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https://github.com/webclinic017/drift.git
synced 2026-08-01 21:27:46 +00:00
Daniel Szemerey
d4676e099b
* feat: Refractored and created new model. Pipeline not ready yet. * feat: Implemented and refactored a data pipeline. * ref: Refractored to make more sense. * feat: Training works now with models that you can change. * feat: Added predict function but without working instructions. * feat: gitignore.
19 lines
623 B
Python
19 lines
623 B
Python
from pytorch_forecasting import TemporalFusionTransformer
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from pytorch_forecasting.metrics import QuantileLoss
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def create_TemporalFusionTransformer(training_dataset, model_options):
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# create the model
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tft = TemporalFusionTransformer.from_dataset(
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training_dataset,
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learning_rate=0.03,
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hidden_size=32,
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attention_head_size=1,
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dropout=0.1,
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hidden_continuous_size=16,
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output_size=7,
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loss=QuantileLoss(),
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log_interval=2,
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reduce_on_plateau_patience=4
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)
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print(f"Number of parameters in network: {tft.size()/1e3:.1f}k")
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return tft |