void (*delete_func)(void*), TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  auto* resource_mgr = cc_ctx->resource_manager();
  tensorflow::core::RefCountPtr<tensorflow::PluginResource>
      tf_plugin_resource_ptr;
  tensorflow::PluginResource* tf_plugin_resource = nullptr;

  auto cc_status = resource_mgr->LookupOrCreate<tensorflow::PluginResource>(

    public MetadataResolutionException() {
        // TODO Auto-generated constructor stub
    }

    public MetadataResolutionException(String message) {
        super(message);
        // TODO Auto-generated constructor stub
    }

    public MetadataResolutionException(Throwable cause) {
        super(cause);
        // TODO Auto-generated constructor stub
    }

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TEST(CAPI, MonitoringSampler0) {
  TF_Status* status = TF_NewStatus();
  auto* buckets = TFE_MonitoringNewExponentialBuckets(1.0, 2.0, 2);
  auto* sampler =
      TFE_MonitoringNewSampler0("test/sampler", buckets, status, "test");
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  auto* cell = TFE_MonitoringGetCellSampler0(sampler);
  TFE_MonitoringSamplerCellAdd(cell, 1.0);
  auto* collection_registry = monitoring::CollectionRegistry::Default();

      TF_SetStatus(status, TF_OUT_OF_RANGE, std::move(os).str().c_str());
      return total_bytes_transferred;
    }
    auto begin = data.begin();
    if (offset > pos) {
      // The block begins before the slice we're reading.
      begin += offset - pos;
    }
    auto end = data.end();
    if (pos + data.size() > offset + n) {
      // The block extends past the end of the slice we're reading.

    int64_t op_id = op_id_it->second;
    auto op_it = op_tape->find(op_id);
    auto result_op_it = result.op_tape.find(op_id);
    if (op_id == -1 || op_it == op_tape->end() ||
        result_op_it != result.op_tape.end()) {
      continue;
    }
    CHECK(result.op_tape.emplace(op_id, op_it->second).second);
    for (auto it : op_it->second.input_tensor_id) {
      auto count_it = result.tensor_usage_counts.find(it);

  TF_Tensor* analytical_tensor;
  auto s = GetValue(t, &analytical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  int64_t num_elem_analytical = 1;
  auto num_dims_analytical = TF_NumDims(analytical_tensor);
  ASSERT_EQ(dims.size(), num_dims_analytical);
  for (int j = 0; j < num_dims_analytical; j++) {
    auto dim_analytical = TF_Dim(analytical_tensor, j);

        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(self, request: Request) -> Optional[str]:
        authorization = request.headers.get("Authorization")
        if not authorization:
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"

  if (TF_GetCode(status) != TF_OK) return -1;
  auto stream = gcs_file->gcs_client.ReadObject(
      bucket, object, gcs::ReadRange(offset, offset + buffer_size));
  TF_SetStatusFromGCSStatus(stream.status(), status);
  if ((TF_GetCode(status) != TF_OK) &&
      (TF_GetCode(status) != TF_OUT_OF_RANGE)) {
    return -1;
  }
  int64_t read;
  auto content_length = stream.headers().find("content-length");

        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(self, request: Request) -> Optional[str]:
        authorization = request.headers.get("Authorization")
        if not authorization:
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"