LSTM error

gistfile1.txt

        NeuralNetConfiguration.Builder builder = new NeuralNetConfiguration.Builder();
        builder.iterations(1).learningRate(LEARNING_RATE).rmsDecay(RMS_DECAY)
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).seed(123).miniBatch(true).updater(Updater.RMSPROP)
                .weightInit(WeightInit.XAVIER).regularization(true).l2(L2)
                .gradientNormalization(GradientNormalization.RenormalizeL2PerLayer);

        GraphBuilder graphBuilder = builder.graphBuilder().pretrain(false).backprop(true).backpropType(BackpropType.TruncatedBPTT)
                .tBPTTBackwardLength(TBPTT_SIZE).tBPTTForwardLength(TBPTT_SIZE);
        graphBuilder.addInputs("firstLine").setInputTypes(InputType.recurrent(dict.size()))
                .addLayer("encoder", new GravesLSTM.Builder().nIn(dict.size()).nOut(HIDDEN_LAYER_WIDTH).activation(Activation.TANH).build(),
                        "firstLine")
                .addVertex("thoughtVector", new LastTimeStepVertex("firstLine"), "encoder")
                .addLayer("decoder",
                        new GravesLSTM.Builder().nIn(HIDDEN_LAYER_WIDTH).nOut(HIDDEN_LAYER_WIDTH).activation(Activation.TANH)
                                .build(),
                        "thoughtVector")
                .addLayer("output", new RnnOutputLayer.Builder().nIn(HIDDEN_LAYER_WIDTH).nOut(dict.size()).activation(Activation.SOFTMAX)
                        .lossFunction(LossFunctions.LossFunction.MCXENT).build(), "decoder")
                .setOutputs("output");

        ComputationGraphConfiguration conf = graphBuilder.build();


Exception in thread "main" org.deeplearning4j.exception.DL4JInvalidInputException: Received input with size(1) = 1024 (input array shape = [17, 1024]); input.size(1) must match layer nIn size (nIn = 11059)
	at org.deeplearning4j.nn.layers.recurrent.LSTMHelpers.activateHelper(LSTMHelpers.java:142)
	at org.deeplearning4j.nn.layers.recurrent.GravesLSTM.activateHelper(GravesLSTM.java:150)
	at org.deeplearning4j.nn.layers.recurrent.GravesLSTM.rnnActivateUsingStoredState(GravesLSTM.java:222)
	at org.deeplearning4j.nn.graph.ComputationGraph.rnnActivateUsingStoredState(ComputationGraph.java:2081)
	at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:955)
	at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:151)
	at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:54)
	at org.deeplearning4j.optimize.Solver.optimize(Solver.java:51)
	at org.deeplearning4j.nn.graph.ComputationGraph.doTruncatedBPTT(ComputationGraph.java:2032)
	at org.deeplearning4j.nn.graph.ComputationGraph.fit(ComputationGraph.java:824)