diff --git a/Makefile b/Makefile
index 9ef36b84..d4a78aad 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-GPU=1
+GPU=0
 CUDNN=0
 OPENCV=0
 DEBUG=0
diff --git a/include/darknet.h b/include/darknet.h
index f2ef660a..06d426cb 100644
--- a/include/darknet.h
+++ b/include/darknet.h
@@ -63,7 +63,7 @@ typedef enum {
     ACTIVE,
     RNN,
     GRU,
-	LSTM,
+    LSTM,
     CRNN,
     BATCHNORM,
     NETWORK,
@@ -253,20 +253,20 @@ struct layer{
     struct layer *input_h_layer;
     struct layer *state_h_layer;
 	
-	struct layer *wz;
-	struct layer *uz;
-	struct layer *wr;
-	struct layer *ur;
-	struct layer *wh;
-	struct layer *uh;
-	struct layer *uo;
-	struct layer *wo;
-	struct layer *uf;
-	struct layer *wf;
-	struct layer *ui;
-	struct layer *wi;
-	struct layer *ug;
-	struct layer *wg;
+    struct layer *wz;
+    struct layer *uz;
+    struct layer *wr;
+    struct layer *ur;
+    struct layer *wh;
+    struct layer *uh;
+    struct layer *uo;
+    struct layer *wo;
+    struct layer *uf;
+    struct layer *wf;
+    struct layer *ui;
+    struct layer *wi;
+    struct layer *ug;
+    struct layer *wg;
 
     tree *softmax_tree;
 
@@ -279,20 +279,20 @@ struct layer{
     float *r_gpu;
     float *h_gpu;
 
-	float *temp_gpu;
-	float *temp2_gpu;
-	float *temp3_gpu;
+    float *temp_gpu;
+    float *temp2_gpu;
+    float *temp3_gpu;
 
-	float *dh_gpu;
-	float *hh_gpu;
-	float *prev_cell_gpu;
-	float *cell_gpu;
-	float *f_gpu;
-	float *i_gpu;
-	float *g_gpu;
-	float *o_gpu;
-	float *c_gpu;
-	float *dc_gpu; 
+    float *dh_gpu;
+    float *hh_gpu;
+    float *prev_cell_gpu;
+    float *cell_gpu;
+    float *f_gpu;
+    float *i_gpu;
+    float *g_gpu;
+    float *o_gpu;
+    float *c_gpu;
+    float *dc_gpu; 
 
     float *m_gpu;
     float *v_gpu;
@@ -546,6 +546,7 @@ list *read_cfg(char *filename);
 #include "dropout_layer.h"
 #include "gemm.h"
 #include "gru_layer.h"
+#include "lstm_layer.h"
 #include "im2col.h"
 #include "image.h"
 #include "layer.h"
diff --git a/src/gru_layer.c b/src/gru_layer.c
index 78964817..917c36f9 100644
--- a/src/gru_layer.c
+++ b/src/gru_layer.c
@@ -185,7 +185,6 @@ void forward_gru_layer_gpu(layer l, network state)
 		activate_array_ongpu(l.hh_gpu, l.outputs*l.batch, TANH);			 
 
 		weighted_sum_gpu(l.h_gpu, l.hh_gpu, l.z_gpu, l.outputs*l.batch, l.output_gpu);
-		//ht = z .* ht-1 + (1-z) .* hh
 		copy_ongpu(l.outputs*l.batch, l.output_gpu, 1, l.h_gpu, 1);
 
 		state.input += l.inputs*l.batch;
diff --git a/src/lstm_layer.h b/src/lstm_layer.h
index a9ed792d..8ed387af 100644
--- a/src/lstm_layer.h
+++ b/src/lstm_layer.h
@@ -8,12 +8,12 @@
 
 layer make_lstm_layer(int batch, int inputs, int outputs, int steps, int batch_normalize);
 
-void forward_lstm_layer(layer l, network state); 
+void forward_lstm_layer(layer l, network net); 
 void update_lstm_layer(layer l, int batch, float learning, float momentum, float decay);
 
 #ifdef GPU
-void forward_lstm_layer_gpu(layer l, network state);
-void backward_lstm_layer_gpu(layer l, network state);
+void forward_lstm_layer_gpu(layer l, network net);
+void backward_lstm_layer_gpu(layer l, network net);
 void update_lstm_layer_gpu(layer l, int batch, float learning_rate, float momentum, float decay); 
 
