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Another feature idea is for a case where we allow the user to upload their model, which we will train for them and evaluate on a chosen benchmark with a chose metric.
We can think of ways to use op…
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I am trying to implement the improved-ddpm project using google colab (1 GPU), I am not sure how to rectify the distributed training problem coming because of the following code
```
Traceback …
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I am following the tutorial on distributed training here https://nixtlaverse.nixtla.io/neuralforecast/docs/tutorials/distributed_neuralforecast.html .
I am using a hdfs backend instead of S3. My da…
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Hello, is there a solution for distributed learning ?
I think the most obvious is to create a small server then send samples to convnetsharp?
Support of RNN is coming soon?
Thank you:)
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Hi!
All Versions under 2.10 result in NAN Values for the loss etc. (as mentioned by another user). Therefore i am using v2.10-cpu with directML plugin, as windows native isnt supported anymore.
…
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Hello.
I have adapted the code from FasterRCNN_train.py to use distributed learning. This is what the learner creation looks like:
```
# Instantiate the learners and the trainer object
num_qua…
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Dear Fluid TOC members and maintainers,
I am proposing to have Shiming Wu(GithubID: wushiming540) as a new committer.
Wu Shiming, senior engineer of Huawei's NAIE platform, is responsible for l…
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Hi,
Looking at the source code, it seems to me that parallelization beyond a single node is currently not supported for Tabular by autogluon. I didn't find an issue dedicated to this topic (however…
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Hello!
Since it required huge amount of computing resources to teach network - is it possible to create some distributed system, where everyone who is willing can join and contribute their machine r…
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**Is your feature request related to a problem? Please describe.**
Could Cellpose use something like [SageMaker SDK
](https://docs.aws.amazon.com/sagemaker/latest/dg/distributed-training.html)
To…