code: def align_method_FRAME(
      left, right, axis, flex: bool | None = False, level: Level = None
  ):
      """
      Convert rhs to meet lhs dims if input is list, tuple or np.ndarray.
  
      Parameters
      ----------
      left : DataFrame
      right : Any
      axis : int, str, or None
      flex : bool or None, default False
          Whether this is a flex op, in which case we reindex.
          None indicates not to check for alignment.
      level : int or level name, default None
  
      Returns
      -------
      left : DataFrame
      right : Any
      """
  
      def to_series(right):
          msg = "Unable to coerce to Series, length must be {req_len}: given {given_len}"
  
          # pass dtype to avoid doing inference, which would break consistency
          #  with Index/Series ops
          dtype = None
          if getattr(right, "dtype", None) == object:
              # can't pass right.dtype unconditionally as that would break on e.g.
              #  datetime64[h] ndarray
              dtype = object
  
          if axis is not None and left._get_axis_name(axis) == "index":
              if len(left.index) != len(right):
                  raise ValueError(
                      msg.format(
                          req_len=len(left.index), given_len=len(right)
                      )
                  )
              right = left._constructor_sliced(
                  right, index=left.index, dtype=dtype
              )
          else:
              if len(left.columns) != len(right):
                  raise ValueError(
                      msg.format(
                          req_len=len(left.columns),
                          given_len=len(right),
                      )
                  )
              right = left._constructor_sliced(
                  right, index=left.columns, dtype=dtype
              )
          return right
  
      if isinstance(right, np.ndarray):
          if right.ndim == 1:
              right = to_series(right)
  
          elif right.ndim == 2:
              # We need to pass dtype=right.dtype to retain object dtype
              #  otherwise we lose consistency with Index and array ops
              dtype = None
              if getattr(right, "dtype", None) == object:
                  # can't pass right.dtype unconditionally as that would break on e.g.
                  #  datetime64[h] ndarray
                  dtype = object
  
              if right.shape == left.shape:
                  right = left._constructor(
                      right,
                      index=left.index,
                      columns=left.columns,
                      dtype=dtype,
                  )
  
              elif (
                  right.shape[0] == left.shape[0]
                  and right.shape[1] == 1
              ):
                  # Broadcast across columns
                  right = np.broadcast_to(right, left.shape)
                  right = left._constructor(
                      right,
                      index=left.index,
                      columns=left.columns,
                      dtype=dtype,
                  )
  
              elif (
                  right.shape[1] == left.shape[1]
                  and right.shape[0] == 1
              ):
                  # Broadcast along rows
                  right = to_series(right[0, :])
  
              else:
                  raise ValueError(
                      "Unable to coerce to DataFrame, shape "
                      f"must be {left.shape}: given {right.shape}"
                  )
  
          elif right.ndim > 2:
              raise ValueError(
                  "Unable to coerce to Series/DataFrame, "
                  f"dimension must be <= 2: {right.shape}"
              )
  
      elif is_list_like(right) and not isinstance(
          right, (ABCSeries, ABCDataFrame)
      ):
          # GH 36702. Raise when attempting arithmetic with list of array-like.
          if any(is_array_like(el) for el in right):
              raise ValueError(
                  f"Unable to coerce list of {type(right[0])} to Series/DataFrame"
              )
          # GH17901
          right = to_series(right)
  
      if flex is not None and isinstance(right, ABCDataFrame):
          if not left._indexed_same(right):
              if flex:
                  left, right = left.align(
                      right, join="outer", level=level, copy=False
                  )
              else:
                  raise ValueError(
                      "Can only compare identically-labeled (both index and columns) "
                      "DataFrame objects"
                  )
      elif isinstance(right, ABCSeries):
          # axis=1 is default for DataFrame-with-Series op
          axis = left._get_axis_number(axis) if axis is not None else 1
  
          if not flex:
              if not left.axes[axis].equals(right.index):
                  raise ValueError(
                      "Operands are not aligned. Do "
                      "`left, right = left.align(right, axis=1, copy=False)` "
                      "before operating."
                  )
  
          left, right = left.align(
              right, join="outer", axis=axis, level=level, copy=False
          )
          right = _maybe_align_series_as_frame(left, right, axis)
  
      return left, right
  
imports: from __future__ import annotations
  import operator
  from typing import TYPE_CHECKING, cast
  import numpy
  from pandas._libs.ops_dispatch import maybe_dispatch_ufunc_to_dunder_op
  from pandas._typing import Axis, AxisInt, Level
  from pandas.util._decorators import Appender
  from pandas.core.dtypes.common import is_array_like, is_list_like
  from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries
  from pandas.core.dtypes.missing import isna
  from pandas.core import algorithms, roperator
  from pandas.core.ops.array_ops import arithmetic_op, comp_method_OBJECT_ARRAY, comparison_op, get_array_op, logical_op, maybe_prepare_scalar_for_op
  from pandas.core.ops.common import get_op_result_name, unpack_zerodim_and_defer
  from pandas.core.ops.docstrings import _flex_comp_doc_FRAME, _op_descriptions, make_flex_doc
  from pandas.core.ops.invalid import invalid_comparison
  from pandas.core.ops.mask_ops import kleene_and, kleene_or, kleene_xor
  from pandas.core.ops.methods import add_flex_arithmetic_methods
  from pandas.core.roperator import radd, rand_, rdiv, rdivmod, rfloordiv, rmod, rmul, ror_, rpow, rsub, rtruediv, rxor
label_desc: Use image node_id 4 for calling a global function with example usage: align_method_FRAME(left, right, axis, flex, level) and returns: left,  right, right