"""StableHLO Quantizer."""
from typing import Mapping

from tensorflow.compiler.mlir.quantization.stablehlo import quantization_config_pb2 as qc
from tensorflow.compiler.mlir.quantization.stablehlo.python import pywrap_quantization
from tensorflow.compiler.mlir.quantization.tensorflow.python import py_function_lib
from tensorflow.compiler.mlir.quantization.tensorflow.python import save_model
from tensorflow.core.protobuf import meta_graph_pb2

             !interleave([bias, op1, op2], ", "),
             ">::Impl")>;

// Specify the operand index of the coefficient operand for an affine op
// and also the quantization dimension if per-axis quantization is support.
// If the quantization dimension is -1, per-axis quantization isn't supported.
class AffineOpCoefficient<int dim, int index> : NativeOpTrait<
  !strconcat("quant::AffineOpCoefficient<",
             !interleave([dim, index], ", "),

Christian Sigg <******@****.***> 1714640622 -0700

#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/config.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/static_range_ptq.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/cc/weight_only_ptq.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"

#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/python/py_function_lib.h"

namespace tensorflow {

// Runs quantization on `module_op`. `saved_model_bundle` is required to
// retrieve information about the original model (e.g. signature def mapping)
// because quantization requires exporting the intermediate `ModuleOp` back to

A. Unique TensorFlower <******@****.***> 1704479080 -0800

// RUN: tf-opt --tfl-decompose-hybrid-quantization --verify-each %s | FileCheck %s

// CHECK-LABEL: @test_conv2d_float
func.func @test_conv2d_float(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x16xf32> {
  // CHECK-DAG: %[[VAL0:.+]] = "tfl.pseudo_const"() <{value = dense<42> : tensor<16x1x1x8xi8>}>
  // CHECK-DAG: %[[VAL1:.+]] = "tfl.pseudo_const"() <{value = dense<1> : tensor<16x1x1x8xi8>}>

  // activation of static range quantization (SRQ). Quantization calibration
  // method is set to MIN_MAX by default.
  stablehlo.quantization.CalibrationOptions calibration_options = 15;

  // Configuration related to quantization debugger.
  stablehlo.quantization.DebuggerConfig debugger_config = 16;

  reserved 3;

                     "array to apply quantization.")};

  Option<QuantMethod> quantization_method_{
      *this, "quantization-method",
      llvm::cl::init(tensorflow::quantization::QuantizationMethod::
                         METHOD_DYNAMIC_RANGE_INT8),
      llvm::cl::desc("Choose quantization method."),
      llvm::cl::values(
          clEnumValN(tensorflow::quantization::QuantizationMethod::

namespace {

using QuantMethod =
    ::tensorflow::quantization::QuantizationMethod::PresetMethod;
using QuantizationUnit = std::pair<Operation*, int>;
using QuantizationUnits = llvm::SetVector<QuantizationUnit>;
using ::tensorflow::quantization::OpSet;

// Preprocesses ops to allow multi-axis quantization, prior to quantization
// passes. Currently, per-channel quantization only supports 1D results.
class PreprocessOpPass