1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
|
#!/usr/bin/python
# Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class GraphStats():
def __init__(self):
from collections import Counter
from collections import defaultdict
self.op_counts = Counter()
self.filled_memory = 0
self.total_memory = 0
def accumulate_op_count(self, op_str, count):
self.op_counts[op_str] += count
def accumulate_filled_memory(self, size):
self.filled_memory += size
def accumulate_total_memory(self, size):
self.total_memory += size
def __iadd__(self, other):
self.op_counts += other.op_counts
self.filled_memory += other.filled_memory
self.total_memory += other.total_memory
return self
def PrintGraphStats(stats, verbose):
print("Number of all operator types: {0}".format(len(stats.op_counts)))
# Print op type stats
for op_name in sorted(stats.op_counts.keys()):
occur = stats.op_counts[op_name]
optype_info_str = "\t{:38}: {:4}".format(op_name, occur)
print(optype_info_str)
summary_str = "{0:46}: {1:4}".format("Number of all operators",
sum(stats.op_counts.values()))
print(summary_str)
print('')
# Print memory stats
from tensor_printer import ConvertBytesToHuman
print("Expected TOTAL memory: {0}".format(ConvertBytesToHuman(stats.total_memory)))
print("Expected FILLED memory: {0}".format(ConvertBytesToHuman(stats.filled_memory)))
print('')
def CalcGraphStats(op_parser):
stats = GraphStats()
for type_str, oper_list in op_parser.operators_per_type.items():
# number of occurrence of this operator type
occur = len(oper_list)
stats.accumulate_op_count(type_str, occur)
# this operator type can be computed?
can_compute = oper_list[0].operation.can_compute
total_memory = 0
filled_memory = 0 # only memory for constant
for tensor in op_parser.GetAllTensors():
if tensor.tf_buffer.DataLength() != 0:
filled_memory += tensor.memory_size
total_memory += tensor.memory_size
stats.accumulate_filled_memory(filled_memory)
stats.accumulate_total_memory(total_memory)
return stats
|
