defer os.RemoveAll(dir)

	const bitLimit = 512
	const charLimit = 10000 // compiler-internal constant length limit
	testProg(dir, "x1", bitLimit, "")
	testProg(dir, "x2", bitLimit+1, "constant overflow")
	testProg(dir, "x3", charLimit-2, "constant overflow") // -2 because literal contains 0b prefix
	testProg(dir, "x4", charLimit-1, "excessively long constant")

namespace mlir {
namespace quant {

// Applies constant folding recursively if the operation and all of its operands
// are foldable. Returns the constants generated by constant-folding or the
// original operation's outputs if not folded.
SmallVector<Value> ConstantFoldOpIfPossible(Operation* op);

// This pattern tries to constant-fold the quantizable operands of supported
// TF operations.

// -----

// CHECK-LABEL: @mhlo_while
func.func private @mhlo_while() {
  // CHECK-NEXT: mhlo.constant
  // CHECK-NEXT: mhlo.constant
  // CHECK-NEXT: mhlo.constant
  %0 = mhlo.constant dense<-1> : tensor<i32>
  %1 = mhlo.constant dense<0> : tensor<i32>
  %2 = mhlo.constant dense<20> : tensor<i32>
  // CHECK-NEXT: mhlo.while

// Checks if the value is a float constant and its splat value is equal to `x`.
class IsSplatValueEqual<string x> : Constraint<CPred<
  "IsSplatValueEqual<float>($0, "# x #")">>;

// Checks if two values are float constants and their values are equal.
def AreSplatValuesEqual : Constraint<CPred<
  "AreSplatValuesEqual<float>($0, $1)">>;

// Checks if the value is an integer constant and its splat value is equal to x.

namespace tensorflow {


// XlaLocalLaunchBase is almost the same as XlaLocalLaunchOp.
// The only difference is that it does not require arguments to follow
// the "constants, then regular args, then resources" order.
// It takes vectors of constant and resource arguments explicitly.
// It does not have corresponding OpDef because it is never present
// in the GraphDef.

			_, _ = fmt.Fprintln(&b, "COMMIT")
		}
	}
	return b.String()
}

func (rb *IptablesRuleBuilder) buildRestore(rules []*Rule) string {
	tableRulesMap := map[string][]string{
		constants.FILTER: {},
		constants.NAT:    {},
		constants.MANGLE: {},
	}

	chainTableLookupMap := sets.New[string]()
	for _, r := range rules {
		chainTable := fmt.Sprintf("%s:%s", r.chain, r.table)

these constants are written to `zerrors_${GOOS}_${GOARCH}.go` via a C program,
`_errors.c`, which prints out all the constants.

To add a constant, add the header that includes it to the appropriate variable.
Then, edit the regex (if necessary) to match the desired constant. Avoid making
the regex too broad to avoid matching unintended constants.

### internal/mkmerge

std::unique_ptr<OperationPass<func::FuncOp>> createConvertSimulatedQuantPass();

/// Creates a pass that converts constants followed by a qbarrier to a
/// constant whose value is quantized. This is typically one of the last
/// passes done when lowering to express actual quantized arithmetic in a
/// low level representation. Because it modifies the constant, it is
/// destructive and cannot be undone.

from tensorflow.tools.proto_splitter import constants
from tensorflow.tools.proto_splitter.python import saved_model as proto_splitter

SPLITTER_TESTDATA_PATH = flags.DEFINE_string(
    "path", None, help="Path to testdata directory.")


def generate_non_chunked_model(non_chunked_dir: str):
  root = module.Module()
  root.c = constant_op.constant(np.random.random_sample([150, 150]))
  constants.debug_set_max_size(80000)

      the second argument is the zero point constant (element type: int) and
      the third argument is the inverse scale constant (element type: float).
    * A tensor is dequantized using a `func::FuncOp` whose name contains
      "uniform_dequantize". The first argument is the tensor to be quantized,
      the second argument is the zero point constant (element type: int) and