From f24a8d8120ad7543e2f46627c472921a126347fd Mon Sep 17 00:00:00 2001
From: Elizabeth <hashim.sharif91@gmail.com>
Date: Tue, 8 Oct 2019 18:22:57 -0500
Subject: [PATCH] Removed functionality to opush h2f/f2h conversions to the
back and added keys for all f2h/h2f conversions
---
.../build_pldi/table_generator.py | 59 +++++--------------
1 file changed, 16 insertions(+), 43 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 e6c4298f30..5d4aec4b94 100644
--- a/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py
+++ b/llvm/projects/hpvm-tensor-rt/build_pldi/table_generator.py
@@ -21,7 +21,6 @@ class TableGenerator:
self.__table_filename = "%s_tensors.txt" % self.__network_name
-
def __is_binary(self, file_path):
# Binary name must start with the network name as per our naming standards
return os.path.isfile(file_path) and os.access(file_path, os.X_OK) and \
@@ -80,7 +79,6 @@ class TableGenerator:
underscore_ind = op_name.find("_")
return op_name[ : underscore_ind], op_name[underscore_ind + 1 : ]
-
def generate_table(self):
self.__table = self.__build_nested_default_dict()
self.__build_internal_table()
@@ -101,16 +99,20 @@ class TableGenerator:
line = line.strip()
op_name, total_time, total_energy = self.__parse_tensor_operation_line(line)
+ # Conv1 --> all approximations --> store f2h and h2f as independent approximations
+ # Need to store their full names
# 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 TableGenerator.precision_conversions):
orig_op_name, conversion_type = self.__get_original_operation_name(op_name)
- # Error bc original op name should ALWAYS be in the 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)
- self.__table[orig_op_name][conversion_type]["time"] = total_time
- self.__table[orig_op_name][conversion_type]["energy"] = total_energy
+ # Need to store f2h and h2f for each type of approximation
+ conversion_key = "%s_%s" % (approx_type, conversion_type)
+ self.__table[orig_op_name][conversion_key]["time"] = total_time
+ self.__table[orig_op_name][conversion_key]["energy"] = total_energy
# Create a new row in the dictionary
else:
@@ -147,50 +149,21 @@ class TableGenerator:
curr_op = [curr_line] # Join into a string later
operation_data = self.__table[curr_line]
- h2f_data = [None] * 2
- f2h_data = [None] * 2
- has_h2f_field = False
- has_f2h_field = False
-
# Iterate through time/energy data for each approx type
for approx_type in operation_data:
op_time = operation_data[approx_type]["time"]
op_energy = operation_data[approx_type]["energy"]
- if approx_type == "h2f":
- h2f_data[0] = op_time
- h2f_data[1] = op_energy
- has_h2f_field = True
- elif approx_type == "f2h":
- f2h_data[0] = op_time
- f2h_data[1] = op_energy
- has_f2h_field = True
- else:
- curr_op.append(op_time)
- curr_op.append(op_energy)
-
- # 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("%s_time" % approx_type)
- header.append("%s_energy" % approx_type)
-
- # Guarantee that the quantization data is at the end of the col
- # TODO: How essential is this bc it increases the complexity of my code
- if has_h2f_field:
- curr_op.append(' '.join(h2f_data))
- if has_f2h_field:
- curr_op.append(' '.join(f2h_data))
- ops_in_layer.append(' '.join(curr_op))
+ # can either just be the approx time or can be the approx type_h2f/f2h field
+ curr_op.append(op_time)
+ curr_op.append(op_energy)
- # update header with h2f/f2h cols if they exist
- if has_h2f_field:
- header.append("h2f_time")
- header.append("h2f_energy")
-
- if has_f2h_field:
- header.append("f2h_time")
- header.append("f2h_energy")
+ # 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("%s_time" % approx_type)
+ header.append("%s_energy" % 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)
--
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