label_desc: Use image node_id 6 for calling a global function with example usage: nanprod() and returns: unknown