}

    /**
     * Parses a sequence of XML elements and converts them to the appropriate array type.
     *
     * @param parser The XML parser
     * @return Converted array instance
     */
    private Object parseArray(final MXParser parser, final TypeLiteral<?> toType) throws Exception {
        // convert to a collection first then convert that into an array

  "CreateXlaDotV2OpFromTfEinsumOp($_builder, $_loc, $0...)">;

def IsEinsumOpSupported : Constraint<
  CPred<"IsEinsumOpSupported($0, $1, $2)">,
  "Check if the given einsum op could be converted into a XlaDotV2 op.">;

// Converts inlined Conv2D pattern to TF XlaConvV2 op. This pattern doesn't
// support non-constant weights.
def ConvertTFConv2DToXLAConvOp : Pat<
  (TF_Conv2DOp:$conv

		return err
	}
	if err := c.convertor.Convert(&parameters, input, nil); err != nil {
		return err
	}
	// if we have defaulter, default the input before converting to output
	if c.defaulter != nil {
		c.defaulter.Default(input)
	}
	return c.convertor.Convert(input, into, nil)
}

// EncodeParameters converts the provided object into the to version, then converts that object to url.Values.

  else
    input_tensor.AsProtoField(&tensor_proto);
  return tensor_proto;
}

static std::string MangleTensor(const Tensor& tensor) {
  return mangling_util::MangleTensor(ConvertToProto(tensor));
}

// Converts a TensorFlow tensor into an MLIR elements attribute.
template <typename T>
absl::StatusOr<ElementsAttr> ConvertFlatTensor(const Tensor& input_tensor,
                                               ShapedType type) {

	return runtimeapi.Protocol_TCP
}

// toKubeContainer converts runtimeapi.Container to kubecontainer.Container.
func (m *kubeGenericRuntimeManager) toKubeContainer(c *runtimeapi.Container) (*kubecontainer.Container, error) {
	if c == nil || c.Id == "" || c.Image == nil {
		return nil, fmt.Errorf("unable to convert a nil pointer to a runtime container")
	}

		period = QuotaPeriod
	}

	// we then convert your milliCPU to a value normalized over a period
	quota = (milliCPU * period) / MilliCPUToCPU

	// quota needs to be a minimum of 1ms.
	if quota < MinQuotaPeriod {
		quota = MinQuotaPeriod
	}
	return
}

// MilliCPUToShares converts the milliCPU to CFS shares.
func MilliCPUToShares(milliCPU int64) uint64 {
	if milliCPU == 0 {

}

def ConvertFuncToBfloat16Pass : Pass<"stablehlo-convert-func-to-bfloat16", "mlir::func::FuncOp"> {
  let summary = "Convert a StableHLO function to bfloat16";
  let dependentDialects = ["mlir::stablehlo::StablehloDialect"];
}

def ConvertXlaCallModuleOpToBfloat16Pass : Pass<"stablehlo-convert-xla-call-module-op-to-bfloat16", "mlir::func::FuncOp"> {
  let summary = "Convert serialized XlaCallModuleOp to bfloat16";

    }

    /**
     * Converts all line separators in the specified string to the specified line separator.
     */
    @Nullable
    public static String convertLineSeparators(@Nullable String str, String sep) {
        return str == null ? null : replaceLineSeparatorsOf(str, sep);
    }

    /**

    }

    /**
     * Each project produces a 'blue' variant, and has a `resolve` task that resolves the 'green' variant and a transform that converts 'blue' to 'red'
     * and another transform that converts 'red' to 'green'.
     * By default the 'blue' variant will contain a single file, and the transform will produce a single 'green' file from this.
     */

// the module.
std::unique_ptr<OperationPass<ModuleOp>> CreateStripNoinlineAttributePass();

// Converts tensor list operations into operations on buffers and sizes. Needs
// static shapes and known max element count.
std::unique_ptr<OperationPass<ModuleOp>> CreateTensorListOpsDecompositionPass();

// Converts tensor array ops into operations on local variables, which can later