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authorGravatar Mikalai Drabovich <nick.drabovich@amd.com>2018-01-26 11:27:28 -0800
committerGravatar Rasmus Munk Larsen <rmlarsen@google.com>2018-01-26 11:27:28 -0800
commita169db5d066efd696d80fd989091a54cc4fe5baf (patch)
tree318284287e890d855bbfe98ed57f9e5a48a85467
parenta12bb2e5719e3cd17916690cc8caef0ec7bcdf4d (diff)
Update README.md (#16437)
* Update README.md -png, --sample_index options are not available in google-perftools (2.4-0ubuntu5.16.04.1). Also, since Ubuntu 16.04 wrongly recommends to install pprof from 'tau' package " The program 'pprof' is currently not installed. You can install it by typing: sudo apt install tau " the typical user command should probably be google-pprof --pdf --nodecount=100 <filename> * Add `google-perftools` installation Note.
-rw-r--r--tensorflow/core/profiler/README.md5
1 files changed, 3 insertions, 2 deletions
diff --git a/tensorflow/core/profiler/README.md b/tensorflow/core/profiler/README.md
index 9e628b1065..7997bdfa05 100644
--- a/tensorflow/core/profiler/README.md
+++ b/tensorflow/core/profiler/README.md
@@ -240,8 +240,9 @@ Open a Chrome browser, enter URL chrome://tracing and load the timeline file.
# can also generate memory profile using `-select bytes`
tfprof> code -select accelerator_micros -max_depth 100000 -output pprof:outfile=<filename> -trim_name_regexes .*apply_op.*
-# Use pprof to visualize the generated file.
-pprof -png --nodecount=100 --sample_index=1 <filename>
+# Use google-pprof, from the google-perftools package to visualize the generated file.
+# On Ubuntu you can install it with `apt-get install it google-perftools`.
+google-pprof --pdf --nodecount=100 <filename>
```
![PprofGraph](g3doc/pprof.jpg)