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
85
86
87
88
|
# Copyright 2017 The TensorFlow Authors. 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.
# =============================================================================
"""Provides a proper python API for the symbols exported through swig."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python import pywrap_tensorflow as tf_wrap
from tensorflow.python.framework import errors
from tensorflow.python.grappler import cluster as gcluster
from tensorflow.python.grappler import item as gitem
def GenerateCostReport(metagraph,
per_node_report=False,
verbose=False,
cluster=None):
"""Analyze the cost of each TensorFlow op and node in the provided metagraph.
Args:
metagraph: A TensorFlow MetaGraphDef.
per_node_report: by default the report contains stats aggregated on a per op
type basis, setting per_node_report to True adds results for each
individual node to the report.
verbose: Prints out the entire operation proto instead of a summary table.
cluster: Analyze the costs using the specified cluster, or the local machine
if no cluster was specified.
Returns:
A string of cost report.
"""
if cluster is None:
cluster = gcluster.Cluster(disable_detailed_stats=False)
with errors.raise_exception_on_not_ok_status():
ret_from_swig = tf_wrap.GenerateCostReport(metagraph.SerializeToString(),
per_node_report, verbose,
cluster.tf_cluster)
return ret_from_swig
def GenerateMemoryReport(metagraph, detailed_report=True, cluster=None):
"""Analyze the peak memory usage for the provided metagraph.
Args:
metagraph: A TensorFlow MetaGraphDef.
detailed_report: print the live tensors in addition to the peak memory
usage.
cluster: Analyze the memory using the specified cluster, or the local
machine if no cluster was specified.
Returns:
A string with the formatted memory usage.
"""
if cluster is None:
cluster = gcluster.Cluster(
disable_detailed_stats=True, disable_timeline=True)
item = gitem.Item(metagraph)
peak_usage = cluster.DeterminePeakMemoryUsage(item)
report = ""
for device, snapshot in peak_usage.items():
peak_usage = snapshot[0]
report += "Peak usage for device " + device + ": " + str(
peak_usage) + " bytes\n"
if detailed_report:
live_tensors = snapshot[1]
for tensor in live_tensors:
op_name = tensor[0]
output_id = tensor[1]
mem_used = tensor[2]
report += " " + str(op_name) + ":" + str(output_id) + " uses " + str(
mem_used) + " bytes\n"
return report
|
