New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ERRO[4334] error getting events from daemon: EOF #31220

Open
BenjiKCF opened this Issue Feb 21, 2017 · 14 comments

Comments

Projects
None yet
8 participants
@BenjiKCF

BenjiKCF commented Feb 21, 2017


BUG REPORT INFORMATION

Description

Hello everyone, after following the google codelabs, Codelabs I have received an error ERRO[4334] error getting events from daemon: EOF after Creating bottleneck at /tf_files/bottlenecks/roses/13231224664_4af5293a37.jpg.txt

Update:
I reran it and this shows up
ERRO[53469] error getting events from daemon: EOF

Steps to reproduce the issue:
1.

 python tensorflow/examples/image_retraining/retrain.py \
> --bottleneck_dir=/tf_files/bottlenecks \
> --how_many_training_steps 500 \
> --model_dir=/tf_files/inception \
> --output_graph=/tf_files/retrained_graph.pb \
> --output_labels=/tf_files/retrained_labels.txt \
> --image_dir /tf_files/flower_photos

Describe the results you received:
ERRO[4334] error getting events from daemon: EOF

Describe the results you expected:
Finish the retraining

Output of docker version:

Docker version 1.13.1, build 092cba3

Output of docker info:

Containers: 6
 Running: 0
 Paused: 0
 Stopped: 6
Images: 2
Server Version: 1.13.1
Storage Driver: overlay2
 Backing Filesystem: extfs
 Supports d_type: true
 Native Overlay Diff: true
Logging Driver: json-file
Cgroup Driver: cgroupfs
Plugins: 
 Volume: local
 Network: bridge host ipvlan macvlan null overlay
Swarm: inactive
Runtimes: runc
Default Runtime: runc
Init Binary: docker-init
containerd version: aa8187dbd3b7ad67d8e5e3a15115d3eef43a7ed1
runc version: 9df8b306d01f59d3a8029be411de015b7304dd8f
init version: 949e6fa
Security Options:
 seccomp
  Profile: default
Kernel Version: 4.9.8-moby
Operating System: Alpine Linux v3.5
OSType: linux
Architecture: x86_64
CPUs: 2
Total Memory: 1.952 GiB
Name: moby
ID: UNXQ:IPAT:2ZHG:3443:M7XI:M3FW:W7Q7:G4HV:IKKW:W5TU:72TI:SH3G
Docker Root Dir: /var/lib/docker
Debug Mode (client): false
Debug Mode (server): true
 File Descriptors: 16
 Goroutines: 27
 System Time: 2017-02-21T14:43:50.071749826Z
 EventsListeners: 1
No Proxy: *.local, 169.254/16
Registry: https://index.docker.io/v1/
Experimental: true
Insecure Registries:
 127.0.0.0/8
Live Restore Enabled: false

Additional environment details (AWS, VirtualBox, physical, etc.):
OS X with python 2.7,
and this shows up
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. Thank you so much

@tomgs

This comment has been minimized.

Show comment
Hide comment
@tomgs

tomgs Mar 2, 2017

Happened to me as well, different error codes though.

tomgs commented Mar 2, 2017

Happened to me as well, different error codes though.

@BenjiKCF

This comment has been minimized.

Show comment
Hide comment
@BenjiKCF

BenjiKCF Mar 22, 2017

Yes, the error code varies all the time.

BenjiKCF commented Mar 22, 2017

Yes, the error code varies all the time.

@uncle-mo

This comment has been minimized.

Show comment
Hide comment
@uncle-mo

uncle-mo Mar 23, 2017

I had this same issue. Having made the following changes I ran the script again and I didn't see the issue again.

In "Docker > Preferences" I increased the CPU's to 4 (from 2) as per the instructions here https://www.reddit.com/r/tensorflow/comments/5uhac5/docker_issues/

I also increased the RAM but I'm not sure if that was required.

uncle-mo commented Mar 23, 2017

I had this same issue. Having made the following changes I ran the script again and I didn't see the issue again.

