return newOutput;
    }

    public void setNewOutput(final String newOutput) {
        this.newOutput = newOutput == null ? null : newOutput.replace("\n", " ");
    }

    public String[] getInputs() {
        return inputs;
    }

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

class ImmediateExecutionOperation : public AbstractOperation {
 public:
  virtual void Clear() = 0;

  // Returns the inputs of this op.
  virtual absl::Span<ImmediateExecutionTensorHandle* const> GetInputs()
      const = 0;
  virtual absl::Status SetInput(size_t index,
                                ImmediateExecutionTensorHandle* input) = 0;

  virtual ImmediateExecutionContext* GetContext() const = 0;

    }

    public String[] getNewOutputs() {
        return newOutputs;
    }

    public void setNewOutputs(final String[] newOutputs) {
        this.newOutputs = newOutputs;
    }

    public String[] getInputs() {
        return inputs;
    }

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

            task.setTitle("Gradle API " + version);

            Javadocs javadocs = extension.getJavadocs();

            // TODO: This should be part of Javadoc task
            task.getInputs().file(javadocs.getJavadocCss())
                .withPropertyName("stylesheetFile")
                .withPathSensitivity(PathSensitivity.NAME_ONLY);

}

extern int TFE_OpGetFlatInputCount(const TFE_Op* op, TF_Status* status) {
  return tensorflow::unwrap(op)->GetInputs().size();
}

extern TFE_TensorHandle* TFE_OpGetFlatInput(const TFE_Op* op, int index,
                                            TF_Status* status) {
  return tensorflow::wrap(tensorflow::unwrap(op)->GetInputs()[index]);
}

TF_AttrType TFE_OpGetAttrType(TFE_Op* op, const char* attr_name,

        }
    }

    public String getNewInput() {
        return newInput;
    }

    public void setNewInput(final String newInput) {
        this.newInput = newInput;
    }

    public String getInput() {
        return input;
    }

    public String getInputValue() {
        if (input == null) {
            return StringUtil.EMPTY;
        }
        return input;
    }

    }

    public String getNewOutput() {
        return newOutput;
    }

    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 String getNewInput() {
        return newInput;
    }

    public void setNewInput(final String newInput) {
        this.newInput = newInput;
    }

    public String getInput() {
        return input;
    }

    public String getInputValue() {
        if (input == null) {
            return StringUtil.EMPTY;
        }
        return input;
    }

  // 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);