Migrate TFJob examples to TensorFlow 2

[sandipanpanda]

What this PR does / why we need it:
Upgrade TensorFlow version in all Dockerfiles to v2

Which issue(s) this PR fixes (optional, in Fixes #<issue number>, #<issue number>, ... format, will close the issue(s) when PR gets merged):
Part of #2015

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[tenzen-y]

@sandipanpanda Have you tried to build and run these in your local?
I guess that some of these couldn't be buildable or runnable.

[tenzen-y]

@kubeflow/wg-training-leads Could you approve CI?

[coveralls]

Pull Request Test Coverage Report for Build 8224250888

Details

• 0 of 0 changed or added relevant lines in 0 files are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage increased (+0.01%) to 42.885%

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Totals
Change from base Build 8214367884:	0.01%
Covered Lines:	3755
Relevant Lines:	8756

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💛 - Coveralls

[tenzen-y]

@sandipanpanda Have you tried to build and run these in your local? I guess that some of these couldn't be buildable or runnable.

Oh, CI proves that all images are buildable.
@sandipanpanda So, can you verify that those images are runnable?

[andreyvelich]

Thank you for your contribution @sandipanpanda 🎉
@tenzen-y Is right, unfortunately we don't run all TensorFlow examples in on CI to verify them.

I am pretty sure that some TensorFlow APIs that we are using in examples are not compatible with TensorFlow 2.0.

For example, tf.train.AdamOptimizer is tf.keras.optimizers.Adam in TF2: https://www.tensorflow.org/guide/migrate/migrate_tf2

So you might need to run these examples manually to migrate to Tensorflow 2.0 unless we will add them to our CI.

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[sandipanpanda]

@tenzen-y @andreyvelich Thank you for reviewing.

I have started working on migrating TFJob examples to TensorFlow 2 using the migration guide.

• Upgrade TensorFlow version in all Dockerfiles to v2
• Run the automated script to convert some of your TF1.x API usage to tf.compat.v1.
• Remove old tf.contrib.layers and replace them with TF Slim symbols. Also check TF Addons for other tf.contrib symbols.
• Rewrite your TF1.x model forward passes to run in TF2 with eager execution enabled.
• Validate the accuracy and numerical correctness of your migrated code.
• Upgrade your training, evaluation and model saving code to TF2 equivalents.
• (Optional) Migrate your TF2-compatible tf.compat.v1 APIs including TF Slim usage to idiomatic TF2 APIs.