Fix for LSTM edge case (minibatch size of 1) after recent TAD changes

deeplearning4j-core/src/main/java/org/deeplearning4j/nn/layers/recurrent/RnnOutputLayer.java

@@ -51,7 +51,7 @@ public RnnOutputLayer(NeuralNetConfiguration conf, INDArray input) {
 	private INDArray reshape3dTo2d(INDArray in){
 		if( in.rank() != 3 ) throw new IllegalArgumentException("Invalid input: expect NDArray with rank 3");
 		int[] shape = in.shape();
-		if(shape[0]==1) return in.tensorAlongDimension(0,1,2);	//Edge case: miniBatchSize==1
+		if(shape[0]==1) return in.tensorAlongDimension(0,1,2).permutei(1,0);	//Edge case: miniBatchSize==1
 		if(shape[2]==1) return in.tensorAlongDimension(0,1,0);	//Edge case: timeSeriesLength=1
 		INDArray permuted = in.permute(0, 2, 1);	//Permute, so we get correct order after reshaping
 		return permuted.reshape(shape[0] * shape[2], shape[1]);