// not `tf.AssignVariableOp`.
llvm::SmallSet<llvm::StringRef, 1> GetCompositeResourceUserNames(
    Value resource) {
  // SmallSet will use a vector when there is only one element and use std::set
  // when there are more than one elements. This ensures that the operations in
  // the error message are ordered.
  llvm::SmallSet<llvm::StringRef, 1> composite_users;
  for (Operation* user : resource.getUsers())

  selected_boxes = tf.gather(boxes, selected_indices)
This op also supports a Soft-NMS (with Gaussian weighting) mode (c.f.
Bodla et al, https://arxiv.org/abs/1704.04503) where boxes reduce the score
of other overlapping boxes instead of directly causing them to be pruned.
To enable this Soft-NMS mode, set the `soft_nms_sigma` parameter to be
larger than 0.
  }];

  let arguments = (ins
    TFL_FpTensor:$boxes,

#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

using std::vector;
using tensorflow::ops::BiasAddGrad;
using tensorflow::ops::ReluGrad;

namespace tensorflow {
namespace gradients {
namespace {

#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_roundtrip_flags.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/lite/toco/model_flags.pb.h"

#include "xla/translate/hlo_to_mhlo/hlo_utils.h"
#include "xla/translate/mhlo_to_hlo/type_to_shape.h"
#include "xla/window_util.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/ir/types/dialect.h"
#include "tsl/platform/errors.h"

#define DEBUG_TYPE "tf-shape-inference"

#define DCOMMENT(MSG) LLVM_DEBUG(llvm::dbgs() << MSG << "\n")

#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/fingerprint.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tensorflow/core/util/device_name_utils.h"

namespace mlir {

// Test that SplitOp is not generated when an input sharding has 
// last_tile_dims REPLICATED and more tile_assignment_dimensions 
// than tensor dimenstions, even when the SPMD sharding is enabled and
// num_cores_per_replica is more than 1.
// Test that ConcatV2 Op is not generated when a output sharding has 
// last_tile_dims REPLICATED and more tile_assignment_dimensions 
// than tensor dimenstions, even when the SPMD sharding is enabled and

logical_core attribute correspond to a TPU core. This op maps the TPU core to a
device_ordinal, where the device ordinal is the index of the core relative to
its host.

The replicate_to_island pass removes and flattens tf_device.replicate, so it
converts this op to the constant index of the core relative to its host.
  }];

  let arguments = (ins
    I64Attr:$logical_core

#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/refcount.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/tfrt/common/async_value_tensor.h"
#include "tensorflow/core/util/stream_executor_util.h"
#include "tsl/framework/device_id_utils.h"

        "//tensorflow/core:test_main",
        "//tensorflow/core/platform:path",
        "//tensorflow/core/platform:protobuf",
        "//tensorflow/core/platform:resource_loader",
        "//tensorflow/core/platform:status_matchers",
        "//tensorflow/core/platform:statusor",
    ],
)

tf_cc_test(
    name = "libtf_tensor_test",
    size = "medium",
    srcs = ["tests/tensor_test.cc"],