diff --git a/.gitignore b/.gitignore
index 46f4be9..160114d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,4 +10,4 @@ __pycache__
 *.h5
 *.obj
 *.sconsign.dblite
-.ipynb_checkpoints
+.ipynb_checkpoints
\ No newline at end of file
diff --git a/docs/index.md b/docs/index.md
index 2595f1d..7dfd590 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -5,6 +5,8 @@
 
 NNoM is a high-level inference Neural Network library specifically for microcontrollers. 
 
+Document version 0.2.1
+
 [[Chinese Intro]](rt-thread_guide.md)
 
 **Highlights**
diff --git a/examples/auto_test/.gitignore b/examples/auto_test/.gitignore
index 4e831c2..6bbeb39 100644
--- a/examples/auto_test/.gitignore
+++ b/examples/auto_test/.gitignore
@@ -11,4 +11,6 @@ Debug
 *.sconsign.dblite
 .ipynb_checkpoints
 weights.h
-result.csv
\ No newline at end of file
+result.csv
+test_*
+_cifar.py
diff --git a/inc/nnom.h b/inc/nnom.h
index c2e9fd0..bbe75b4 100644
--- a/inc/nnom.h
+++ b/inc/nnom.h
@@ -25,6 +25,12 @@
 #define q15_t 	int16_t
 #define q31_t 	int32_t
 
+/* version */
+#define NNOM_MAJORVERSION     0L              /**< major version number */
+#define NNOM_SUBVERSION       2L              /**< minor version number */
+#define NNOM_REVISION         1L              /**< revise version number */
+#define NNOM_VERSION          (NNOM_MAJORVERSION * 10000) + (NNOM_SUBVERSION * 100) + NNOM_REVISION)
+										 
 typedef enum
 {
 	NN_SUCCESS = 0,			/**< No error */
diff --git a/scripts/nnom_utils.py b/scripts/nnom_utils.py
index ff99444..af62b76 100644
--- a/scripts/nnom_utils.py
+++ b/scripts/nnom_utils.py
@@ -350,7 +350,7 @@ def layers_output_ranges(model, x_test, kld=True, calibrate_size=1000):
 
         # saturation shift, using KLD method
         # Ref: http://on-demand.gputechconf.com/gtc/2017/presentation/s7310-8-bit-inference-with-tensorrt.pdf
-        if(kld and not is_shift_fixed(layer) and "input" not in layer.name): # test, also do not use kld in input layer
+        if(kld and not is_shift_fixed(layer) and "input" not in layer.name and "dense" not in layer.name): # test, also do not use kld in input layer
             import scipy.stats
             abs_max = max(abs(max_val), abs(min_val))
             small_var = 1e-5
@@ -359,7 +359,7 @@ def layers_output_ranges(model, x_test, kld=True, calibrate_size=1000):
             flat_hist = np.histogram(features.flatten(), bins=bins)[0]
             kl_loss = []
             kl_shifts = []
-            for shift in range(8):
+            for shift in range(4):
                 t = 2 ** (dec_bits + shift)     # 2-based threshold
                 act = np.round(features.flatten() * t)
                 act = act / t
@@ -701,6 +701,29 @@ def is_skipable_layer(layer):
                 fp.write('\tlayer[%s] = model.hook(Softmax(), layer[%s]);\n'%(id, LI[inp][0]))
             else:
                 raise Exception('unsupported layer', layer.name, layer)
+			
+            """
+            # temporary fixed for activations attached into layers in construction
+            def is_activation_attached(layer):
+                if(("Softmax" in layer.output.name and "softmax" not in layer.name)or
+                ("Relu" in layer.output.name and "re_lu" not in layer.name) or
+                ("Sigmoid" in layer.output.name and "sigmoid" not in layer.name) or
+                ("Tanh" in layer.output.name and "tanh" not in layer.name)):
+                    return True
+                return False
+            if "input" not in layer.name and is_activation_attached(layer):
+                inp = layer.output.name.replace(':', '/').split('/')[0]
+                cfg = layer.get_config()
+                if(cfg['activation'] == 'relu'):
+                    fp.write('\tlayer[%s] = model.active(act_relu(), layer[%s]);\n'%(id, LI[inp][0]))
+                if(cfg['activation'] == 'tanh'):
+                    fp.write('\tlayer[%s] = model.active(act_tanh(%s_OUTPUT_SHIFT), layer[%s]);\n'%(id, inp.upper(), LI[inp][0]))
+                if(cfg['activation'] == 'sigmoid'):
+                    fp.write('\tlayer[%s] = model.active(act_sigmoid(%s_OUTPUT_SHIFT), layer[%s]);\n'%(id, inp.upper(), LI[inp][0]))
+                elif(cfg['activation'] == 'softmax'):
+                    fp.write('\tlayer[%s] = model.hook(Softmax(), layer[%s]);\n'%(id, LI[inp][0]))
+            """
+			
         # FIXME, test later.
         if('softmax' in layer.name
            or ('activation' in layer.name and layer.get_config()['activation'] == 'softmax')):
diff --git a/src/nnom.c b/src/nnom.c
index c2a3480..87644e8 100644
--- a/src/nnom.c
+++ b/src/nnom.c
@@ -868,7 +868,8 @@ nnom_status_t model_compile(nnom_model_t *m, nnom_layer_t *input, nnom_layer_t *
 	if (output == NULL)
 		m->tail = find_last(input);
 
-	NNOM_LOG("\nStart compiling model...\n");
+	NNOM_LOG("\nNNoM version %d.%d.%d\n", NNOM_MAJORVERSION, NNOM_SUBVERSION, NNOM_REVISION);
+	NNOM_LOG("Start compiling model...\n");
 	NNOM_LOG("Layer(#)         Activation    output shape    ops(MAC)   mem(in, out, buf)      mem blk lifetime\n");
 	NNOM_LOG("-------------------------------------------------------------------------------------------------\n");