From 80176cd79093ad7b649bdf3faf3ffb2dff1690b5 Mon Sep 17 00:00:00 2001
From: Elizabeth <hashim.sharif91@gmail.com>
Date: Tue, 8 Oct 2019 16:33:27 -0500
Subject: [PATCH] Implemented table outputter function
---
.../build_pldi/table_generator.py | 95 ++++++++++++++-----
1 file changed, 70 insertions(+), 25 deletions(-)
diff --git a/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py b/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py
index e944de7d37..71f88fed3e 100644
--- a/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py
+++ b/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py
@@ -79,13 +79,16 @@ class TableGenerator:
return op_name[ : underscore_ind], op_name[underscore_ind + 1 : ]
def generate_table(self):
- table = self.__build_nested_default_dict()
+ self.__table = self.__build_nested_default_dict()
+ self.__build_internal_table()
+ self.__output_table()
+
+ def __build_internal_table(self):
for results_file_name in os.listdir(self.__results_dir_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):
+ # Ignore if it's not a results file
+ if results_file_name.startswith(self.__network_name):
continue
approx_type = self.__get_approximation_type(results_file_name)
@@ -103,39 +106,81 @@ class TableGenerator:
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
- if orig_op_name not in table:
+ if orig_op_name not in self.__table:
print("ERROR: Conversion found but original %s is not in the table" % orig_op_name)
exit(1)
- table[orig_op_name][conversion_type]["time"] = total_time
- table[orig_op_name][conversion_type]["energy"] = total_energy
+ self.__table[orig_op_name][conversion_type]["time"] = total_time
+ self.__table[orig_op_name][conversion_type]["energy"] = total_energy
# Create a new row in the dictionary
else:
- table[op_name][approx_type]["time"] = total_time
- table[op_name][approx_type]["energy"] = total_energy
+ self.__table[op_name][approx_type]["time"] = total_time
+ self.__table[op_name][approx_type]["energy"] = total_energy
results_file.close()
- # Then output everything
+ def __output_table(self):
# 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
-
+ soc_operations_file_name = os.path.join("/home/nvidia/soc_simulator", "%s_cifar10" % self.__network_name, "%s_ops.txt" % self.__network_name)
+
+ # 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")
+
+ # Read header line to get layer name and # operations in layer
+ # Get ops in each layer using the dict
+ # TODO possible for operations in the same layer to not have the same # of cols?
+ # Need to store a list of all 2nd level dict keys we go through!
+ # at the very end --> then generate the header and write everything in
+
+ curr_line = soc_operations_file.readline().strip()
+
+ while curr_line:
+ # First line is always the layers line (#layer_name,num_ops)
+ layer_name, num_ops = self.__parse_layer_info_line(curr_line)
+
+ # Get each operation in the layer
+ ops_in_layer = []
+ header = []
+
+ for op_in_layer_count in range(num_ops):
+ # Each line consists of operation name
+ curr_line = soc_operations_file.readline().strip()
+
+ curr_op = [curr_line] # Join into a string later
+ operation_data = self.__table[curr_line]
+ # Iterate through time/energy data for each approx type
+ for approx_type in operation_data:
+ curr_op.append(operation_data[approx_type]["time"])
+ curr_op.append(operation_data[approx_type]["time"])
+
+ # CRITICAL ASSUMPTION: All ops within a layer have the same # cols
+ # Only fill out the header once for the layer
+ if op_in_layer_count == 0:
+ header.append(approx_type)
+
+ ops_in_layer.append(' '.join(curr_op))
+ # Getting all operation rows and then writing everything because
+ # calls to write() are slow (memory vs time tradeoff)
+ print("%s" % ' '.join(header))
+ print("%s" % '\n'.join(ops_in_layer))
+ table_file.write("%s\n" % ' '.join(header))
+ table_file.write("%s\n" % '\n'.join(ops_in_layer))
+
+ curr_line = soc_operations_file.readline().strip()
+
+ def __parse_layer_info_line(self, layer_info_line): #layer_name,num_ops
+ comma_ind = layer_info_line.find(",")
+ return layer_info_line[layer_info_line.find("#") : comma_ind], int(layer_info_line[comma_ind + 1 : ])
+
+ def __generate_header(self, table):
+ # <approx type time/energy> <conversion type at very end>
+ # should the header be per tensor op or per layer?
+ # Try doing this per layer first
+ pass
binary_dir_name = "/home/nvidia/Gitlab/hpvm/llvm/projects/hpvm-tensor-rt/build_pldi/mobilenet"
num_iters = 1
--
GitLab