In "Docker > Preferences" I increased the CPU's to 4 (from 2) as per the instructions here https://www.reddit.com/r/tensorflow/comments/5uhac5/docker_issues/

I also increased the RAM but I'm not sure if that was required.

@cazantyl

This comment has been minimized.

Show comment
Hide comment
@cazantyl

cazantyl Mar 27, 2017

uncle-mo's answer fixed my issue. Just needed to bump the CPU's to 4

cazantyl commented Mar 27, 2017

uncle-mo's answer fixed my issue. Just needed to bump the CPU's to 4

@pelly

This comment has been minimized.

Show comment
Hide comment
@pelly

pelly Jun 2, 2017

Are there any plans to look at underlying issue? I'm getting a similar error and would like to keep the CPUs dedicated to 2.

pelly commented Jun 2, 2017

Are there any plans to look at underlying issue? I'm getting a similar error and would like to keep the CPUs dedicated to 2.

@cpuguy83

This comment has been minimized.

Show comment
Hide comment
@cpuguy83

cpuguy83 Jun 2, 2017

Contributor

Can you provide the daemon logs from when this occurs?

Contributor

cpuguy83 commented Jun 2, 2017

Can you provide the daemon logs from when this occurs?

@pelly

This comment has been minimized.

Show comment
Hide comment
@pelly

pelly Jun 2, 2017

pelly commented Jun 2, 2017

@cpuguy83

This comment has been minimized.

Show comment
Hide comment
@cpuguy83

cpuguy83 Jun 2, 2017

Contributor

@pelly This would be logs for the daemon itself, not the container.
@justincormack What's the best way to get daemon logs on docker4mac? (@pelly I'm assuming you are on Docker4Mac).

Contributor

cpuguy83 commented Jun 2, 2017

@pelly This would be logs for the daemon itself, not the container.
@justincormack What's the best way to get daemon logs on docker4mac? (@pelly I'm assuming you are on Docker4Mac).

@thaJeztah

This comment has been minimized.

Show comment
Hide comment
@thaJeztah

thaJeztah Jun 2, 2017

Member

@cpuguy83 @pelly something like this should work;

docker run --rm -v /var/log:/logs alpine cat /logs/docker.log > daemon-logs

Which puts the logs in a local file named daemon-logs

Member

thaJeztah commented Jun 2, 2017

@cpuguy83 @pelly something like this should work;

docker run --rm -v /var/log:/logs alpine cat /logs/docker.log > daemon-logs

Which puts the logs in a local file named daemon-logs

@pelly

This comment has been minimized.

Show comment
Hide comment
@pelly

pelly Jun 2, 2017

pelly commented Jun 2, 2017

@pelly

This comment has been minimized.

Show comment
Hide comment
@pelly

pelly Jun 2, 2017

Log file needed a supported extension (used .txt)
docker_log.txt

pelly commented Jun 2, 2017

Log file needed a supported extension (used .txt)
docker_log.txt

@cpuguy83

This comment has been minimized.

Show comment
Hide comment
@cpuguy83

cpuguy83 Jun 5, 2017

Contributor

It looks like the daemon is restarting but I do not see why it would be restarting.
Is this on docker4mac? @pelly

Contributor

cpuguy83 commented Jun 5, 2017

It looks like the daemon is restarting but I do not see why it would be restarting.
Is this on docker4mac? @pelly

@pelly

This comment has been minimized.

Show comment
Hide comment
@pelly

pelly Jun 5, 2017

pelly commented Jun 5, 2017

@cancerberoSgx

This comment has been minimized.

Show comment
Hide comment
@cancerberoSgx

cancerberoSgx Oct 18, 2017

same here I-m getting this error in a high performance task that exit with that same error and the docker daemon is restarted. In my case removing the --privileged argument from my docker run command solved the problem !

cancerberoSgx commented Oct 18, 2017

same here I-m getting this error in a high performance task that exit with that same error and the docker daemon is restarted. In my case removing the --privileged argument from my docker run command solved the problem !

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment