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40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import logging
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from abc import ABC, abstractmethod
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import torch
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from freqtrade.freqai.freqai_interface import IFreqaiModel
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from freqtrade.freqai.torch.PyTorchDataConvertor import PyTorchDataConvertor
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logger = logging.getLogger(__name__)
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class BasePyTorchModel(IFreqaiModel, ABC):
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"""
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Base class for PyTorch type models.
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User *must* inherit from this class and set fit() and predict() and
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data_convertor property.
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"""
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def __init__(self, **kwargs):
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super().__init__(config=kwargs["config"])
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self.dd.model_type = "pytorch"
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self.device = (
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"mps"
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if torch.backends.mps.is_available() and torch.backends.mps.is_built()
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else ("cuda" if torch.cuda.is_available() else "cpu")
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)
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test_size = self.freqai_info.get("data_split_parameters", {}).get("test_size")
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self.splits = ["train", "test"] if test_size != 0 else ["train"]
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self.window_size = self.freqai_info.get("conv_width", 1)
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@property
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@abstractmethod
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def data_convertor(self) -> PyTorchDataConvertor:
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"""
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a class responsible for converting `*_features` & `*_labels` pandas dataframes
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to pytorch tensors.
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"""
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raise NotImplementedError("Abstract property")
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