def ComposeUniformQuantizedTypePass : Pass<"compose-uniform-quantized-type", "ModuleOp"> {
  let summary = "Compose uniform quantized types in StableHLO.";
  let constructor = "mlir::odml::CreateComposeUniformQuantizedTypePass()";
  let description = [{
    Identifies uniform quantization patterns and composes them to uniform
    quantized types. This pass targets a specific set of models that are
    quantized from the framework level, which produces "decomposed"

// RUN: stablehlo-quant-opt %s -stablehlo-test-post-calibration-component='unpack-quantized-types=false' \
// RUN:   -split-input-file | FileCheck %s --check-prefix=CHECK-NO-UNPACK

// Tests that a simple dot_general (lifted as a function) with CustomAggregators
// around it is quantized. The resulting graph has quantized types unpacked into
// int ops.
func.func @main(%arg0: tensor<1x1024xf32>) -> tensor<1x3xf32> {

/// quantized and the operand type is quantizable.

LogicalResult QuantizedConstRewrite::matchAndRewrite(
    QuantizeCastOp qbarrier, PatternRewriter &rewriter) const {
  Attribute value;

  // Is the operand a constant?
  if (!matchPattern(qbarrier.getArg(), m_Constant(&value))) {
    return failure();
  }

  // Does the qbarrier convert to a quantized type. This will not be true

// (e.g. matmul) has both quantized and unquantized inputs by dequantizing
// the quantized inputs, performing the operation in the expressed type, then
// requantizing if a quantized output is required.
//
// The motivation behind these changes is for Dialects that assume only float
// or quantized computation, and do not support a mixture of these types on

// and NumericVerify ops to compare output values from the quantized and float
// ops.
//
// When `legacy_float_scale` is true, the quantizer will use float scale instead
// of double, and call TOCO's quantization routines to maintain bit-exactness of
// the values with the TOCO quantizer.
TfLiteStatus QuantizeModel(
    absl::string_view model_buffer, const tflite::TensorType &input_type,

    // 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.";
      signalPassFailure();

#include "mlir/Pass/Pass.h"  // from @llvm-project

namespace mlir::quant::stablehlo {

// Creates an instance of the ConvertTFQuantOpsToMHLOPass pass, which will
// convert TF uniform quantized ops to the corresponding quantized MHLO ops.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateConvertTFQuantOpsToMHLOPass();

// TODO(b/288094093): Migrate uniform quantization legalization in a separate
// pass.

// RUN: tf-quant-opt %s -quant-insert-quantized-functions='quantization-method=drq' | FileCheck %s
// RUN: tf-quant-opt %s -quant-insert-quantized-functions='quantization-method=drq target-opset=UNIFORM_QUANTIZED' | FileCheck --check-prefix=UQ-CHECK %s

// Empty module
module {
  func.func @simple_fn(%arg0: tensor<*xf32>) -> tensor<*xf32> {
    func.return %arg0 : tensor<*xf32>
  }
}

// CHECK-NOT: func private @internal_calculate_quant_params

// identifies the `MetaGraphDef`. `quantization_config` determines the behavior
// of StableHLO Quantizer. `quantization_py_function_lib` contains python
// implementations of certain APIs that are required for calibration.
// `module_op` is the input graph to be quantized and it should contain
// StableHLO ops.
//
// Returns a quantized `ModuleOp` in StableHLO, potentially wrapped inside a

class RewriteQuantizedIOPass
    : public PassWrapper<RewriteQuantizedIOPass, OperationPass<ModuleOp>> {
 public:
  StringRef getArgument() const final { return "tfr-rewrite-quantized-io"; }

  StringRef getDescription() const final {
    return "Replaces operands and results that has quantized type with their "
           "storage types.";
  }
  void runOnOperation() override;
};

void RewriteQuantizedIOPass::runOnOperation() {