FFinalized internal table storage code

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

@@ -11,10 +11,13 @@ class TableGenerator:
 
     def __init__(self, dir_name, iters, profiler_binary_name):
         self.__dir_name = dir_name
-        self.__network_name = dir_name
+
+        # directory/path/network_name (last item in path)  
+        self.__network_name = os.path.split(dir_name)[-1]
 
         self.__iters = iters 
         self.__profiler_binary_name = profiler_binary_name
+        self.__results_dir_name = "%s_results" % self.__dir_name
 
 
     def __is_binary(self, file_path):
@@ -27,7 +30,6 @@ class TableGenerator:
         if not os.path.isdir(self.__dir_name):
             print("ERROR: Directory %s not found" % self.__dir_name)
             exit(1)
-        self.__results_dir_name = "%s_results" % self.__dir_name 
 
         try:
             os.mkdir(self.__results_dir_name)
@@ -56,13 +58,14 @@ class TableGenerator:
 
 
     def __get_approximation_type(self, results_filename):
-        approx_type_start_ind = results_file.find(self.__network_name) \
+        approx_type_start_ind = results_filename.find(self.__network_name) \
                 + len(self.__network_name) + 1 # + 1 to account for _ delimiter
-        approx_type_end_ind = results_file.find(".txt")
+        approx_type_end_ind = results_filename.find(".txt")
         return results_filename[approx_type_start_ind : approx_type_end_ind] 
    
 
     def __parse_tensor_operation_line(self, tensor_op_line):
+        print(tensor_op_line)
         line_as_list = tensor_op_line.split(",")
         return line_as_list[0], line_as_list[1], line_as_list[2] 
 
@@ -76,19 +79,13 @@ class TableGenerator:
         return op_name[ : underscore_ind], op_name[underscore_ind + 1 : ]
 
     def generate_table(self):
-        # Copy ops file to results directory to use as empty table 
-        table_filename = os.path.join(self.__results_dir_name, \
-                    "%s_tensors.txt" % self.__network_name) 
-        # TODO un hard code this 
-        soc_operations_file_name = os.path.join("/home/nvidia/soc_simulator", \
-                        "%s_cifar10" % self.__network_name)
-        shutil.copyfile(soc_operations_file_name, table_filename) 
-      
         table = self.__build_nested_default_dict()
 
         for results_file_name in os.listdir(self.__results_dir_name):
-            # Ignore if not a results file
-            if not results_file_name.startswith(self.__network_name):
+            print(results_file_name, self.__network_name)
+            # Ignore if it's the output file or if it's not a results file
+            if results_file_name == table_filename or \
+                    not results_file_name.startswith(self.__network_name):
                 continue
 
             approx_type = self.__get_approximation_type(results_file_name)
@@ -96,12 +93,13 @@ class TableGenerator:
             results_file = open(os.path.join(self.__results_dir_name, results_file_name), "r")
 
             for line in results_file:
+                line = line.strip()
                 op_name, total_time, total_energy = self.__parse_tensor_operation_line(line)
                 print(op_name, total_time, total_energy)
 
                 # Handle _f2h and _h2f output for tensor operation
                 # Store as columns of original operation rather than independent rows 
-                if any(op_name.endswith(prec_conv) for prec_conv in precision_conversions):
+                if any(op_name.endswith(prec_conv) for prec_conv in TableGenerator.precision_conversions):
                     orig_op_name, conversion_type = self.__get_original_operation_name(op_name)
                     print("f2h/h2f", orig_op_name, conversion_type)
                     # Error bc original op name should ALWAYS be in the table
@@ -117,16 +115,31 @@ class TableGenerator:
                     table[op_name][approx_type]["energy"] = total_energy
 
             results_file.close()
+        # Then output everything
 
-        # <operation name> <type of approx> <time> <energy>
-        # Need to map to soc_operations file 
-        # final file should be in the format of the soc_operations file
-        # output file --> just need to search by the conv name 
-        # generate header
+        # Copy ops file to results directory to use as empty table 
+        table_filename = "%s_tensors.txt" % self.__network_name
+        table_file_path = os.path.join(self.__results_dir_name, table_filename)
+        # TODO un hard code this 
+        soc_operations_file_name = os.path.join("/home/nvidia/soc_simulator", \
+                        "%s_cifar10" % self.__network_name, "%s_ops.txt" % self.__network_name)
+        #shutil.copyfile(soc_operations_file_name, table_file_path)
+
+		# Output in the order of everything in the file
+		# Conv1,1 = leave the same
+		# Next line: Conv1 --> find it  
+		# don't need to copy the file over --> can use the original file as a reference
+		soc_operations_file = open(soc_operations_file_name, "r")
+		table_file = open(table_filename, "w")
+		for line in soc_operations_file:
+			if line.startswith("#"): # TODO variable
+				table_file.write(line) # Copy to table file 
+				# Then write the new header for 
+				
 
 binary_dir_name = "/home/nvidia/Gitlab/hpvm/llvm/projects/hpvm-tensor-rt/build_pldi/mobilenet"
 num_iters = 1 
 profiler_binary_name = "/home/nvidia/awesome_profiler/pp"
 table_gen = TableGenerator(binary_dir_name, num_iters, profiler_binary_name)
-table_gen.run_binaries_in_input_dir()
+#table_gen.run_binaries_in_input_dir()
 table_gen.generate_table()