response_content: Any,
    include: Optional[IncEx] = None,
    exclude: Optional[IncEx] = None,
    by_alias: bool = True,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    is_coroutine: bool = True,
) -> Any:
    if field:
        errors = []
        if not hasattr(field, "serialize"):
            # pydantic v1

// true.
bool VerifyOperandsHaveSameShapesOrBroadcastableShape(
    Operation* op, ArrayRef<unsigned> indices, int max_bcast_rank) {
  if (indices.empty()) return true;

  // First, it checks there are any inputs that has unknown rank.
  bool has_unknown_shape_input = false;
  bool has_same_shape = true;
  bool reach_first_known_shape = false;
  int64_t max_rank = -1;

    const bool has_i32_output =
        IsI32F32UniformQuantizedPerAxisType(GetElementType(op.getResult()));
    stablehlo::ConvDimensionNumbersAttr dimension_numbers =
        op.getDimensionNumbers();

    const bool is_depthwise = IsDepthwiseConvolution(op);
    const bool is_transpose_conv = IsTransposeConv(op, dimension_numbers);
    const bool fuse_bias_constant =

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(OptimizePass)

  OptimizePass() = default;
  OptimizePass(const OptimizePass &) {}
  explicit OptimizePass(bool enable_canonicalization,
                        bool disable_fuse_mul_and_fc = false) {
    this->enable_canonicalization_ = enable_canonicalization;
    this->disable_fuse_mul_and_fc_ = disable_fuse_mul_and_fc;
  }

        deprecated: Optional[bool] = None,
        methods: Optional[List[str]] = None,
        operation_id: Optional[str] = None,
        response_model_include: Optional[IncEx] = None,
        response_model_exclude: Optional[IncEx] = None,
        response_model_by_alias: bool = True,
        response_model_exclude_unset: bool = False,
        response_model_exclude_defaults: bool = False,

	return Value{ptrTo(v.typ()), v.ptr, fl | flag(Pointer)}
}

// Bool returns v's underlying value.
// It panics if v's kind is not [Bool].
func (v Value) Bool() bool {
	// panicNotBool is split out to keep Bool inlineable.
	if v.kind() != Bool {
		v.panicNotBool()
	}
	return *(*bool)(v.ptr)
}

func (v Value) panicNotBool() {
	v.mustBe(Bool)
}

var bytesType = rtypeOf(([]byte)(nil))

					FSGroupChangePolicy: &changePolicy,
				},
			},
		}
	}
	podInfos := []struct {
		description                  string
		newPodHasFSGroupChangePolicy bool
		pod                          func() *api.Pod
		expectPolicyInPod            bool
	}{
		{
			description:                  "oldPod.FSGroupChangePolicy=nil, feature=true, newPod.FSGroupChangePolicy=true",
			pod:                          nofsGroupPod,

		{new(float64), [...]bool{false, false, false, false}},
		{new(complex64), [...]bool{false, false, false, false}},
		{new([5]int), [...]bool{false, false, false, false}},
		{new(integer), [...]bool{false, false, false, false}},
		{new(map[int]int), [...]bool{false, false, false, false}},
		{new(chan<- int), [...]bool{false, false, false, false}},
		{new(func(a int8)), [...]bool{false, false, false, false}},

    std::vector<string>* shape_inference_graphs,
    bool* has_outside_compilation) {
  // Instantiate "cond" and "body".
  NameAttrList cond, body;
  TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "cond", &cond));
  TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "body", &body));

  // Extract outside compilation for cond and body.
  bool cond_has_outside_compilation = false;
  bool body_has_outside_compilation = false;

		containerFsStats              string
		kubeletSeparateDiskFeature    bool
		writeableSeparateFromReadOnly bool
		expectContainerGcCall         bool
		expectImageGcCall             bool
		thresholdToMonitor            evictionapi.Threshold
		podToMakes                    []podToMake
		dedicatedImageFs              *bool
		expectErr                     string
		inducePressureOnWhichFs       string