if (info.params_size() == 0) return;

  SmallVector<APFloat, 4> min_maxs;
  min_maxs.reserve(info.params_size() * 2);
  for (const auto &param : info.params()) {
    llvm::APFloat min(param.min_max().min());
    llvm::APFloat max(param.min_max().max());
    min_maxs.push_back(min);
    min_maxs.push_back(max);
  }
  // The layer stats contain only the first min/max pairs.

  if (mins.size() != maxs.size() || mins.empty()) return nullptr;

  llvm::SmallVector<llvm::APFloat, 4> min_maxs;
  min_maxs.reserve(mins.size() * 2);
  for (int i = 0, end = mins.size(); i < end; ++i) {
    llvm::APFloat min(mins[i]);
    llvm::APFloat max(maxs[i]);
    min_maxs.push_back(min);
    min_maxs.push_back(max);
  }
  // The layer stats contain only the first min/max pairs.

    int32 zero_point = 2;
  }

  // Params to quantize the axis. Only one of the field can be used.
  message PerAxisParams {
    oneof params_oneof {
      // min/max of the ranges.
      MinMax min_max = 1;

      // affine parameters to quantize the per axis value.
      AffineParams affine_params = 2;
    }
  }

  // The metadata defines the target properties.
  message Metadata {

Matthew Dempsky <******@****.***> 1684455363 -0700

// RUN: tf-opt %s -quant-import-stats --quant-test-stats='entries { name: "op" params { min_max { min: -1 max: 1 } } } entries { name: "op_0:0" params { min_max { min: -2 max: 2 } } }  entries { name_regex: "op_*" params { min_max { min: -3 max: 3 } } }' | FileCheck %s


// CHECK-LABEL: import_stats_skip
func.func @import_stats_skip(%arg0: tensor<4xf32>, %cst: tensor<i32>) -> (tensor<2xf32>,tensor<2xf32>) {

entries {
  name: "Add"
  params {
    min_max {
      min: -1
      max: 1
    }
  }

          return;
        }

        auto min_max = GetMinMaxValuesForArgument(func_name, i);
        // The input min/max or mean/std are not specified, then skip.
        if (!min_max.first.has_value() || !min_max.second.has_value()) return;

        TypeAttr params = quant::GetQuantizedTypeAttr(
            builder, input_type, builder.getF64FloatAttr(min_max.first.value()),

          return;
        }

        auto min_max = GetMinMaxValuesForArgument(func_name, i);
        // The input min/max or mean/std are not specified, then skip.
        if (!min_max.first.has_value() || !min_max.second.has_value()) return;

        TypeAttr params = quant::GetQuantizedTypeAttr(
            builder, input_type, builder.getF64FloatAttr(min_max.first.value()),

      if (flag.has_mean_value() && flag.has_std_value()) {
        TF_ASSIGN_OR_RETURN(
            auto min_max, InputStatsToMinMax(flag.mean_value(),
                                             flag.std_value(), inference_type));
        node_mins->push_back(min_max.first);
        node_maxs->push_back(min_max.second);
      } else {
        node_mins->push_back(std::nullopt);
        node_maxs->push_back(std::nullopt);

// Copyright 2017 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

#include "textflag.h"

// Minimax polynomial coefficients and other constants
DATA ·acosrodataL13<> + 0(SB)/8, $0.314159265358979323E+01   //pi
DATA ·acosrodataL13<> + 8(SB)/8, $-0.0
DATA ·acosrodataL13<> + 16(SB)/8, $0x7ff8000000000000    //Nan
DATA ·acosrodataL13<> + 24(SB)/8, $-1.0