// RUN: tf-opt -tfl-legalize-tensorlist -canonicalize -split-input-file %s | FileCheck %s

// CHECK-LABEL: listReserveScalarShapeI32
func.func @listReserveScalarShapeI32(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
  %0 = "tf.TensorListReserve"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>

A. Unique TensorFlower <******@****.***> 1684532433 -0700

A. Unique TensorFlower <******@****.***> 1712999357 -0700

      });
  return has_variant_input || has_variant_output;
}

// There are 2 standard tf ops which are not TensorList ops that may take as
// input a tensorlist. These are tf.AddN and tf.ZeroesLike. Since the runtime
// implementation of a tensorlist are not compatible between tf and tflite
// we cannot use tflite tensorlist kernels until these cases are handled.
bool IsNonTensorListVariantOp(Operation* op) {

//===----------------------------------------------------------------------===//
// TensorList transformation patterns.
// Note that the pattern below rewrites `TensorList` tensors  (which has type DT_VARIANT)
// into regular tensors. We also assume that each element in the `TensorList` has
// a same constant shape.
//===----------------------------------------------------------------------===//

    // meaningless value -1 for non resource outputs.
    out_desc.input_index =
        it != output_to_input_alias.end() ? it->getSecond() : -1;
    // MLIR-based TF-Compiler bridge doesn't support tensorlist output yet.
    // TODO(ycao): Support tensorlist-type output.
    out_desc.is_tensor_list = false;
  }

  // XLA computation always uses Tuple shape.
  *xla_output_shape = xla::ShapeUtil::MakeTupleShape(shapes);

    name = "tensor_types_test_util",
    testonly = True,
    hdrs = ["tensor_types_test_util.h"],
    deps = [
        "//tensorflow/c:tf_datatype",
    ],
)

tf_cc_test(
    name = "tensor_test",
    srcs = [
        "tensor_test.cc",
    ],
    deps = [
        ":tensor_types_test_util",
        "//tensorflow/c:tf_datatype",
        "//tensorflow/cc/experimental/base/public:status",

// RUN: tf-opt "-tfl-lower-static-tensor-list=allow-tensorlist-pass-through default-to-single-batch=false" -split-input-file %s | FileCheck %s

// -----

func.func @tensorlistReserveConstantUnknownElementShapeDim(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<?x7xf32> {
  %cst = arith.constant dense<[-1, 7]> : tensor<2xi32>
  %0 = "tf.TensorListReserve"(%cst, %arg0) : (tensor<2xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<?x7xf32>>>

    }
  };

  while (!worklist.empty()) {
    tensorlist = worklist.top();
    worklist.pop();

    // TensorLists are semantically immutable. For example, TensorListSetItem
    // takes a TensorList as input and produces a TensorList as output. So to
    // traverse modifications to TensorList and verify that all elements written

             "legalized by this pass, then the IR won't be changed so that "
             "tensorlist ops can pass through (default false).">,
      Option<
        "default_to_single_batch_", "default-to-single-batch", "bool", "false",
        "When specified to true, if the tensorlist ops has unspecified batch "
        "size, this pass will assume that the batch size is one to proceed "