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--- software:singularity:caviness [2018-08-09 12:45] – anita
+++ software:singularity:caviness [2021-05-06 18:45] (current) – [Troubleshooting] anita
@@ Line 23: / Line 23: @@
 <code>
 $ vpkg_require singularity
-$ $ singularity build hello-world.simg shub://vsoch/hello-worldw
+$ singularity build hello-world.simg shub://vsoch/hello-worldw
 </code>
@@ Line 36: / Line 36: @@
 ===== Execute your Singularity container through SLURM =====
-Once your container is on Caviness you can run it. Containers must run on Caviness' compute nodes, not on the head node. Remember you must specify a workgroup before running any jobs on Caviness, then use either the ''salloc'' or ''sbatch'' command to get access to a compute node.  See the [[abstract:caviness:runjobs:runjobs|Running Jobs on Caviness]] for more information on SLURM and using Caviness' compute nodes.
+Once your container is on Caviness you can run it. Containers must run on Caviness' compute nodes, not on the head node. Remember you must specify a **[[abstract:caviness:app_dev:compute_env#using-workgroup-and-directories|workgroup]]** before running any jobs on Caviness, then use either the ''salloc'' or ''sbatch'' command to get access to a compute node.  See the [[abstract:caviness:runjobs:runjobs|Running Jobs on Caviness]] for more information on SLURM and using Caviness' compute nodes.
 ==== Inside your interactive session or your batch job you must first issue the command ====
@@ Line 47: / Line 47: @@
 <code>
+[traine@login01 ~]$ workgroup -g it_css
+[(it_css:traine)@login01 ~]$ salloc --ntasks=1 --cpus-per-task=4
+salloc: Granted job allocation 844
+salloc: Waiting for resource configuration
+salloc: Nodes r00n45 are ready for job
+[traine@r00n45 ~]$ vpkg_require singularity
+Adding package `singularity/2.5.1` to your environment
+[traine@r00n45 ~]$ singularity shell tensorflow.simg
+Singularity: Invoking an interactive shell within container...
-    [(it_css:traine)@login01 ~]$ salloc --ntasks=1 --cpus-per-task=4
+Singularity tensorflow.simg:~> tensorboard --help
-    salloc: Granted job allocation 844
+usage: tensorboard [-h] [--logdir PATH] [--host ADDR] [--port PORT]
-    salloc: Waiting for resource configuration
+                   [--purge_orphaned_data BOOL] [--reload_interval SECONDS]
-    salloc: Nodes r00n45 are ready for job
+                   [--db URI] [--inspect] [--tag TAG] [--event_file PATH]
-    [traine@r00n45 ~]$ vpkg_require singularity
+                   [--path_prefix PATH] [--window_title TEXT]
-    Adding package `singularity/2.5.1` to your environment
+                   [--max_reload_threads COUNT]
-    [traine@r00n45 ~]$ singularity shell tensorflow.simg
+                   [--samples_per_plugin SAMPLES_PER_PLUGIN]
-    Singularity: Invoking an interactive shell within container...
+                   [--master_tpu_unsecure_channel ADDR]
+                   [--debugger_data_server_grpc_port PORT]
+                   [--debugger_port PORT]
-    Singularity tensorflow.simg:~> tensorboard --help
+TensorBoard is a suite of web applications for inspectinng and understanding
+your TensorFlow runs and graphs. https://github.com/tensorflow/tensorboard
-           USAGE: /usr/local/bin/tensorboard [flags]
+Singularity tensorflow.simg:~> grep Cpus_allowed_list /proc/$$/status
+Cpus_allowed_list:	0-3
+Singularity tensorflow.simg:~> exit
+exit
+[traine@r00n45 ~]$
+</code>
+==== Troubleshooting ====
+=== Locale error ===
+If you experience the error below after starting a particular shell container, then it is likely due to your current locale not being supported in this particular container's shell.
+<code bash>
+[traine@r00n45 ~]$ vpkg_require singularity
+Adding package `singularity/2.5.1` to your environment
+[traine@r00n45 ~]$ singularity shell tensorflow.simg
+Singularity: Invoking an interactive shell within container...
+Singularity tensorflow.simg:~> tensorboard --help
+Traceback (most recent call last):
+  File "/usr/local/bin/tensorboard", line 11, in <module>
+    sys.exit(run_main())
+  File "/usr/local/lib/python2.7/dist-packages/tensorboard/main.py", line 48, in run_main
+    program.setup_environment()
+  File "/usr/local/lib/python2.7/dist-packages/tensorboard/program.py", line 57, in setup_environment
+    util.setup_logging()
+  File "/usr/local/lib/python2.7/dist-packages/tensorboard/util.py", line 50, in setup_logging
+    locale.setlocale(locale.LC_ALL, '')
+  File "/usr/lib/python2.7/locale.py", line 581, in setlocale
+    return _setlocale(category, locale)
+locale.Error: unsupported locale setting
+</code>
+Once you start the container shell, check which locale's are supported by using the ''locale -a'' command:
+<code bash>
+Singularity tensorflow.simg:~> locale -a
+locale: Cannot set LC_CTYPE to default locale: No such file or directory
+locale: Cannot set LC_MESSAGES to default locale: No such file or directory
+locale: Cannot set LC_COLLATE to default locale: No such file or directory
+C
+C.UTF-8
+POSIX
+</code>
+Of course in this particular case, the locale setting for account ''traine'' is defined as ''en_US.UTF-8'' which is not supported in this shell.  To fix the situation, simply set the ''LANG'' locale to one that is supported before starting the container shell.
+<code bash>
+[traine@r00n45 ~]$ vpkg_require singularity
+Adding package `singularity/2.5.1` to your environment
+[tainne@r00n45 ~]$ LANG=C.UTF-8 singularity shell tensorflow.simg
+Singularity: Invoking an interactive shell within container...
+Singularity tensorflow.simg:~> tensorboard --help
+usage: tensorboard [-h] [--logdir PATH] [--host ADDR] [--port PORT]
+                   [--purge_orphaned_data BOOL] [--reload_interval SECONDS]
+                   [--db URI] [--inspect] [--tag TAG] [--event_file PATH]
+                   [--path_prefix PATH] [--window_title TEXT]
+                   [--max_reload_threads COUNT]
+                   [--samples_per_plugin SAMPLES_PER_PLUGIN]
+                   [--master_tpu_unsecure_channel ADDR]
+                   [--debugger_data_server_grpc_port PORT]
+                   [--debugger_port PORT]
+TensorBoard is a suite of web applications for inspectinng and understanding
+your TensorFlow runs and graphs. https://github.com/tensorflow/tensorboard
-    Try --helpfull to get a list of all flags.
+[[ lots of additional information displayed for optional arguments
-    Singularity tensorflow.simg:~> grep Cpus_allowed_list /proc/$$/status
+Singularity tensorflow.simg:~> exit
-    Cpus_allowed_list:	0-3
+exit
-    Singularity tensorflow.simg:~>
+[traine@r00n45 ~]$
 </code>