//  noutputs - number of elements in `outputs` array
//  outputs - array of TF_Outputs that specify the outputs of the function.
//            If `noutputs` is zero (the function returns no outputs), `outputs`
//            can be null. `outputs` can contain the same tensor more than once.
//  output_names - The names of the function's outputs. `output_names` array

                         const std::vector<IOSpec>& outputs) {
    const OpDef& signature = fdef.signature();
    ASSERT_EQ(outputs.size(), signature.output_arg_size());
    for (int i = 0; i < outputs.size(); ++i) {
      const OpDef::ArgDef& arg = signature.output_arg(i);
      const IOSpec& out = outputs[i];
      if (out.second != DT_INVALID) {
        ASSERT_EQ(arg.type(), out.second)

    // Convert back to a C++ Tensor and ensure we get expected output.
    Tensor output;
    ASSERT_EQ(absl::OkStatus(), TF_TensorToTensor(dst, &output)) << line;
    ASSERT_EQ(src.NumElements(), output.NumElements()) << line;
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      ASSERT_EQ(data[i], output.flat<tstring>()(i)) << line;
    }

    TF_DeleteTensor(dst);
  }
}

      ListenableFuture<V> future) {
    if (future.isDone()) {
      return future;
    }
    NonCancellationPropagatingFuture<V> output = new NonCancellationPropagatingFuture<>(future);
    future.addListener(output, directExecutor());
    return output;
  }

  /** A wrapped future that does not propagate cancellation to its delegate. */

			// necessary. Test passes as expected, but the output values
			// are verified for correctness here.
			if err == nil && testCase.shouldPass {
				// The length of the expected ListObjectsResult.Objects
				// should match in both expected result from test cases
				// and in the output. On failure calling t.Fatalf,
				// otherwise it may lead to index out of range error in

			}
		}
		// Test passes as expected, but the output values are verified for correctness here.
		if actualErr == nil && testCase.shouldPass {
			// Asserting whether the md5 output is correct.
			if testCase.inputMd5 != actualInfo.ETag {

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteTensorHandle(retvals[0]);
  float output[2] = {0};
  EXPECT_EQ(sizeof(output), TF_TensorByteSize(t));
  memcpy(&output[0], TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  EXPECT_EQ(1, output[0]);
  EXPECT_EQ(3, output[1]);
  TFE_DeleteContext(ctx);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

labels.docId=ID Dokumen
labels.endTime=Waktu Selesai
labels.hq=hq
labels.inputs=Input
labels.jobLogging=Logging
labels.jobName=Nama
labels.jobStatus=Status
labels.labelTypeIds=Label
labels.lang=Bahasa
labels.outputs=Output
labels.pos=Kelas Kata
labels.purgeJobLogDay=Hapus log job lama
labels.purgeUserInfoDay=Hapus log pengguna lama
labels.reading=Pembacaan
labels.roleTypeIds=ID Peran
labels.scriptData=Script

			objectsToDelete[object] = index
		}
	}

	toNames := func(input map[ObjectToDelete]int) (output []ObjectToDelete) {
		output = make([]ObjectToDelete, len(input))
		idx := 0
		for obj := range input {
			output[idx] = obj
			idx++
		}
		return output
	}

	// Disable timeouts and cancellation
	ctx = bgContext(ctx)

	deleteList := toNames(objectsToDelete)

labels.docId=Document ID
labels.endTime=End Time
labels.hq=hq
labels.inputs=Inputs
labels.jobLogging=Logging
labels.jobName=Name
labels.jobStatus=Status
labels.labelTypeIds=Labels
labels.lang=Language
labels.outputs=Outputs
labels.pos=Part-of-speech
labels.purgeJobLogDay=Delete old job logs
labels.purgeUserInfoDay=Delete old user logs
labels.reading=Reading
labels.roleTypeIds=Role IDs
labels.scriptData=Script