Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

[FEATURE] Handling TFRecords

See original GitHub issue

🚨🚨 Feature Request

Related to an existing Issue
A new implementation (Improvement, Extension)

Is your feature request related to a problem?

There is no opinionated way on how TFRecords should play with Hub.

If your feature will improve `HUB`

Treating TFRecords as if its a first class data type would reduce friction. Currently, users (like me) unpack TFRecords into str before pushing to Hub.

Issue Analytics

State:
Created 3 years ago
Comments:13 (12 by maintainers)

Top GitHub Comments

1reaction

DebadityaPalcommented, Feb 5, 2021

In their docs, I have found the TFRecords Reader twice.

tf.compat.v1.TFRecordsReader : Problem with this is it is deprecated in all versions of TF 2. Does not support eager execution.
tf.raw_ops.TFRecordsReader : Couldn’t find proper documentation for this, really hard to read and properly understand its current docs as not much is written, also does not support eager execution.

1reaction

DebadityaPalcommented, Feb 2, 2021

Yep! I shall get it done

Top Results From Across the Web

TFRecord and tf.train.Example | TensorFlow Core

The simplest way to handle non-scalar features is to use tf.io.serialize_tensor to convert tensors to binary-strings. Strings are scalars in TensorFlow.

A hands-on guide to TFRecords - Towards Data Science

Two things: The TFRecord file is stored sequentially, enabling fast streaming due to low access times. And secondly, the TFRecord files are ...

Tensorflow Records? What they are and how to use them

Another major advantage of TFRecords is that it is possible to store sequence data — for instance, a time series or word encodings...

Creating TFRecords - Keras

The TFRecord format is a simple format for storing a sequence of binary records. Converting your data into TFRecord has many advantages, such...

Introduction to TFRecords - PyImageSearch

TFRecord is a custom TensorFlow format for storing a sequence of binary records. TFRecords are highly optimized for TensorFlow, which lead to ...