#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/error_payloads.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/protobuf/core_platform_payloads.pb.h"
#include "tensorflow/core/tpu/tpu_defs.h"
#include "tensorflow/core/util/debug_data_dumper.h"

  let description = [{
    Interface for ops that are stateful and need to identify stateful operands.

    Stateful operands correspond to TF's variables semantics. An op that has 1
    or more stateful operands is a stateful op.
  }];

  let methods = [
    InterfaceMethod<
      [{Returns the indices of stateful operands.}],
      "std::vector<int>", "GetStatefulOperands", (ins)
    >,
  ];
}

from tensorflow.core.framework import attr_value_pb2
from tensorflow.core.framework import graph_pb2
from tensorflow.core.framework import node_def_pb2
from tensorflow.core.framework import tensor_pb2
from tensorflow.core.framework import tensor_shape_pb2
from tensorflow.core.framework import types_pb2
from tensorflow.python.client import session

#include "tensorflow/compiler/jit/xla_cluster_util.h"
#include "xla/status_macros.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/algorithm.h"
#include "tensorflow/core/graph/control_flow.h"
#include "tensorflow/core/graph/graph_node_util.h"
#include "tensorflow/core/graph/tensor_id.h"
#include "tensorflow/core/lib/hash/hash.h"

// ALGORITHM OVERVIEW
// ==================
//

    llvm::APSInt result(storage_bit_width_, !is_signed_);
    fixed_point.convertToInteger(result, round_mode_, &lossy);

    return std::move(result);
  }

  int64_t quantizeFloatToInt64(APFloat expressed_value) const {
    const APInt q_value = quantizeFloatToInt(std::move(expressed_value));
    return is_signed_ ? q_value.getSExtValue() : q_value.getZExtValue();
  }

#include "tensorflow/cc/gradients/grad_testutil.h"
#include "tensorflow/cc/ops/math_ops.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/random/random.h"

namespace tensorflow {
namespace {

using ops::Abs;
using ops::Add;
using ops::AddN;
using ops::AddV2;
using ops::Atan2;

  }

  // LSTM `func::FuncOps` with indy behavior always have the `tf.api_implements`
  // function attribute prefixed with `"indy_lstm_"`.
  // IndyLSTMs have diagonal recurrent weight matrices and can benefit from
  // more efficent operations in TFLite with the correct conversion (i.e. when
  // the diagonal recurrent weight matrices are provided as vectors).
  if (attr.getValue().starts_with("indy_lstm_")) {

  // Return true if number of input nodes doesn't equal to that of the input
  // ranges.
  bool SetInputNodesQuantizationParams(func::FuncOp func);

  // The function might contain more stats ops than required, and it will
  // introduce requantize if the calibration stats have conflicts. This method
  // tries to remove all the redundant stats ops.
  bool RemoveRedundantStats(func::FuncOp func);

        // direct parent:
        // For example, ops with regions usually don't expose values used in a
        // region to the op's interface which means that the usage of a value
        // can be 2 or more levels below an island (see b/242920486).
      } else if (auto other_island_op =
                     owner->getParentOfType<tf_executor::IslandOp>()) {

//   1. DENSE: each coordinate in this dimension is stored implicitly.
//   2. SPARSE_CSR: only the coordinates with non-zero elements are stored. The
//      compression technique is the same what CSR uses.
// More types like a sparse dimension with a different compression technique
// could be added to the list in the future.
enum DimensionType : byte {
  DENSE = 0,
  SPARSE_CSR = 1,
}

table Int32Vector {