code: def partial_tensor_to_vec(
      x: Union[ivy.Array, ivy.NativeArray],
      /,
      skip_begin: Optional[int] = 1,
      skip_end: Optional[int] = 0,
      *,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """Partial vectorization of a tensor while ignoring the specified dimension
      at the beginning and the end.
  
      Parameters
      ----------
      x
          tensor to partially vectorise
      skip_begin
          number of dimensions to leave untouched at the beginning
      skip_end
          number of dimensions to leave untouched at the end
      out
          optional output array, for writing the result to.
  
      Returns
      -------
      ret
          partially vectorised tensor with the
          `skip_begin` first and `skip_end` last dimensions untouched
      """
      return partial_unfold(
          x,
          mode=0,
          skip_begin=skip_begin,
          skip_end=skip_end,
          ravel_tensors=True,
          out=out,
      )
  
imports: from typing import Optional, Union, Tuple, Iterable, Sequence, Callable, Any, Literal, List
  from numbers import Number
  from functools import partial
  import math
  import ivy
  from ivy.func_wrapper import handle_out_argument, handle_partial_mixed_function, to_native_arrays_and_back, inputs_to_native_shapes, handle_nestable, handle_array_like_without_promotion, handle_view, inputs_to_ivy_arrays, handle_array_function, handle_device, handle_backend_invalid
  from ivy.functional.ivy.general import _numel
  from ivy.utils.backend import current_backend
  from ivy.utils.exceptions import handle_exceptions
label_desc: Use image node_id 52 for calling a global function with example usage: partial_tensor_to_vec(skip_begin, skip_end) and returns: partial_unfold