#include "tensorflow/core/public/session.h"

namespace mlir {
namespace tf_saved_model {

// Initializes all variables in Session Init function for all variables in
// 'session'.
LogicalResult InitializeVariablesInSessionInitializer(
    ModuleOp module, tensorflow::Session *session);

}  // namespace tf_saved_model

}  // namespace mlir

}

// CHECK-LABEL: func @set_readonly_stateless
func.func @set_readonly_stateless(%arg: tensor<i32> {tf_saved_model.index_path = ["arg"]}, %cond: tensor<i1> {tf_saved_model.index_path = ["cond"]}) -> (tensor<i32> {tf_saved_model.index_path = ["output"]}) attributes {tf_saved_model.exported_names = ["main"]} {

  func.func @depthwise_conv(%arg0: tensor<1x3x4x3xf32> {tf_saved_model.index_path = ["input_tensor"]}) -> (tensor<1x2x2x3xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input_tensor:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

#include "tensorflow/core/public/session.h"

namespace mlir {
namespace tf_saved_model {

// Creates GlobalTensorOp for each variable from function arguments and converts
// them to the corresponding saved model arguments.
LogicalResult LiftVariables(ModuleOp module, ::tensorflow::Session* session);

}  // namespace tf_saved_model
}  // namespace mlir

  func.func @serving_default(%arg0: tensor<1x4xf32> {tf_saved_model.index_path = ["x"]}) -> (tensor<1x3xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_x:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/session_utils.h"
#include "tensorflow/core/framework/resource_var.h"
#include "tensorflow/core/public/session.h"

namespace mlir {
namespace tf_saved_model {
namespace {

void InitializeVariable(TF::VarHandleOp var_handle_op,

#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/core/public/session.h"

namespace mlir {
namespace tf_saved_model {

// Returns the variable for the provided 'var_handle_op'.
std::string GetVariableName(TF::VarHandleOp var_handle_op);

// Returns pointer to the variable from 'session' that 'var_handle_op'

from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1

# Verify that the tf.versions attribute exists. It is difficult to enforce
# contents, since the version numbers change over time. The conversion logic
# itself is verified in the common graphdef converter, so here just assert
# it is being invoked.
# CHECK: module
# CHECK-NOT: tf_saved_model.global_tensor


def Test():

  func.func @conv_with_filter_larger_than_1GB(%arg0: tensor<1x2240x2240x3xf32> {tf_saved_model.index_path = ["input"]}) -> (tensor<1x2240x1120x512xf32> {tf_saved_model.index_path = ["output"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_input:0", outputs = "PartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

#include "absl/strings/string_view.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project

namespace mlir {
namespace tf_saved_model {

// Helper function that sets up a module for an AssetSinkingPass. The sole
// argument of the main function of `module` is prepared to be inlined with
// the value `checkpoint_path`.
// Also adds SessionInitializer op.