code: def get_second_solve_batch_matrix(
      draw, allow_simplified=True, choose_side=False
  ):
      """Generate right hand side of equation system. Possible with a batch
      dimension and possibly with several columns of values. Use
      get_first_solve_batch_matrix to generate the left hand side.
  
      Parameters
      ----------
      allow_simplified
          if True, a 1D vector with correct length can be returned as the right hand side
      choose_side
          Randomly choose if the system to be solved is AX=B or XA=B,
          where X is the unknown solution
  
      Returns
      -------
      dtype
          Data type of the generated array
      matrix
          Generated array
      left
          If True, the system is AX=B, otherwise it is XA=B
      """
      # float16 causes a crash when filtering out matrices
      # for which `np.linalg.cond` is large.
      input_dtype_strategy = st.shared(
          st.sampled_from(draw(helpers.get_dtypes("float"))).filter(
              lambda x: "float16" not in x
          ),
          key="shared_dtype",
      )
      input_dtype = draw(input_dtype_strategy)
  
      shared_size = draw(
          st.shared(
              helpers.ints(min_value=2, max_value=4), key="shared_size"
          )
      )
      batch_size = draw(
          st.shared(
              helpers.ints(min_value=0, max_value=3),
              key="shared_batch_size",
          )
      )
      num_systems = draw(
          st.shared(helpers.ints(min_value=1, max_value=4))
      )
      left = True
      if choose_side:
          left = draw(st.booleans())
      shape = []
      if batch_size > 0:
          shape += [batch_size]
      if left:
          if (
              allow_simplified
              and batch_size == 0
              and num_systems == 1
              and draw(st.booleans())
          ):
              shape = tuple(shape + [shared_size])
          else:
              shape = tuple(shape + [shared_size, num_systems])
      else:
          shape = tuple(shape + [num_systems, shared_size])
  
      return (
          input_dtype,
          draw(
              helpers.array_values(
                  dtype=input_dtype,
                  shape=shape,
                  min_value=2,
                  max_value=5,
              )
          ),
          left,
      )
  
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 27 for calling a global function with example usage: get_second_solve_batch_matrix(draw, allow_simplified, choose_side) and returns: input_dtype,  draw,  left