flex_builder->Bool(name.c_str(),
                         array[i].cast<mlir::BoolAttr>().getValue());
    } else if (llvm::isa<mlir::StringAttr>(attr)) {
      flex_builder->String(name.c_str(),
                           array[i].cast<mlir::StringAttr>().getValue().str());
    } else if (llvm::isa<mlir::vhlo::BooleanV1Attr>(array[i])) {
      flex_builder->Bool(name.c_str(),

  // Permute filter sizes operand.
  OpBuilder builder(getOperation());
  auto filter_sizes_permuted = builder.create<TF::DataFormatVecPermuteOp>(
      getLoc(), getFilterSizes(),
      StringAttr::get(getContext(), src_data_format),
      StringAttr::get(getContext(), data_format));
  setOperand(1, filter_sizes_permuted);

  return success();
}

StringRef Conv2DBackpropFilterOp::GetOptimalLayout(

mlir::Value GetFcOutput(OpBuilder *builder,
                        ::mlir::Operation::result_range result, Value input,
                        Value filter, Value bias,
                        StringAttr fused_activation_function,
                        StringAttr weights_format, BoolAttr keep_num_dims,
                        BoolAttr asymmetric_quantize_inputs) {
  auto fc_op = builder->create<FullyConnectedOp>(

  NameUniquifier* function_name_uniquifier_;
  mlir::StatusScopedDiagnosticHandler error_handler_;
  // All the TF ops encountered that aren't modelled in dialect.
  llvm::DenseSet<mlir::StringAttr> unmodelled_op_names_;

 protected:
  // Maps feed as TensorId to new Placeholder node name.
  absl::flat_hash_map<TensorId, absl::string_view> remapped_feeds_;

    std::vector<std::string> disabled_checks;
    for (auto attr : op.getDisabledChecks().getAsRange<StringAttr>()) {
      disabled_checks.push_back(attr.getValue().str());
    }
    std::vector<std::string> platforms;
    for (auto attr : op.getPlatforms().getAsRange<StringAttr>()) {
      platforms.push_back(attr.getValue().str());
    }

    Type result_type = op.getResult(0).getType();
    Value input = op.getOperand(0);
    // Ops with padding is rejected in matching function, so we can use the
    // padding to be 'VALID'.
    StringAttr padding = rewriter.getStringAttr("VALID");

    // Use NHWC format.
    int32_t stride_h = 1;
    int32_t stride_w = 1;
    std::optional<ArrayRef<int64_t>> window_strides = op.getWindowStrides();

def TFL_BoolFalse : AttrConstraint<
    CPred<"$_self.isa<BoolAttr>() && !$_self.cast<BoolAttr>().getValue()">,
    "whose value is false">;

class TFL_StringEqualsTo<string value> : AttrConstraint<
    CPred<"$_self.cast<StringAttr>().getValue() == \"" # value # "\"">,
    "whose value equals to '" # value # "'">;

// Ensures the array attribute's size is within the given maximum size.
class TFL_ArrayMaxCount<int n> : AttrConstraint<

// For `NcclAllReduceOp` ops the `device` attribute corresponds to the resource
// instance.
std::optional<std::string> NcclAllReduceOp::GetResourceInstanceStr() {
  auto device_attr = (*this)->getAttrOfType<StringAttr>("device");
  // Treat missing device attribute like unspecified (= empty string) attribute.
  // Note that different op instances with the same string (including empty

  }
}

void buildFusedBroadcastableBinOp(Builder* builder, OperationState& result,
                                  Value lhs, Value rhs,
                                  StringAttr fused_activation_function) {
  auto result_type =
      OpTrait::util::getBroadcastedType(lhs.getType(), rhs.getType());

  if (!result_type)
    emitError(result.location)