"""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: odml-to-stablehlo-opt %s --tf-stablehlo=skip-quantization-ops=true | FileCheck %s --check-prefix=CHECK-SKIP
// RUN: odml-to-stablehlo-opt %s --tf-stablehlo=skip-quantization-ops=false | FileCheck %s --check-prefix=CHECK-NOSKIP

func.func @fake_quant_with_min_max_vars(%arg0: tensor<1x1x28x48xf32>, %arg1: tensor<f32>, %arg2: tensor<f32>) -> tensor<1x1x28x48xf32> {

  // 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::

      llvm::cl::values(
          clEnumValN(tensorflow::quantization::QuantizationMethod::
                         METHOD_STATIC_RANGE_INT8,
                     "ptq", "Post-training static-range quantization"),
          clEnumValN(tensorflow::quantization::QuantizationMethod::
                         METHOD_DYNAMIC_RANGE_INT8,
                     "drq", "Post-training dynamic-range quantizaiton"),