#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics_collector_min_max.h"

#include <algorithm>
#include <cstdint>
#include <limits>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

namespace tensorflow {
namespace calibrator {

void CalibrationStatisticsCollectorMinMax::ClearData() {

namespace tensorflow {
namespace gradients {
namespace {
class IdentityNGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    for (int i = 0; i < grad_outputs.size(); i++) {
      auto grad_input = grad_outputs[i];

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_STABLEHLO_CC_CALIBRATION_REPRESENTATIVE_DATASET_H_

#include <string>

#include "absl/container/flat_hash_map.h"
#include "absl/status/statusor.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"

namespace stablehlo::quantization {

#include <optional>
#include <string>
#include <unordered_set>
#include <vector>

#include "absl/base/macros.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "tensorflow/cc/saved_model/loader.h"

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_TENSORFLOW_CALIBRATOR_CALIBRATION_STATISTICS_COLLECTOR_MIN_MAX_H_

#include <cstdint>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

  bool UseFunction() const { return std::get<2>(GetParam()); }
};

// Checks that inputs[0] is a scalar.
Status TestScalarShape(AbstractContext* ctx,
                       absl::Span<AbstractTensorHandle* const> inputs,
                       absl::Span<AbstractTensorHandle*> outputs) {
  PartialTensorShape shape;
  TF_RETURN_IF_ERROR(inputs[0]->Shape(&shape));
  if (shape.dims() != 0) {
    return errors::InvalidArgument(

plugins: forked-1.1.3, xdist-1.31.0, cov-2.8.1
collected 6 items

---> 100%

test_main.py <span style="color: green; white-space: pre;">......                            [100%]</span>

<span style="color: green;">================= 1 passed in 0.03s =================</span>
```

#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics_collector_average_min_max.h"

#include <cstdint>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

namespace tensorflow {
namespace calibrator {

void CalibrationStatisticsCollectorAverageMinMax::ClearData() {

// apart from the arg and retval nodes corresponding to `args` and
// `result_types` respectively.
absl::StatusOr<std::unique_ptr<Graph>> CreateSingleOpGraph(
    const NodeDef& node_def, absl::Span<const XlaArgument> args,
    absl::Span<const DataType> result_types);

// Checks if single device compilation and execution with PJRT is enabled for
// `device_type` in either the XlaLaunch op or the XlaCompileOnDemand op.

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_TENSORFLOW_CALIBRATOR_CALIBRATION_STATISTICS_COLLECTOR_AVERAGE_MIN_MAX_H_

#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"