//
    // TODO(b/112837194): This restriction can be lifted with some work.
    bool allow_stack_ops = false;

    // Whether TensorArray operations are allowed.  We avoid auto-clustering
    // TensorArray operations in general because we do not support snapshotting
    // them.
    //
    // TODO(b/112837194): This restriction can be lifted with some work.

          return t;
        } else if (auto scatter =
                       llvm::dyn_cast<TF::TensorArrayScatterV3Op>(user)) {
          // TensorArrayScatter writes vector of tensors to TensorArray. We can
          // deduce the shape of TensorArray by dropping the 0th dim of
          // TensorArrayScatter `value`.
          auto t = scatter.getValue().getType().dyn_cast<RankedTensorType>();

  supported_ops->insert(OperationName(
      mlir::TF::SendTPUEmbeddingGradientsOp::getOperationName(), context));
}

// Stack, TensorList and TensorArray ops are rewritten during the second phase
// of the bridge (compilation of TPUCompile op). They would not match any
// legalization/canonicalization pattern and have to be manually added to the
// list of supported ops.

    LogNotCompilable(node, uncompilable_reason);
    return false;
  }

  if (!op_filter_.allow_tensor_array_ops && IsTensorArrayOp(node)) {
    absl::string_view uncompilable_reason = "TensorArray op";
    MaybeMarkUncompilableNode(uncompilable_reason, *stack_trace,
                              encapsulating_function, uncompilable_nodes);
    LogNotCompilable(node, uncompilable_reason);
    return false;
  }

                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);

}

// Resource types
def TF_VariableResource : TF_ResourceBase<"Variable">;
def TF_StackResource : TF_ResourceBase<"Stack">;
def TF_TensorArrayResource : TF_ResourceBase<"TensorArray">;
def TF_SummaryResource : TF_ResourceBase<"Summary">;
def TF_LookupTableResource : TF_ResourceBase<"LookupTable">;
def TF_DatasetSeedGeneratorResource : TF_ResourceBase<"DatasetSeedGenerator">;