 #endif
diff --git a/src/parser.c b/src/parser.c
index 499be075..16012212 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -57,7 +57,7 @@ LAYER_TYPE string_to_layer_type(char * type)
             || strcmp(type, "[network]")==0) return NETWORK;
     if (strcmp(type, "[crnn]")==0) return CRNN;
     if (strcmp(type, "[gru]")==0) return GRU;
-	if (strcmp(type, "[lstm]") == 0) return LSTM;
+    if (strcmp(type, "[lstm]") == 0) return LSTM;
     if (strcmp(type, "[rnn]")==0) return RNN;
     if (strcmp(type, "[conn]")==0
             || strcmp(type, "[connected]")==0) return CONNECTED;
@@ -678,8 +678,8 @@ network parse_network_cfg(char *filename)
             l = parse_rnn(options, params);
         }else if(lt == GRU){
             l = parse_gru(options, params);
-		}else if (lt == LSTM) {
-			l = parse_lstm(options, params);
+	}else if (lt == LSTM) {
+            l = parse_lstm(options, params);
         }else if(lt == CRNN){
             l = parse_crnn(options, params);
         }else if(lt == CONNECTED){
@@ -921,22 +921,22 @@ void save_weights_upto(network net, char *filename, int cutoff)
             save_connected_weights(*(l.self_layer), fp);
             save_connected_weights(*(l.output_layer), fp);
         } if (l.type == LSTM) {
-			save_connected_weights(*(l.wi), fp);
-			save_connected_weights(*(l.wf), fp);
-			save_connected_weights(*(l.wo), fp);
-			save_connected_weights(*(l.wg), fp);
-			save_connected_weights(*(l.ui), fp);
-			save_connected_weights(*(l.uf), fp);
-			save_connected_weights(*(l.uo), fp);
-			save_connected_weights(*(l.ug), fp);
-		} if (l.type == GRU) {
-			save_connected_weights(*(l.wz), fp);
-			save_connected_weights(*(l.wr), fp);
-			save_connected_weights(*(l.wh), fp);
-			save_connected_weights(*(l.uz), fp);
-			save_connected_weights(*(l.ur), fp);
-			save_connected_weights(*(l.uh), fp);
-		}  if(l.type == CRNN){
+	    save_connected_weights(*(l.wi), fp);
+	    save_connected_weights(*(l.wf), fp);
+	    save_connected_weights(*(l.wo), fp);
+	    save_connected_weights(*(l.wg), fp);
+	    save_connected_weights(*(l.ui), fp);
+	    save_connected_weights(*(l.uf), fp);
+	    save_connected_weights(*(l.uo), fp);
+	    save_connected_weights(*(l.ug), fp);
+	} if (l.type == GRU) {
+	    save_connected_weights(*(l.wz), fp);
+	    save_connected_weights(*(l.wr), fp);
+	    save_connected_weights(*(l.wh), fp);
+	    save_connected_weights(*(l.uz), fp);
+    	    save_connected_weights(*(l.ur), fp);
+	    save_connected_weights(*(l.uh), fp);
+	}  if(l.type == CRNN){
             save_convolutional_weights(*(l.input_layer), fp);
             save_convolutional_weights(*(l.self_layer), fp);
             save_convolutional_weights(*(l.output_layer), fp);
@@ -1128,24 +1128,24 @@ void load_weights_upto(network *net, char *filename, int start, int cutoff)
             load_connected_weights(*(l.self_layer), fp, transpose);
             load_connected_weights(*(l.output_layer), fp, transpose);
         }
-		if (l.type == LSTM) {
-			load_connected_weights(*(l.wi), fp, transpose);
-			load_connected_weights(*(l.wf), fp, transpose);
-			load_connected_weights(*(l.wo), fp, transpose);
-			load_connected_weights(*(l.wg), fp, transpose);
-			load_connected_weights(*(l.ui), fp, transpose);
-			load_connected_weights(*(l.uf), fp, transpose);
-			load_connected_weights(*(l.uo), fp, transpose);
-			load_connected_weights(*(l.ug), fp, transpose);
-		}
-		if (l.type == GRU) {
-			load_connected_weights(*(l.wz), fp, transpose);
-			load_connected_weights(*(l.wr), fp, transpose);
-			load_connected_weights(*(l.wh), fp, transpose);
-			load_connected_weights(*(l.uz), fp, transpose);
-			load_connected_weights(*(l.ur), fp, transpose);
-			load_connected_weights(*(l.uh), fp, transpose);
-		}
+	if (l.type == LSTM) {
+	    load_connected_weights(*(l.wi), fp, transpose);
+	    load_connected_weights(*(l.wf), fp, transpose);
+	    load_connected_weights(*(l.wo), fp, transpose);
+	    load_connected_weights(*(l.wg), fp, transpose);
+	    load_connected_weights(*(l.ui), fp, transpose);
+	    load_connected_weights(*(l.uf), fp, transpose);
+	    load_connected_weights(*(l.uo), fp, transpose);
+	    load_connected_weights(*(l.ug), fp, transpose);
+	}
+	if (l.type == GRU) {
+	    load_connected_weights(*(l.wz), fp, transpose);
+	    load_connected_weights(*(l.wr), fp, transpose);
+	    load_connected_weights(*(l.wh), fp, transpose);
+	    load_connected_weights(*(l.uz), fp, transpose);
+	    load_connected_weights(*(l.ur), fp, transpose);
+	    load_connected_weights(*(l.uh), fp, transpose);
+	}
         if(l.type == LOCAL){
             int locations = l.out_w*l.out_h;
             int size = l.size*l.size*l.c*l.n*locations;