#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/debug/debug.h"
#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"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/compiler/mlir/lite/tf_tfl_passes.h"

#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/core/model_builder.h"
#include "tensorflow/lite/tools/optimize/reduced_precision_support.h"

namespace mlir {
namespace lite {
namespace {


TEST(SparsifyModelTest, MetadataIsAddedToOutputModel) {
  std::string expected_key = tflite::optimize::kTfLiteReducedPrecisionKey;

#include "absl/container/flat_hash_set.h"
#include "flatbuffers/flatbuffer_builder.h"  // from @flatbuffers
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/c/c_api_types.h"
#include "tensorflow/lite/model.h"

namespace mlir {
namespace lite {

// Supported resulting types from quantization process.
enum class BufferType { QUANTIZED_INT8, QUANTIZED_FLOAT16 };

        } 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

func (x *Float) validate0() string {
	if x.form != finite {
		return ""
	}
	m := len(x.mant)
	if m == 0 {
		return "nonzero finite number with empty mantissa"
	}
	const msb = 1 << (_W - 1)
	if x.mant[m-1]&msb == 0 {
		return fmt.Sprintf("msb not set in last word %#x of %s", x.mant[m-1], x.Text('p', 0))
	}
	if x.prec == 0 {
		return "zero precision finite number"
	}
	return ""
}

       *   `tflite::Interpreter::signature_keys`
       *   `tflite::Interpreter::signature_inputs`
       *   `tflite::Interpreter::signature_outputs`
       *   `tflite::Interpreter::input_tensor_by_signature`
       *   `tflite::Interpreter::output_tensor_by_signature`

    *  Similarly, the following signature runner functions in the TF Lite C API are no longer considered experimental:

       *    `TfLiteInterpreterGetSignatureCount`

#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_import.h"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/compiler/mlir/lite/tf_tfl_passes.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"

    return -1;
  }

  // Set num of string
  //
  // NOTE: The string buffer is accessed here as if it's native endian (instead
  // of small endian, as documented in the header). This will protentially break
  // when TFLite is ported to big endian platforms.
  // TODO(b/165919229): This code will need changing if/when we port to a
  // big-endian platform.
  memcpy(*buffer, &num_strings, sizeof(int32_t));

  // Set offset of strings.

#include "tensorflow/compiler/mlir/lite/common/tfl_pass_config.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_import.h"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"
#include "tensorflow/compiler/mlir/lite/utils/convert_type.h"

#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/targets.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/hardwares/target_hardware.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/runtime_metadata_generated.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.h"