code: def test_default_bias_type(self, compute_unit, backend, input_type):
      # Test the default bias matches the dtype of x and weight.
      @mb.program(
          input_specs=[mb.TensorSpec(shape=(1, 2), dtype=types.fp32)],
          opset_version=backend.opset_version,
      )
      def prog(x):
          x = mb.cast(x=x, dtype=builtin_to_string(input_type))
          weight = np.random.rand(3, 2).astype(
              nptype_from_builtin(input_type)
          )
          res = mb.linear(x=x, weight=weight)
          assert res.op.bias.val.dtype == nptype_from_builtin(
              input_type
          )
          return res
  
imports: import itertools
  import platform
  import numpy
  import pytest
  import coremltools
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import get_new_symbol, types
  from coremltools.converters.mil.mil.ops.tests.iOS14 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import run_compare_builder
  from coremltools.converters.mil.mil.types import builtin_to_string, nptype_from_builtin
  from coremltools.converters.mil.testing_reqs import compute_units
  from coremltools.converters.mil.testing_utils import random_gen, ssa_fn
label_desc: Use image node_id 4 for calling the TestLinear obj's underlying member method code with example usage: obj.test_default_bias_type(compute_unit, backend, input_type) and returns: res