==============================================================================*/

#include "tensorflow/c/eager/c_api_experimental.h"

#include <cstdint>
#include <memory>
#include <utility>
#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/match.h"
#include "absl/time/time.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"

}

inline absl::Status AbstractOperation::SetAttrStringList(
    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());

/**
 * Represents the FILE_FS_SIZE_INFORMATION structure used to query file system size information.
 * This structure provides details about the total allocation units, free allocation units,
 * sectors per allocation unit, and bytes per sector for a file system volume.
 */
public class FileFsSizeInformation implements AllocInfo {

    private long alloc; // Also handles SmbQueryFSSizeInfo
    private long free;

		}
	}
	if opd, ok := riscv64SpecialOperand[name]; ok {
		return opd
	}
	return riscv.SPOP_END
}

// RISCV64ValidateVectorType reports whether the given configuration is a
// valid vector type.
func RISCV64ValidateVectorType(vsew, vlmul, vtail, vmask int64) error {
	_, err := riscv.EncodeVectorType(vsew, vlmul, vtail, vmask)
	return err

    } else {
      TFE_OpAddInput(op, input, s);
    }
    if (TF_GetCode(s) != TF_OK) return;
  }
  std::vector<TFE_TensorHandle*> op_outputs(*num_outputs);
  TFE_Execute(op, op_outputs.data(), num_outputs, s);
  TFE_DeleteOp(op);
  if (TF_GetCode(s) != TF_OK) return;
  std::vector<TFE_TensorHandle*> unwrapped_outputs;
  unwrapped_outputs.reserve(op_outputs.size());
  for (auto* handle : op_outputs) {

  tensorflow::JobDef* job_def = server_def->mutable_cluster()->mutable_job(0);
  job_def->mutable_tasks()->at(task_index) = absl::StrCat(host, ":", port);
}

std::vector<std::string> ListDeviceNames(TFE_Context* ctx) {
  TF_Status* status = TF_NewStatus();
  std::vector<std::string> device_names;
  TF_DeviceList* devices = TFE_ContextListDevices(ctx, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

	VMOVQ		V3.W[1], V7.W4  // 67e4f772
	VMOVQ		V4.V[0], V6.V2  // 86f0f772

	// Move vector register to vector register.
	VMOVQ		V1, V9		// 29002d73
	VMOVQ		V2, V8		// 48002d73
	XVMOVQ		X3, X7		// 67002d77
	XVMOVQ		X4, X6		// 86002d77

	// Load data from memory and broadcast to each element of a vector register: VMOVQ    offset(Rj), <Vd>.<T>
	VMOVQ		(R4), V0.B16	// 80008030
	VMOVQ		1(R4), V0.B16	// 80048030

    EXPECT_TRUE(found);
    TF_DeleteBuffer(op_list_buffer);
  }
}

void TestEncodeDecode(int line, const std::vector<std::string>& data) {
  const int64_t n = data.size();
  absl::Status status;
  for (const std::vector<int64_t>& dims :
       std::vector<std::vector<int64_t>>{{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
    // Create C++ Tensor
    Tensor src(tensorflow::DT_STRING, TensorShape(dims));

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include <vector>

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"

    @Test
    void testInit_WithJcifsParameters() throws ServletException {
        // Reset mocks for this test
        reset(servletConfig, servletContext);

        // Setup init parameters
        Vector<String> paramNames = new Vector<>();
        paramNames.add("jcifs.smb.client.domain");
        paramNames.add("jcifs.http.enableBasic");
        paramNames.add("someOtherParam");