code: def create_concatenable_arrays_dtypes(
      draw,
      min_num_dims,
      max_num_dims,
      min_num_arrays,
      max_num_arrays,
      concat_dim,
      dtypes,
      common_shape=None,
  ):
      """Draws a random number of arrays with concatenable or stackable
      dimensions. Arrays have same number of dimensions, but their shape can
      differ along a specified dimension (concat_dim). If concat_dim is None,
      arrays have the same shape. Dtypes of arrays can differ.
  
      Parameters
      ----------
      min_num_dims
          minimum number of dimensions
      max_num_dims
          maximum number of dimensions
      min_num_arrays
          minimum number of arrays
      max_num_arrays
          maximum number of arrays
      concat_dim
          dimension along which the shape of arrays can differ,
          if None all the arrays will have the same shape
      dtypes
          list of dtypes from which array dtypes will be draws,
          each array can have different dtype
      given_common_shape
          if not None, specifies the shape of the arrays
          (dimension concat_dim can still be modified)
      """
      num_arrays = draw(
          helpers.ints(
              min_value=min_num_arrays, max_value=max_num_arrays
          )
      )
      if common_shape is None:
          num_dims = draw(
              helpers.ints(
                  min_value=min_num_dims, max_value=max_num_dims
              )
          )
          common_shape = draw(
              helpers.list_of_size(
                  x=helpers.ints(min_value=1, max_value=5),
                  size=num_dims,
              )
          )
      else:
          num_dims = len(common_shape)
      input_dtypes = draw(
          helpers.array_dtypes(
              num_arrays=num_arrays, available_dtypes=dtypes
          )
      )
      array_shapes = [common_shape.copy() for i in range(num_arrays)]
      if num_dims > 0 and concat_dim is not None:
          unique_dims = draw(
              helpers.list_of_size(
                  x=helpers.ints(min_value=1, max_value=5),
                  size=num_arrays,
              )
          )
          for i in range(num_arrays):
              array_shapes[i][concat_dim] = unique_dims[i]
  
      xs = []
  
      for sh, dt in zip(array_shapes, input_dtypes):
          x = draw(
              helpers.array_values(
                  shape=sh,
                  dtype=dt,
              )
          )
          xs.append(x)
      return xs, input_dtypes
  
imports: import numpy
  import hypothesis.extra.numpy
  from hypothesis import strategies
  from hypothesis.internal.floats import float_of
  from functools import reduce
  from operator import mul
  import sys
  import string
  import ml_dtypes
  import ivy_tests.test_ivy.helpers.globals
  from ..pipeline_helper import WithBackendContext
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers.hypothesis_helpers.dtype_helpers import get_dtypes
  from .None import general_helpers
  from .None import dtype_helpers, number_helpers
  from ..globals import mod_backend
label_desc: Use image node_id 25 for calling a global function with example usage: create_concatenable_arrays_dtypes(draw, min_num_dims, max_num_dims, min_num_arrays, max_num_arrays, concat_dim, dtypes, common_shape) and returns: xs,  input_dtypes