Fixed input scaling bugs delay prediction model

compiler/characterizer/lib.py

@@ -585,11 +585,14 @@ class lib:
     def compute_delay(self):
         """Compute SRAM delays for current corner"""
         if self.use_model:
+            import math
             #FIXME: ML models only designed for delay. Cannot produce all values for Lib
             d = linear_regression()
-            model_inputs = [OPTS.num_words, 
+            temp_wpr = 2.0 #OPTS not working right now
+            log_num_words = math.log(OPTS.num_words, 2)
+            model_inputs = [log_num_words, 
                             OPTS.word_size, 
-                            OPTS.words_per_row, 
+                            temp_wpr, 
                             self.sram.width * self.sram.height]
             char_results = d.get_prediction(model_inputs)
         

compiler/characterizer/linear_regression.py

@@ -22,17 +22,14 @@ class linear_regression():
     def __init__(self):
         self.model = None
 
-    def get_prediction(self, model_inputs):
-
-        train_sets = []
-        test_sets = []     
+    def get_prediction(self, model_inputs): 
                
         file_path = data_dir +'/'+data_filename
-        scaled_inputs = np.asarray(scale_input_datapoint(model_inputs, data_dir))
+        scaled_inputs = np.asarray([scale_input_datapoint(model_inputs, data_dir)])
 
         features, labels = get_scaled_data(file_path, data_dir)
         self.train_model(features, labels)
-        scaled_pred = model_prediction(model_inputs)
+        scaled_pred = self.model_prediction(scaled_inputs)
         pred = unscale_data(scaled_pred.tolist(), data_dir)
         debug.info(1,"Unscaled Prediction = {}".format(pred))
         return pred