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pytorch - set n_steps type as optional

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This commit is contained in:
yinon
2023-08-04 14:33:59 +00:00
parent 9f69a45afd
commit 23d2bad2a0
1 changed files with 7 additions and 13 deletions
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freqtrade/freqai/torch/PyTorchModelTrainer.py
+7 -13
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@@ -50,9 +50,9 @@ class PyTorchModelTrainer(PyTorchTrainerInterface):
self.criterion = criterion self.criterion = criterion
self.model_meta_data = model_meta_data self.model_meta_data = model_meta_data
self.device = device self.device = device
self.n_steps: int = kwargs.get("n_steps", None)
self.n_epochs: Optional[int] = kwargs.get("n_epochs", 10) self.n_epochs: Optional[int] = kwargs.get("n_epochs", 10)
if not self.n_steps and not self.n_epochs: self.n_steps: Optional[int] = kwargs.get("n_steps", None)
if self.n_steps is None and not self.n_epochs:
raise Exception("Either `n_steps` or `n_epochs` should be set.") raise Exception("Either `n_steps` or `n_epochs` should be set.")
self.batch_size: int = kwargs.get("batch_size", 64) self.batch_size: int = kwargs.get("batch_size", 64)
@@ -79,12 +79,7 @@ class PyTorchModelTrainer(PyTorchTrainerInterface):
data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary, splits) data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary, splits)
n_obs = len(data_dictionary["train_features"]) n_obs = len(data_dictionary["train_features"])
n_epochs = self.n_epochs or self.calc_n_epochs( n_epochs = self.n_epochs or self.calc_n_epochs(n_obs=n_obs)
n_obs=n_obs,
batch_size=self.batch_size,
n_iters=self.n_steps,
)
batch_counter = 0 batch_counter = 0
for _ in range(n_epochs): for _ in range(n_epochs):
for _, batch_data in enumerate(data_loaders_dictionary["train"]): for _, batch_data in enumerate(data_loaders_dictionary["train"]):
@@ -147,8 +142,7 @@ class PyTorchModelTrainer(PyTorchTrainerInterface):
return data_loader_dictionary return data_loader_dictionary
@staticmethod def calc_n_epochs(self, n_obs: 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 Calculates the number of epochs required to reach the maximum number
of iterations specified in the model training parameters. of iterations specified in the model training parameters.
@@ -156,9 +150,9 @@ class PyTorchModelTrainer(PyTorchTrainerInterface):
the motivation here is that `n_steps` is easier to optimize and keep stable, the motivation here is that `n_steps` is easier to optimize and keep stable,
across different n_obs - the number of data points. across different n_obs - the number of data points.
""" """
assert isinstance(self.n_steps, int), "Either `n_steps` or `n_epochs` should be set."
n_batches = n_obs // batch_size n_batches = n_obs // self.batch_size
n_epochs = min(n_iters // n_batches, 1) n_epochs = min(self.n_steps // n_batches, 1)
if n_epochs <= 10: if n_epochs <= 10:
logger.warning( logger.warning(
f"Setting low n_epochs: {n_epochs}. " f"Setting low n_epochs: {n_epochs}. "