See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"

#include <stddef.h>
#include <stdlib.h>

#include <algorithm>
#include <cassert>
#include <cstdint>
#include <cstdio>
#include <cstring>
#include <iterator>
#include <limits>

Chuan He <******@****.***> 1699497939 -0800

#include "mlir/Pass/PassManager.h"  // from @llvm-project
#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"

    ],
)

cc_library(
    name = "flatbuffer_translate_lib",
    hdrs = [
        "flatbuffer_export.h",
        "flatbuffer_export_flags.h",
        "flatbuffer_import.h",
        "utils/convert_type.h",
    ],
    deps = [
        ":flatbuffer_export",
        ":flatbuffer_import",
        "//tensorflow/compiler/mlir:op_or_arg_name_mapper",

// dependent on side effects. Reflects the current runtime logic; see below.
bool OpHasSideEffects(Operation *op) {
  // Note that TFL::IfOp are only ever instantiated in flatbuffer_export; until
  // then, they are represented as mlir::TF::IfOp. We add them here, anyway, to
  // be future-proof.
  if (llvm::isa<TF::IfOp, TFL::IfOp, TFL::CallOnceOp, TFL::WhileOp>(op))
    return true;

#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 {

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#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"

#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 "mlir/IR/Dialect.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/Parser/Parser.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/flatbuffer_export.h"
#include "tensorflow/compiler/mlir/lite/flatbuffer_export_flags.h"
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

  // flatbuffer file.
  if (auto custom_op = dyn_cast<mlir::TFL::CustomOp>(*op)) {
    return custom_op.getCustomCode().starts_with("Flex");
  }

  // We never see TFL::IfOps in the IR -- it is flatbuffer_export that rewrites
  // them from TF::IfOps.
  if (isa<TF::IfOp>(op)) {
    return false;
  }

  // We assume all other TF operators are flex delegated.
  return op->getDialect()->getNamespace() == "tf";
}