From b795a70102bbc6b0c26a57b0d7d87586500ac747 Mon Sep 17 00:00:00 2001 From: Yinon Polak Date: Tue, 28 Mar 2023 14:41:25 +0300 Subject: [PATCH] fix config example in pytorch mlp documentation --- freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py | 4 ++-- freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py b/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py index 389aa6155..a44214367 100644 --- a/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py +++ b/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py @@ -26,7 +26,7 @@ class PyTorchMLPClassifier(BasePyTorchClassifier): "trainer_kwargs": { "max_iters": 5000, "batch_size": 64, - "max_n_eval_batches": None, + "max_n_eval_batches": null, }, "model_kwargs": { "hidden_dim": 512, @@ -49,7 +49,7 @@ class PyTorchMLPClassifier(BasePyTorchClassifier): """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold - all the training and test data/labels. + all the training and test data/labels. :raises ValueError: If self.class_names is not defined in the parent class. """ diff --git a/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py b/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py index ca6a13f6e..6fc2be1a5 100644 --- a/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py +++ b/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py @@ -27,7 +27,7 @@ class PyTorchMLPRegressor(BasePyTorchRegressor): "trainer_kwargs": { "max_iters": 5000, "batch_size": 64, - "max_n_eval_batches": None, + "max_n_eval_batches": null, }, "model_kwargs": { "hidden_dim": 512, @@ -50,7 +50,7 @@ class PyTorchMLPRegressor(BasePyTorchRegressor): """ User sets up the training and test data to fit their desired model here :param data_dictionary: the dictionary constructed by DataHandler to hold - all the training and test data/labels. + all the training and test data/labels. """ n_features = data_dictionary["train_features"].shape[-1]