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I am about to embark on making some primitive version of TensorBoard for my DRL library built with TorchSharp.
If any of you are interested in something like this perhaps you can give me some tips how to make it more universal. I've no idea how original TensorBoard is built and I'm not going to check.
For this one I'm planning on using the stack:
Blazor Server for backend
Plotly for charting
rxnet to wire things internally
SignalR to talk to Blazor Server application
I'm going to write it as standalone application so its always possible to add something later... Eventually it will be customisable but for now I dont have time/energy. I was going to expose interfaces for things such as:
Plots over time:
Loss
Learning Rate
Rewards
Cumulative reward
Episode length
KL Divergence
Entropy
Methods:
-Export plot as csv
-Save model to path
-Save buffer to path
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Hey TorchSharp community.
I am about to embark on making some primitive version of TensorBoard for my DRL library built with TorchSharp.
If any of you are interested in something like this perhaps you can give me some tips how to make it more universal. I've no idea how original TensorBoard is built and I'm not going to check.
For this one I'm planning on using the stack:
Blazor Server for backend
Plotly for charting
rxnet to wire things internally
SignalR to talk to Blazor Server application
I'm going to write it as standalone application so its always possible to add something later... Eventually it will be customisable but for now I dont have time/energy. I was going to expose interfaces for things such as:
Plots over time:
Loss
Learning Rate
Rewards
Cumulative reward
Episode length
KL Divergence
Entropy
Methods:
-Export plot as csv
-Save model to path
-Save buffer to path
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