Closed KineticCookie closed 4 years ago
1) The protocol was created as a way to host both the documentation and module from the same URL. Although there are no planned features that required it, it seem better to leave the extensible option on the table rather than closed. Please file specific feature requests and :+1: accordingly.
2) At the moment, it is unclear if the version will be part of the protocol, or is left as something that exists at a layer above. For now it is a "recommended best practice".
3) Do you mean a local deployment of "tfhub.dev"? No. The hosting.md is all there is at the moment.
Thank you for the answer.
Do you mean a local deployment of "tfhub.dev"? No. The hosting.md is all there is at the moment.
I want to deploy a TF module registry for playground and was wondering if there is a solution to quickly create a TF hub compatible server, so I could access modules from internal network with x.x.x.x/modules/ssd/1
URL.
Seems like I need to develop a custom module registry server.
One alternative to hosting your own registry server is to store module archive file (.tar.gz archived module) in a GCS or S3 bucket. Then this file can be made public which would generate a URL to it. Then, this URL can be used in the constructor of hub.Module.
On Wed, Apr 18, 2018 at 10:15 AM Bulat notifications@github.com wrote:
Thank you for the answer.
Do you mean a local deployment of "tfhub.dev"? No. The hosting.md is all there is at the moment.
I want to deploy a TF module registry for playground and was wondering if there is a solution to quickly create a TF hub compatible server, so I could access modules from internal network with x.x.x.x/modules/ssd/1 URL.
Seems like I need to develop a custom module registry server.
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@akhorlin thanks for the solution. But I don't want to use cloud storages (all the work is done in LAN, and isolated) and the solution doesn't provide standardised docs for modules. (like https://www.tensorflow.org/hub/modules/google/imagenet/inception_v1/feature_vector/1)
Is there a docker image or maybe an instruction on how to do a local deployment of TF hub?
This is not exactly what you might have asked, but is related to TF-Hub and Docker. Namely, if you want to run TF Hub inside a docker container and run some of Colabs in that environment you can easily build a docker image that extents the Jupyter TensorFlow docker stack as follows:
Dockerfile
with:
# Start from a TensorFlow-compatible Docker image
FROM jupyter/tensorflow-notebook
# Add the extra dependencies for TF-hub
RUN pip install --upgrade pip
RUN pip install --upgrade "tensorflow>=1.7.0"
RUN pip install --upgrade tensorflow-hub
RUN pip install --upgrade seaborn
docker build --rm -t jupyter/tensorflow-with-tfhub-notebook .
docker run -p 8888:8888 jupyter/tensorflow-with-tfhub-notebook
ipynp
files and upload them to the local notebook --- they should run verbatim (although you might need to move any pip install
from the ipynp
cells to the Dockerfile
config).Any module you run will be locally cached in the TF-hub cache dir and will be part of your image. So, in theory, you could run all modules and they will be locally cached and part of the image.
Hello! I read docs and source code of TF hub and have questions:
Thank you in advance.