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add documentation

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This commit is contained in:
Yinon Polak 2023-03-09 11:21:10 +02:00
parent 3081b9402b
commit ba5de0cd00
1 changed files with 8 additions and 4 deletions
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12
freqtrade/freqai/base_models/PyTorchModelTrainer.py
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@ -54,10 +54,7 @@ class PyTorchModelTrainer:
def fit(self, data_dictionary: Dict[str, pd.DataFrame]): def fit(self, data_dictionary: Dict[str, pd.DataFrame]):
""" """
general training loop: General training loop.
- converting data to tensors
- calculating n_epochs
-
""" """
data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary) data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary)
epochs = self.calc_n_epochs( epochs = self.calc_n_epochs(
@ -117,6 +114,9 @@ class PyTorchModelTrainer:
self, self,
data_dictionary: Dict[str, pd.DataFrame] data_dictionary: Dict[str, pd.DataFrame]
) -> Dict[str, DataLoader]: ) -> Dict[str, DataLoader]:
"""
Converts the input data to PyTorch tensors using a data loader.
"""
data_loader_dictionary = {} data_loader_dictionary = {}
for split in ['train', 'test']: for split in ['train', 'test']:
labels_shape = data_dictionary[f'{split}_labels'].shape labels_shape = data_dictionary[f'{split}_labels'].shape
@ -141,6 +141,10 @@ class PyTorchModelTrainer:
@staticmethod @staticmethod
def calc_n_epochs(n_obs: int, batch_size: int, n_iters: int) -> int: def calc_n_epochs(n_obs: int, batch_size: int, n_iters: int) -> int:
"""
Calculates the number of epochs required to reach the maximum number
of iterations specified in the model training parameters.
"""
n_batches = n_obs // batch_size n_batches = n_obs // batch_size
epochs = n_iters // n_batches epochs = n_iters // n_batches
return epochs return epochs