(TFL_HardSwishOp $input)>;

def IsNchwLayoutOp: Constraint<CPred<
  "$0.get(\"is_nchw_op\") && $0.get(\"is_nchw_op\").dyn_cast<BoolAttr>() "
      "== mlir::BoolAttr::get($_builder.getContext(), true)">>;

def IsNhwcLayoutOp: Constraint<Neg<IsNchwLayoutOp.predicate>>;

// TODO(b/343278954): Move the creation of transposes to a separate prepare pass

// Receives a composite DictionaryAttr as an argument and checks if has a
// BoolAttr with the name `attr_name` and value `val`.
class IsBoolCompositeAttribute <string attr_name, string val>:
  IsCompositeAttribute<attr_name, BoolAttr, val>;

// Receives a composite DictionaryAttr as an argument and checks if has a
// StrAttr with the name `attr_name` and value `val`.

Type DeduceEqualCmpOpType(Builder *builder, Location loc, Value x, Value y,
                          BoolAttr incompatible_shape_error);

Type InferReductionOpType(Value input, Value reduction_indices,
                          BoolAttr keep_dims);

// Verifies that the given types are cast compatible. If not, emits appropriate

// incompatible shapes. Otherwise, returns a tensor type with unknown rank.
Type DeduceEqualCmpOpType(Builder *builder, Location loc, Value x, Value y,
                          BoolAttr incompatible_shape_error) {
  auto result_type =
      OpTrait::util::getBroadcastedType(x.getType(), y.getType());
  if (!result_type) {
    if (incompatible_shape_error.getValue()) {

    // If TFLite variable legalization is not allowed, then we skip this pass.
    if (auto legalize_tfl_variables_attr =
            module->getAttr(kLegalizeTflVariables)) {
      if (!mlir::cast<BoolAttr>(legalize_tfl_variables_attr).getValue()) return;
    }

    RewritePatternSet patterns(&getContext());
    populateWithGenerated(patterns);
    (void)applyPatternsAndFoldGreedily(module, std::move(patterns));
  }
};

std::optional<bool> GetBoolFromCompositeAttr(
    const DictionaryAttr& composite_attrs, llvm::StringRef attr_name) {
  auto attr = composite_attrs.get(attr_name);
  if (!attr) return std::nullopt;
  if (auto bool_attr = mlir::dyn_cast_or_null<BoolAttr>(attr)) {
    return bool_attr.getValue();
  }
  return std::nullopt;
}

ShapedType GetNhwcReturnTypeFromNchw(Operation* old_op) {
  auto composite_result_shape =

}

def TF_DumpTensorOp : TF_Op<"DumpTensor", []> {
  let summary = "Dump tensor proto.";

  let arguments = (ins
    Arg<TF_Tensor>:$input,

    StrAttr:$log_dir_path,
    StrAttr:$file_name,
    BoolAttr:$enabled,
    StrAttr:$func_name,
    StrAttr:$node_name
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;

        legalize_to_tfl = false;
        return WalkResult::interrupt();
      }
    }
    return WalkResult::advance();
  });
  module->setAttr(kLegalizeTflVariables,
                  BoolAttr::get(context, legalize_to_tfl));
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateAnalyzeVariablesPass() {
  return std::make_unique<AnalyzeVariablesPass>();
}

}  // namespace TFL

  // to stateful, otherwise the op will not be executed.
  OpBuilder builder(&ctx);
  module_op.walk([&builder](Operation* op) {
    if (op->hasAttrOfType<BoolAttr>("is_stateless") &&
        ContainCalibrationStatisticsSaverOp(op)) {
      op->setAttr("is_stateless", builder.getBoolAttr(false));
    }
  });
}

std::unique_ptr<OperationPass<ModuleOp>>

    // attribute to create the quantization parameter for the new quantize op.
    rewriter.setInsertionPointAfter(tf_op.getOperation());
    IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.getNumBits());
    BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.getNarrowRange());
    Type res_type = tf_op.getType();
    TypeAttr qtype = quant::GetQuantizedTypeAttr(
        rewriter, res_type, min_value, max_value, quant_dim, num_bits,