(Xor(64|32|16|8) x x) => (Const(64|32|16|8) [0])
(Xor(64|32|16|8) (Const(64|32|16|8) [0]) x) => x
(Xor(64|32|16|8) (Com(64|32|16|8)    x)  x) => (Const(64|32|16|8) [-1])

(Add(64|32|16|8) (Const(64|32|16|8) [0]) x) => x
(Sub(64|32|16|8) x x) => (Const(64|32|16|8) [0])
(Mul(64|32|16|8) (Const(64|32|16|8) [0]) _) => (Const(64|32|16|8) [0])
(Select0 (Mul(64|32)uover (Const(64|32) [0]) x)) => (Const(64|32) [0])

		v0.AuxInt = int64ToAuxInt(int64(math.Float64bits(val)))
		v.AddArg(v0)
		return true
	}
}
func rewriteValueRISCV64_OpConst8(v *Value) bool {
	// match: (Const8 [val])
	// result: (MOVDconst [int64(val)])
	for {
		val := auxIntToInt8(v.AuxInt)
		v.reset(OpRISCV64MOVDconst)
		v.AuxInt = int64ToAuxInt(int64(val))
		return true
	}
}

  // CHECK-DAG: %[[CONST1:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}>
  // CHECK-DAG: %[[CONST2:.*]] = "tf.Const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}>
  // CHECK: %[[TRANS1:.*]] = "tf.Transpose"(%arg0, %[[CONST1]]) : (tensor<1x4x4x8xf32>, tensor<4xi32>) -> tensor<1x8x4x4xf32>

  %index_in_list = "tf.Const"() {value = dense<0> : tensor<1xi32>} : () -> tensor<1xi32>
  %arg0_shape = "tf.Const"() {value = dense<[1, 8, 4]> : tensor<3xi32>} : () -> tensor<3xi32>
  %arg0_reshaped = "tf.Reshape"(%arg0, %arg0_shape) : (tensor<8x4xf32>, tensor<3xi32>) -> tensor<1x8x4xf32>
  %zeroi2 = "tf.Const"() {value = dense<0> : tensor<2xi32>} : () -> tensor<2xi32>

}

void TF_SetAttrString(TF_OperationDescription* desc, const char* attr_name,
                      const void* value, size_t length) {
  tensorflow::StringPiece s(static_cast<const char*>(value), length);
  desc->node_builder.Attr(attr_name, s);
}

void TF_SetAttrStringList(TF_OperationDescription* desc, const char* attr_name,
                          const void* const* values, const size_t* lengths,

  TFL::QConstOp GetBiasOp(
      stablehlo::ConvolutionOp op, PatternRewriter& rewriter,
      const RankedTensorType new_filter_result_type,
      const UniformQuantizedPerAxisType new_filter_quantized_type,
      const SmallVector<int64_t, 1> bias_shape, const bool has_i32_output,
      const bool fuse_bias_constant) const {
    const SmallVector<double> bias_scales = GetBiasScales(
        /*input_scale=*/GetElementType(op.getOperand(0))

TF_ATTRIBUTE_NOINLINE Status BuildHostGraphForIfNode(
    const string& xla_cluster_attr_name,
    const string& outside_compilation_attr_name, const string& xla_cluster_name,
    const string& if_node_name, const string& host_transfer_key,
    const string& host_graph_func_name, FunctionLibraryDefinition* fld,
    const string& then_branch_host_func_name,
    const string& else_branch_host_func_name) {
  Graph host_graph(fld);

}

template <class Tkey, class Tvalue>
bool EqualProtoMap(const ::tensorflow::protobuf::Map<Tkey, Tvalue>& a,
                   const ::tensorflow::protobuf::Map<Tkey, Tvalue>& b,
                   const std::function<string(const Tkey&)>& key_to_string,
                   const std::function<string(const Tvalue&)>& value_to_string,
                   const std::function<bool(const Tkey&, const Tvalue&,

      mlir::MLIRContext* context, const Graph& graph,
      const GraphDebugInfo& debug_info,
      const FunctionLibraryDefinition& flib_def, const GraphImportConfig& specs,
      std::unordered_map<std::string, std::string>& tf_name_to_mlir_name,
      bool disable_crash_analysis = false);

 private:
  explicit GraphDefImporter(
      const FunctionLibraryDefinition& flib, const GraphDebugInfo& debug_info,

      const std::vector<int32_t>& results);

  BufferOffset<tflite::Operator> BuildCustomOperator(
      Operation* inst, mlir::TFL::CustomOp op,
      const std::vector<int32_t>& operands,
      const std::vector<int32_t>& results);

  std::optional<CustomOptionsOffset> CreateFlexOpCustomOptions(
      const ::tensorflow::NodeDef& node_def, const mlir::Location& loc);