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mlops
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Description
We're running usability tests and would love for you to record walking through our tutorials. The idea for this ticket is that you do a screen capture walking through one of more of the following examples:
- Hello World! (15 minutes)
- [Iris Dataset](https://kedro.readthedocs.io/en/stable/02_get_started
🚨 🚨 Feature Request
We need description, citation, license, and version meta info to be added to the dataset.
Is your feature request related to a problem?
Some datasets need this info inside them for legal reasons.
If your feature will improve HUB
Easy to implement, won't hurt for sure.
Description of the possible solution
Currently, we have all metadata store
Fixed size batching
Hello,
Would it be feasible to activate batching at a fixed size. As far as I know bentoML actually implement both non-batching and micro-bacthing which is adaptive one.
For certain architectures as AWS instances, the torchscript compiler is based on fixed batch size.
Thanks!
For SC Operator it may be a good idea to generate CRD manifests from inside a docker container.
This should provide reproducible generation step and avoid "produces different output on my machine" issues.
Linter should also fail if generation of manifests produce diff with the commited version.
Steps to reproduce
In Full Kubeflow mode, select a pipeline and click Create Run. During selecting experiment, open a dialog to select existing experiment.
By default, there is no available experiment, but there is no w
Describe the Issue
In pytest-flyte, @samhita-alla has a pr that will enable us to test flyte workflow but we don't have many examples of pytest-flyte. Ideally, we should write a test for each example workflow and that should be the best practice of flyte workflow development and release
The goal of this issue is to write a test for each workflow example of flytesnacks, This task is huge i
from jrieke on Slack:
"path/anaconda3/lib/python3.7/site-packages/aimrecords/artifact_storage/storage.py:3: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3,and in 3.9 it will stop working.
from collections import Iterator`"
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Describe the bug
When trying to run scaffolding (profiling) command, it fails because of commas in columns.
To Reproduce
Steps to reproduce the behavior:
great_expectations suite scaffold scaffold-nameon datasource where commas are in columnpandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 5323 saw 2Expected behavior
D