#include "absl/container/flat_hash_set.h"
#include "absl/strings/str_cat.h"
#include "tensorflow/compiler/jit/defs.h"
#include "tensorflow/compiler/jit/xla_cluster_util.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/graph/algorithm.h"

namespace tensorflow {
namespace {

class ClusterScopingPassImpl {
 public:
  ClusterScopingPassImpl(Graph* graph,

#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/graph/graph_debug_info_builder.h"
#include "tensorflow/core/graph/node_builder.h"
#include "tensorflow/core/graph/tensor_id.h"
#include "tensorflow/core/grappler/utils/transitive_fanin.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/crash_analysis.h"
#include "tensorflow/core/platform/env.h"

  pass_manager.addNestedPass<mlir::func::FuncOp>(
      mlir::odml::createLegalizeCompositeToCustomOpPass());
}

// This is the early part of the conversion in isolation. This enables a caller
// to inject more information in the middle of the conversion before resuming
// it.
void AddPreVariableFreezingTFToTFLConversionPasses(
    const mlir::TFL::PassConfig& pass_config,
    mlir::OpPassManager* pass_manager) {

    func.return
  }
}

// -----

// Tests that the pass does not format variables when model parallelism is
// present. Model parallelism is present when there is more than 1
// TPUExecuteAndUpdateVariables in a parallel_execute.

!tf_res_f32 = tensor<*x!tf_type.resource<tensor<f32>>>
!tf_res_md_f32 = tensor<*x!tf_type.resource<tensor<3x3x1x32xf32>>> // Multi-dim f32

    mlir::emitError(
        location,
        llvm::formatv("Attempted to map cluster_func output index {0} to "
                      "program assigned to core {1}. The tensor at this output "
                      "index was not assigned or sharded to this core.",
                      cluster_func_output_index, core_id));
    return mlir::failure();
  }
  return mlir::success();
}

@@ -748,27 +422,11 @@ __stpcpy_small (char *__dest,
   }
   return __dest + __srclen - 1;
 }
-#   endif
 #  endif
 # endif
 #endif
 
 
-/* Copy no more than N characters of SRC to DEST.  */
-#ifndef _HAVE_STRING_ARCH_strncpy
-# if __GNUC_PREREQ (3, 2)
-#  define strncpy(dest, src, n) __builtin_strncpy (dest, src, n)
-# else
-#  define strncpy(dest, src, n) \

    llvm::SmallVector<Value, 4> operands(addn_op.getInputs().begin(),
                                         addn_op.getInputs().end());

    int64_t n = operands.size();
    // Keep doing tree-based reduction when there are more than one operand.
    while (n > 1) {
      for (int64_t i = 0; i < n; i += 2) {
        // Add two adjacent operands if applicable.
        operands[i / 2] =

      return WalkResult::advance();
    }

    // If any of the operands is a resource type, then we break
    // and mark the module as not valid for TFLite legalization.
    // Note: this might disable native variables in more than needed cases.
    // TODO(b/189370197): Enhance variable analysis.
    for (auto operand : op->getOperands()) {
      if (mlir::isa<TF::ResourceType>(
              getElementTypeOrSelf(operand.getType()))) {

#include "tensorflow/core/common_runtime/function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/memory_types.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/graph/graph_node_util.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/public/version.h"

namespace tensorflow {

// Version 2: Rename operators to conform to NN API.
// Version 3: Move buffer data from Model.Subgraph.Tensors to Model.Buffers.
// Version 3a: Add new builtin op code field. Has backward compatibility with
//             version 3.
// Version 3b: Rename fields in SignatureDef. Has backward compatibility with
//             version 3 and 3a.
// Version 3c: Move constant tensor buffers & custom op buffers outside from