limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/save_variables.h"

#include <string>
#include <utility>
#include <vector>

#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

Dan Suh <******@****.***> 1671674377 -0800

        "//tensorflow/compiler/mlir/quantization:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "save_variables",
    srcs = ["save_variables.cc"],
    hdrs = ["save_variables.h"],
    compatible_with = get_compatible_with_portable(),
    deps = [
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/core:framework",

#include "mlir/Pass/PassManager.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/run_passes.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/save_variables.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/passes/passes.h"
#include "tensorflow/core/platform/env.h"
#include "tsl/platform/errors.h"
#include "tsl/platform/status.h"
#include "tsl/platform/statusor.h"

limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/mlir/quantization/tensorflow/cc/save_variables.h"

#include <string>
#include <vector>

#include "absl/cleanup/cleanup.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_format.h"

  TensorShape shape(std::get<1>(test_params));

  SavedVariable saved_variable;
  saved_variable.set_dtype(dtype);
  saved_variable.set_device("/job:localhost/replica:0/task:0/device:CPU:99"),
      shape.AsProto(saved_variable.mutable_shape());

  std::unique_ptr<Variable> var;
  ASSERT_NE(absl::OkStatus(),
            internal::LoadSavedVariable(context(), saved_variable, &var));
}

// Creates a tensorflow::Variable from a SavedVariable. This is similar to the
// logic in:
// https://github.com/tensorflow/tensorflow/blob/516608035f85cec8b126712b0ff8407220206b22/tensorflow/python/saved_model/load.py#L407
// Note that the caller **must assign a value** to the loaded variable.
Status LoadSavedVariable(ImmediateExecutionContext* ctx,
                         const SavedVariable& variable,

// https://github.com/tensorflow/tensorflow/blob/516608035f85cec8b126712b0ff8407220206b22/tensorflow/python/saved_model/load.py#L407
Status LoadSavedVariable(ImmediateExecutionContext* ctx,
                         const SavedVariable& variable,
                         std::unique_ptr<Variable>* output) {
  const std::string& name = variable.name();
  tensorflow::TensorShape shape(variable.shape());
  tensorflow::DataType dtype = variable.dtype();

        func.setResultAttr(index_path.index(), kTfSavedModelIndexPathAttr,
                           index_path.value());
      }
    } else if (object.kind_case() == SavedObject::kVariable) {
      const SavedVariable& variable = object.variable();
      // Find the trackable in the side data structure.
      auto variable_trackable_it = restored_objects.find(node_id);

      TF_ASSIGN_OR_RETURN(