Replaced hard coded strs with variables for portability

llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py

@@ -6,7 +6,12 @@ import shutil
 from collections import defaultdict
 
 class TableGenerator: 
-   
+
+    __ops_header_delimiter = "#"
+    __table_header_delimter = "**" 
+    __time_col_name = "time" 
+    __energy_col_name = "energy"
+
     '''
     Stores all precision conversions used. 
     '''
@@ -37,8 +42,8 @@ class TableGenerator:
         self.__table = self.__build_nested_default_dict()
 
 
-	def generate_table(self):
-		'''
+    def generate_table(self):
+        '''
         Generates a table file called <network_name>_tensors.txt in the following 
         steps:
         1. Runs the offline profiler against the inputted binaries to generate
@@ -47,7 +52,7 @@ class TableGenerator:
         the offline profiler generated
         3. Writes the internal table to <network_name>_tensors.txt file and uses the 
         <network_name>_ops.txt file as a guideline in terms of row order 
-		'''
+        '''
         #self.__run_inputted_binaries()
         self.__build_internal_table()
         self.__output_table_to_file()
@@ -115,13 +120,13 @@ class TableGenerator:
                         exit(1)
 
                     # Store f2h and h2f as columns in the row belonging to the original operation
-                    self.__table[orig_op_name][approx_type]["time"] = total_time
-                    self.__table[orig_op_name][approx_type]["energy"] = total_energy
+                    self.__table[orig_op_name][approx_type][TableGenerator.__time_col_name] = total_time
+                    self.__table[orig_op_name][approx_type][TableGenerator.__energy_col_name] = total_energy
 
                 # Create a new row in the dictionary
                 else:
-                    self.__table[op_name][approx_type]["time"] = total_time
-                    self.__table[op_name][approx_type]["energy"] = total_energy
+                    self.__table[op_name][approx_type][TableGenerator.__time_col_name] = total_time
+                    self.__table[op_name][approx_type][TableGenerator.__energy_col_name] = total_energy
 
             results_file.close()
 
@@ -156,7 +161,7 @@ class TableGenerator:
             # The header is only generated for the first operation in the layer
             # CRITICAL ASSUMPTION: All operations within a layer have the same # columns
             # or everything breaks bc the header is per layer, not per operation
-            header = ["**", layer_name, str(num_ops)]
+            header = [TableGenerator.__table_header_delimter, layer_name, str(num_ops)]
 
             # Iterate through all operations within the layer 
             for op_in_layer_count in range(num_ops):
@@ -170,8 +175,8 @@ class TableGenerator:
                 # Iterate through time/energy data for each approximation type corresponding
                 # to the current operation
                 for approx_type in operation_data:
-                    op_time = operation_data[approx_type]["time"]
-                    op_energy = operation_data[approx_type]["energy"]
+                    op_time = operation_data[approx_type][TableGenerator.__time_col_name]
+                    op_energy = operation_data[approx_type][TableGenerator.__energy_col_name]
 
                     curr_op.append(op_time)
                     curr_op.append(op_energy)
@@ -273,7 +278,7 @@ class TableGenerator:
             number of ops in the layer
         '''
         comma_ind = layer_info_line.find(",")
-        return layer_info_line[layer_info_line.find("#") + 1 : comma_ind], \
+        return layer_info_line[layer_info_line.find(TableGenerator.__ops_header_delimiter) + 1 : comma_ind], \
                     int(layer_info_line[comma_ind + 1 : ])
 
 
@@ -282,5 +287,4 @@ if __name__ == "__main__":
     num_iters = 1 
     profiler_binary_name = "/home/nvidia/awesome_profiler/pp"
     table_gen = TableGenerator(binary_dir_path, num_iters, profiler_binary_name)
-    #table_gen.run_inputted_binaries()
     table_gen.generate_table()