std::vector<bool> const_args(arg_types.size());
  // If we can't analyze the const args. Bail out.
  TF_RETURN_IF_ERROR(
      BackwardsConstAnalysis(*((*fbody)->graph), &const_args,
                             /*compile_time_const_nodes=*/nullptr, flr));

  for (size_t i = 0; i < const_args.size(); ++i) {
    if (const_args[i]) {
      constant_arg_indices->push_back(i);
    }
  }

        OptimizeGraph(flr, subgraph, graph_optimizer_options);

        const int num_args = input_permutation->size();
        std::vector<bool> const_args(num_args);
        TF_RETURN_IF_ERROR(
            BackwardsConstAnalysis(**subgraph, &const_args,
                                   /*compile_time_const_nodes=*/nullptr, flr));

        DataTypeVector arg_types(num_args);

package types

import (
	"go/constant"
	. "internal/types/errors"
	"unicode"
)

// conversion type-checks the conversion T(x).
// The result is in x.
func (check *Checker) conversion(x *operand, T Type) {
	constArg := x.mode == constant_

	constConvertibleTo := func(T Type, val *constant.Value) bool {
		switch t, _ := under(T).(*Basic); {
		case t == nil:
			// nothing to do
		case representableConst(x.val, check, t, val):

package types2

import (
	"go/constant"
	. "internal/types/errors"
	"unicode"
)

// conversion type-checks the conversion T(x).
// The result is in x.
func (check *Checker) conversion(x *operand, T Type) {
	constArg := x.mode == constant_

	constConvertibleTo := func(T Type, val *constant.Value) bool {
		switch t, _ := under(T).(*Basic); {
		case t == nil:
			// nothing to do
		case representableConst(x.val, check, t, val):

class DataStructureModel(module.Module):
  """Model used for testing data structures in the C++ API."""

  def __init__(self):
    self.arr1 = [1.]
    self.const_arr = [constant_op.constant(1.)]
    self.var_arr = [variables.Variable(1.), variables.Variable(2.)]
    self.dict1 = {"a": 1.}
    self.var_dict = {"a": variables.Variable(1.), "b": variables.Variable(2.)}

                 (Arith_ConstantOp:$const_axes I32ElementsAttr:$axes)),
    (ArgMinMaxOp $logits, $const_axes),
    [(HasOneUse $softmax),
     (AxesIsLastDimension $axes, $logits)]>;

  def RemoveLogSoftmaxOpBefore#ArgMinMaxOp : Pat<
    (ArgMinMaxOp (TFL_LogSoftmaxOp:$log_softmax $logits),
                 (Arith_ConstantOp:$const_axes I32ElementsAttr:$axes)),
    (ArgMinMaxOp $logits, $const_axes),

    TensorOf<[TF_Float16, TF_Float32, TF_Float64, TF_Int8, TF_Qint8]>:$input,
    TensorOf<[TF_Float16, TF_Float32, TF_Float64, TF_Int8, TF_Qint8]>:$filter,
    Variadic<TF_Tensor>:$args,
    Variadic<TF_Float32Tensor>:$host_args,

    ConfinedAttr<I64Attr, [IntMinValue<0>]>:$num_args,
    I64ArrayAttr:$strides,
    TF_AnyStrAttrOf<["SAME", "VALID", "EXPLICIT"]>:$padding,