code: def get_support_shape_1d(
      support_shape: Optional[Union[int, np.ndarray, TensorVariable]],
      *,
      shape: Optional[Shape] = None,
      dims: Optional[Dims] = None,
      observed: Optional[Any] = None,
      support_shape_offset: int = 0,
  ) -> Optional[TensorVariable]:
      """Helper function for cases when you just care about one dimension."""
      support_shape_tuple = get_support_shape(
          support_shape=(support_shape,)
          if support_shape is not None
          else None,
          shape=shape,
          dims=dims,
          observed=observed,
          support_shape_offset=(support_shape_offset,),
      )
  
      if support_shape_tuple is not None:
          (support_shape_,) = support_shape_tuple
          return support_shape_
      else:
          return None
  
imports: import warnings
  from functools import singledispatch
  from typing import Any, Optional, Sequence, Tuple, Union, cast
  import numpy
  from pytensor import config
  from pytensor import tensor
  from pytensor.graph.basic import Variable
  from pytensor.graph.op import Op, compute_test_value
  from pytensor.raise_op import Assert
  from pytensor.tensor.random.op import RandomVariable
  from pytensor.tensor.shape import SpecifyShape
  from pytensor.tensor.variable import TensorVariable
  from typing_extensions import TypeAlias
  from pymc.model import modelcontext
  from pymc.pytensorf import convert_observed_data
  from pymc.exceptions import ShapeError
  from pymc.pytensorf import PotentialShapeType
  from pymc.util import _add_future_warning_tag
label_desc: Use image node_id 15 for calling a global function with example usage: get_support_shape_1d(support_shape) and returns: support_shape_, None