experimental_debug_info {
        original_node_names: "const_2"
      }
    }
    ret {
      key: "bar"
      value: "const_2:output:0"
    }
  }
  function {
    signature {
      name: "foo"
      output_arg {
        name: "foo"
        type: DT_FLOAT
      }
    }
    node_def {
      name: "const_1"
      op: "Const"
      attr {
        key: "dtype"
        value {

(Lsh32x64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Rsh32x64 x (Int64Make (Const32 [c]) _)) && c != 0 => (Signmask x)
(Rsh32Ux64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Lsh16x64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])
(Rsh16x64 x (Int64Make (Const32 [c]) _)) && c != 0 => (Signmask (SignExt16to32 x))
(Rsh16Ux64 _ (Int64Make (Const32 [c]) _)) && c != 0 => (Const32 [0])

  // CHECK: %[[CONST1:.*]] = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
  %const1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
  // CHECK: %[[SUB:.*]] = "tf.Sub"(%[[BARG1]], %[[CONST1]])
  %sub = "tf.Sub"(%arg1, %const1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %elem = "tf._SomeOp"() : () -> tensor<3xf32>

// COM: CHECK-DAG: %[[CONST:.*]] = stablehlo.constant dense<{{.*}}> : tensor<1x1x2x8xf32>
// COM: CHECK: return %[[CONST]] : tensor<1x1x2x8xf32>

func.func @fused_batchnorm_no_training_arg_input(%arg_0: tensor<1x1x2x8xf32>) -> (tensor<1x1x2x8xf32>) {
  %cst_0 = "tf.Const"() {value = dense<[0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2]> : tensor<8xf32>} : () -> tensor<8xf32>

absl::StatusOr<Node*> ReplaceFunctionCallWithPartitionedCall(
    const GraphOptimizationPassOptions& options,
    const FunctionLibraryDefinition& flib_def, Node* n, Graph* g,
    const NameAttrList& func, const Scope& root) {
  string config_string = options.session_options->config.SerializeAsString();

  int input_count = absl::c_count_if(
      n->in_edges(), [](const Edge* e) { return !e->IsControlEdge(); });

namespace tac {
namespace {

// This pass is used to fold tfl.const ops to each subgraph (func::FuncOp):
// See the example below:
//
// In main:
// %0 = tfl.const...
// %1 = tfl.const...
// %2 = call func_1(..., %0,...)
// %3 = call func_2(..., %0, ..., %1...)
// ...
//
// Then those consts will be copied into each function and replace their usage.
// func_1:
//   %0 = tfl.const...
// func_2:
//   %0 = tfl.const...

)

// numeric constant conversions are in const1.src.

func string_conversions() {
	const A = string(65)
	assert(A == "A")
	const E = string(-1)
	assert(E == "\uFFFD")
	assert(E == string(1234567890))

	type myint int
	assert(A == string(myint(65)))

	type mystring string
	const _ mystring = mystring("foo")

	const _ = string(true /* ERROR "cannot convert" */ )
	const _ = string(1.2 /* ERROR "cannot convert" */ )

package constdecl

import "math"
import "unsafe"

var v int

// Const decls must be initialized by constants.
const _ = v /* ERROR "not constant" */
const _ = math /* ERROR "not constant" */ .Sin(0)
const _ = int /* ERROR "not an expression" */

func _() {
	const _ = v /* ERROR "not constant" */
	const _ = math /* ERROR "not constant" */ .Sin(0)
	const _ = int /* ERROR "not an expression" */
}

// CHECK-DAG: %[[CONST_8:.*]] = "tf.Const"() <{value = dense<[162, 160]> : tensor<2xi32>}> : () -> tensor<2xi32>
// CHECK: %[[PADV2_0:.*]] = "tf.PadV2"({{.*}}, %[[CONST_4]], %[[CONST_5]]) : (tensor<1x3x4x3xi8>, tensor<4x2xi32>, tensor<i8>) -> tensor<1x4x5x3xi8>
// CHECK: %[[XLACONVV2_0:.*]] = "tf.XlaConvV2"(%[[PADV2_0]], %[[CONST_6]], %[[CONST_0]], %[[CONST_3]], %[[CONST_1]], %[[CONST_1]], %[[CONST_2]])

// license that can be found in the LICENSE file.

// Issue 20185: type switching on untyped values (e.g. nil or consts)
// caused an internal compiler error.

package p

func F() {
	switch t := nil.(type) { // ERROR "cannot type switch on non-interface value|not an interface"
	default:
		_ = t
	}
}

const x = 1

func G() {