if errors:
            raise ResponseValidationError(
                errors=_normalize_errors(errors), body=response_content
            )

        if hasattr(field, "serialize"):
            return field.serialize(
                value,
                include=include,
                exclude=exclude,
                by_alias=by_alias,
                exclude_unset=exclude_unset,

                    not include that field, the JSON sent to the client would not have
                    that `password`.
                * Validation: whatever you return will be serialized with the
                    `response_model`, converting any data as necessary to generate the
                    corresponding JSON. But if the data in the object returned is not

			if err != nil {
				err = msgp.WrapError(err)
				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z *allTierStats) Msgsize() (s int) {
	s = 1 + 3 + msgp.MapHeaderSize
	if z.Tiers != nil {
		for za0001, za0002 := range z.Tiers {
			_ = za0002

//   tile_assignment_dimensions: 2
//   tile_assignment_devices: 0
//   tile_assignment_devices: 1
// Serialized string:
//  "\08\03\1A\02\01\02\22\02\00\01"
//
// input 1
//  type: MAXIMAL
//  tile_assignment_dimensions: 1
//  tile_assignment_devices: 1
// Serialized string:
//  "\08\01\1A\01\01\22\01\01"

// -----

			if err != nil {
				err = msgp.WrapError(err)
				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z BaseOptions) Msgsize() (s int) {
	s = 1
	return
}

// DecodeMsg implements msgp.Decodable
func (z *CheckPartsHandlerParams) DecodeMsg(dc *msgp.Reader) (err error) {
	var field []byte

  func.return %0 : tensor<4x4x4xf32>
}

// -----

// CHECK-LABEL: func @testParseExampleV2DenseOnlyValid
func.func @testParseExampleV2DenseOnlyValid(%serialized: tensor<32x!tf_type.string>, %names : tensor<32x!tf_type.string>, %dense_keys : tensor<2x!tf_type.string>, %dense_default_0 : tensor<?xf32>, %dense_default_1 : tensor<?xf32>) -> (tensor<32xf32>) {

                          const void** buf, size_t* len);

// TODO(josh11b,mrry): Change Session to be able to use a Graph*
// directly, instead of requiring us to serialize to a GraphDef and
// call Session::Extend().
bool ExtendSessionGraphHelper(TF_Session* session, TF_Status* status) {
  if (session->graph != nullptr) {

};

// Translates an MLIR module in TFLite dialect to TFLite FlatBuffer.
class Translator {
 public:
  // Translates the given MLIR module into TFLite FlatBuffer format and returns
  // the serialized output. Returns std::nullopt on unsupported, invalid inputs
  // or internal error.
  static std::optional<std::string> Translate(
      ModuleOp module, const toco::TocoFlags& toco_flags,

    : Pass<"tf-xla-call-module-serialization", "ModuleOp"> {
  let summary = "Serializes StableHLO functions from top-level module into `tf.XlaCallModule`'s `module` attribute";

  let description = [{
    This pass collects StableHLO functions referenced from `tf.XlaCallModule`'s
    `_entry_function` attribute into a module, serializes the module into MLIR

will be emitted - The exponent (or suffix) is as large as possible.\n\nThe sign will be omitted unless the number is negative.\n\nExamples:\n\n- 1.5 will be serialized as \"1500m\" - 1.5Gi will be serialized as \"1536Mi\"\n\nNote that the quantity will NEVER be internally represented by a floating point number. That is the whole point of this exercise.\n\nNon-canonical values will still parse as long as they are well formed, but will be re-emitted in their canonical form. (So always use canonical...