}

    public String getInputsValue() {
        if (inputs == null) {
            return StringUtil.EMPTY;
        }
        return String.join("\n", inputs);
    }

    public String[] getOutputs() {
        return outputs;
    }

    public String getOutputsValue() {
        if (outputs == null) {
            return StringUtil.EMPTY;
        }
        return String.join("\n", outputs);
    }

    }

    public String getInputsValue() {
        if (inputs == null) {
            return StringUtil.EMPTY;
        }
        return String.join("\n", inputs);
    }

    public String getOutput() {
        return output;
    }

    public boolean isUpdated() {
        return newInputs != null && newOutput != null;
    }

    public boolean isDeleted() {

    }

    public void setNewOutput(final String newOutputs) {
        newOutput = newOutputs;
    }

    public String getInput() {
        return input;
    }

    public String getOutput() {
        return output;
    }

    public boolean isUpdated() {
        return newInput != null && newOutput != null;
    }

    public boolean isDeleted() {

            final int exitValue = currentProcess.exitValue();

            if (logger.isInfoEnabled()) {
                logger.info("ThumbnailGenerator: Exit Code={} - Process Output:\n{}", exitValue, it.getOutput());
            }
            if (exitValue != 0) {
                final StringBuilder out = new StringBuilder();
                if (processTimeout) {

  // Create a session for this graph.
  CSession csession(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Run the graph.
  csession.SetInputs({{feed, Int32Tensor(3)}});
  csession.SetOutputs({add});
  csession.Run(s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_Tensor* out = csession.output_tensor(0);
  ASSERT_TRUE(out != nullptr);
  EXPECT_EQ(TF_INT32, TF_TensorType(out));