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Add tensorflow-serving-api to jupyter image #358
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/assign @jlewi |
@@ -1,5 +1,12 @@ | |||
# Copyright (c) Jupyter Development Team. | |||
# Distributed under the terms of the Modified BSD License. | |||
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# TODO(inc0): When tf-serving-api becomes available for py3, this should be |
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What about the GPU image?
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We merged images together now, rebased for it
@@ -161,6 +168,8 @@ RUN apt-get update && apt-get install -yq --no-install-recommends graphviz \ | |||
# Install Python 3 Tensorflow without GPU support | |||
RUN pip install --quiet --no-cache-dir tf-nightly | |||
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COPY --from=tf-serving-install /usr/local/lib/python2.7/site-packages/tensorflow_serving /opt/conda/lib/python3.6/site-packages/tensorflow_serving |
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Using the 2.7 version of TF Serving API with Python 3 seems like a recipe for problems.
Do we really want to do this?
It seems like a bad idea. But since this is what the official docs say:
https://github.com/tensorflow/serving/blob/master/tensorflow_serving/g3doc/setup.md#tensorflow-serving-python-api-pip-package
I guess it might be OK. Can you please add a comment though that this is what the docs recommend?
/lgtm |
Test failure looks unrelated to this PR
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@inc0 can you try syncing? I suspect you just need to pull in changes to the tests. |
It's really hacky way to add api to jupyter image. We should remove it and make it properly once package becomes available for python 3. Fixes kubeflow#355
/lgtm |
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: jlewi The full list of commands accepted by this bot can be found here. The pull request process is described here
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* fix for backtick escape error * rebased from upstream/master
It's really hacky way to add api to jupyter image. We should remove it
and make it properly once package becomes available for python 3.
Fixes #355
This change is