// DISABLE-ALL-DOT-GENERAL: return %[[XLA_CALL_MODULE:.+]] : tensor<1x1x64xf32>
// DISABLE-ALL-DOT-GENERAL: }

// DISABLE-ALL-DOT-GENERAL-LABEL: private @composite_dot_general_fn_1
// DISABLE-ALL-DOT-GENERAL-SAME: tf_quant.composite_function
// DISABLE-ALL-DOT-GENERAL: %[[DOT_GENERAL:.+]] = stablehlo.dot_general %arg0, %arg1
// DISABLE-ALL-DOT-GENERAL: return %[[DOT_GENERAL:.+]] : tensor<1x1x64xf32>
// DISABLE-ALL-DOT-GENERAL: }

// -----

    // For consistency, we require all quantized composite function to have
    // the "tf_quant.quantized_ops" attribute.
    if (!new_func.getSymName().starts_with("quantized_")) continue;
    if (!new_func->hasAttrOfType<ArrayAttr>("tf_quant.quantized_ops")) {
      new_func->emitError() << "Missing \"tf_quant.quantized_ops\" "
                               "attribute in the quantized composite function.";

    func.return %1: tensor<*xf32>
  }
  func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>

      return %1 : tensor<1x4x4x3xf32>
    }
    func.func private @composite_fn_1(%arg0: tensor<1x4x4x3xf32>, %arg1: tensor<3x1x1x3xf32>, %arg2: tensor<3xf32>) -> tensor<1x4x4x3xf32> attributes {tf_quant.composite_function} {

namespace tensorflow {
namespace quantization {

// Default MLIR dump file prefix for TensorFlow quantization passes.
inline constexpr absl::string_view kDefaultTfQuantMlirDumpFilePrefix =
    "tf_quant";

// Preprocesses the `module_op` for quantization. The preprocess steps include
// freezing the variables in the graph into constants. `is_inliner_run`
// determines whether the `InlinerPass` should be run after unfreezing.

namespace mlir::quant {

// This attribute will be set for functions created by this pass.
// Presence of this attribute will mark the function as quantization target.
inline constexpr StringRef kFusedFunctionAttr = "tf_quant.composite_function";
// The keyword to detect if this is a `NullAttribute`.
inline constexpr StringRef kNullAttributeValue = "N/A";

// Prefixes attached to lifted functions.

class NamedAttr<string attr_name> :
    NativeCodeCall<"NamedAttribute{$_builder.getStringAttr(\"" # attr_name # "\"), $0}">;

// Checks if the value is not defined inside a lifted function by checking the
// `tf_quant.composite_function` attribute.
def IsNotInLiftedFunc :
      Constraint<CPred<"!IsInLiftedFunc($0.getDefiningOp())">>;

// Checks if the value is not inside a StableHLO op with region.
def IsNotInStableHloOpRegion :

  // CHECK: return

  func.func private @composite_dot_general_with_relu_fn_1(%arg0: tensor<10x1x1024xf32>, %arg1: tensor<10x1024x3xf32>) -> tensor<10x1x3xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
    %cst = stablehlo.constant dense<0.000000e+00> : tensor<10x1x3xf32>

  // CHECK-LABEL: composite_conv2d_with_bias_and_relu6_fn_10
  func.func private @composite_conv2d_with_bias_and_relu6_fn_10(%arg0: tensor<1x3x2x3xf32>, %arg1: tensor<2x3x3x2xf32>, %arg2: tensor<2xf32>) -> tensor<1x2x2x2xf32> attributes {tf.tf_quant.composite_function} {
    %0 = "quantfork.stats"(%arg1) {layerStats = dense<[-3.54062747, 0.54742622]> : tensor<2xf32>} : (tensor<2x3x3x2xf32>) -> tensor<2x3x3x2xf32>