tensorflow / tensorflow/datasets
Document how to use TFDS on Colab with TPU
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- Dominant language
- Python
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Description
What I need help with / What I was wondering
When trying to use TFDS on Google Colab with TPU acceleration, there's the following exception:
UnimplementedError: File system scheme '[local]' not implemented
What I've tried so far
From e.g. https://cloud.google.com/tpu/docs/quickstart one can see that TPUs expect data to be stored on GCS.
However there are examples using Keras+TPU on Colab which load data via tf.keras.datasets, such as:
https://colab.research.google.com/gist/ceshine/f196d6b030adb1ec3a8d0b50642709dc/keras-fashion-mnist-tpu.ipynb
It would be nice if...
...there was documentation on how to use TFDS with Keras using TPU on Colab.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Read the linked Google Cloud TPU quickstart and Keras+TPU Colab notebook first, then compare their data-loading approaches with TFDS. Document a reproducible TFDS-with-Keras workflow for Colab TPU acceleration, including how to avoid the '[local]' filesystem exception and where data should be stored.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- google-cloud, python, tensorflow
- Domain
- cloud, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100