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Run some Sanity Checks for PyAF 5.0 #224
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Invariance tests.
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For profiling, there are a lot of unnecessary precautions (np.clip(x, 0, None) for log(x), etc). These can sometimes be relaxed. |
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…the transformed signal in the model forecasts dataframe. Kolmogorov rocks.
Computation time for long term models. |
Memory footprint for long term models. |
This was referenced Mar 4, 2023
Closing. |
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…bage collection. Refactored perf computations.
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…bage collection. Refactored perf computations. Updated this notebook
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…. No need to transfer the whole pytorch/xgboost models to perform model selection. xeon-phi side-effect
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…. No need to transfer the whole pytorch/xgboost models to perform model selection. xeon-phi side-effect
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…tailed infor about test executions (Time, Memory, CPU usage).
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…tailed infor about test executions (Time, Memory, CPU usage).
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…tailed infor about test executions (Time, Memory, CPU usage).
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Following #45
Need to run some profiling checks to review the current state of PyAF 5.0.
A check for signal transformations stability and invariance is welcome.
To be included in the next PyAF release (5.0, expected on 2023-07-14).
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