fix config example in pytorch mlp documentation
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		| @@ -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. | ||||
|         """ | ||||
|  | ||||
|   | ||||
| @@ -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] | ||||
|   | ||||
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