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Merge pull request #8596 from autoscatto/bugfix/tensor-to-numpy

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Bugfix/tensor to numpy
This commit is contained in:
Robert Caulk
2023-05-06 17:31:49 +02:00
committed by GitHub
parent efb5cd6545 908a2e817a
commit e365e913c7
2 changed files with 5 additions and 3 deletions
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5
freqtrade/freqai/base_models/BasePyTorchClassifier.py
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@@ -45,6 +45,7 @@ class BasePyTorchClassifier(BasePyTorchModel):
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
:param dk: dk: The datakitchen object
:param unfiltered_df: Full dataframe for the current backtest period.
:return:
:pred_df: dataframe containing the predictions
@@ -78,7 +79,9 @@ class BasePyTorchClassifier(BasePyTorchModel):
probs = F.softmax(logits, dim=-1)
predicted_classes = torch.argmax(probs, dim=-1)
predicted_classes_str = self.decode_class_names(predicted_classes)
pred_df_prob = DataFrame(probs.detach().numpy(), columns=class_names)
# used .tolist to convert probs into an iterable, in this way Tensors
# are automatically moved to the CPU first if necessary.
pred_df_prob = DataFrame(probs.detach().tolist(), columns=class_names)
pred_df = DataFrame(predicted_classes_str, columns=[dk.label_list[0]])
pred_df = pd.concat([pred_df, pred_df_prob], axis=1)
return (pred_df, dk.do_predict)

3
freqtrade/freqai/base_models/BasePyTorchRegressor.py
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@@ -45,6 +45,5 @@ class BasePyTorchRegressor(BasePyTorchModel):
device=self.device
)
y = self.model.model(x)
y = y.cpu()
pred_df = DataFrame(y.detach().numpy(), columns=[dk.label_list[0]])
pred_df = DataFrame(y.detach().tolist(), columns=[dk.label_list[0]])
return (pred_df, dk.do_predict)