#include "mlir/Parser/Parser.h"  // from @llvm-project
#include "mlir/Support/FileUtilities.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_import.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"

namespace mlir {
namespace TFL {
namespace tac {

absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ImportFlatbufferOrMlir(

        } else {
          return tflite::TensorType_INT4;
        }
      case 8:
        return itype.isUnsigned() ? tflite::TensorType_UINT8
                                  : tflite::TensorType_INT8;
      case 16:
        return itype.isUnsigned() ? tflite::TensorType_UINT16
                                  : tflite::TensorType_INT16;
      case 32:
        return itype.isUnsigned() ? tflite::TensorType_UINT32

#include "tensorflow/compiler/mlir/lite/metrics/error_collector.h"
#include "tensorflow/compiler/mlir/lite/metrics/types_util.h"
#include "tensorflow/lite/python/metrics/converter_error_data.pb.h"

namespace mlir {
namespace TFL {

// Collects errors when running the pass manager.
class ErrorCollectorInstrumentation : public PassInstrumentation {
  using ConverterErrorData = tflite::metrics::ConverterErrorData;

#include "mlir/Pass/PassManager.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tensorflow {

// Add the TF to TFLite passes, specified in the pass_config, into a
// pass_manager. The session object will be provided when the TF MLIR is

#include "tensorflow/compiler/mlir/lite/metrics/error_collector.h"
#include "tensorflow/compiler/mlir/lite/metrics/types_util.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_dialect.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/lite/python/metrics/converter_error_data.pb.h"

#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_export_flags.h"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/compiler/mlir/lite/tf_tfl_translate_cl.h"
#include "tensorflow/compiler/mlir/lite/tf_to_tfl_flatbuffer.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"

#include "tensorflow/compiler/mlir/lite/experimental/tac/py_wrapper/tac_wrapper.h"

// Warning: The API is experimental and subject to change.
PYBIND11_MODULE(_pywrap_tac_wrapper, m) {
  m.def(
      "run_tac",
      [](const std::string& model_file_path,
         const std::vector<std::string>& device_specs,
         const std::string& model_output_path) {
        return ::tflite::run_tac(model_file_path, device_specs,

---
name: TensorFlow Lite Op Request
about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace TFL {
namespace {
#define GEN_PASS_DEF_LEGALIZEWHILEPASS
#include "tensorflow/compiler/mlir/lite/transforms/passes.h.inc"

#include <memory>

#include "tensorflow/compiler/mlir/lite/experimental/tac/common/targets.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/utils.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/hardwares/target_hardware.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/utils/arithmetic_count_util.h"

namespace mlir {
namespace TFL {