89 lines
2.6 KiB
Python
89 lines
2.6 KiB
Python
#####################################################
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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
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#####################################################
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import math
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import abc
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import numpy as np
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from typing import Optional
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import torch
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import torch.utils.data as data
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class UnifiedSplit:
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"""A class to unify the split strategy."""
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def __init__(self, total_num, mode):
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# Training Set 60%
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num_of_train = int(total_num * 0.6)
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# Validation Set 20%
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num_of_valid = int(total_num * 0.2)
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# Test Set 20%
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num_of_set = total_num - num_of_train - num_of_valid
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all_indexes = list(range(total_num))
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if mode is None:
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self._indexes = all_indexes
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elif mode.lower() in ("train", "training"):
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self._indexes = all_indexes[:num_of_train]
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elif mode.lower() in ("valid", "validation"):
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self._indexes = all_indexes[num_of_train : num_of_train + num_of_valid]
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elif mode.lower() in ("test", "testing"):
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self._indexes = all_indexes[num_of_train + num_of_valid :]
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else:
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raise ValueError("Unkonwn mode of {:}".format(mode))
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self._mode = mode
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@property
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def mode(self):
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return self._mode
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class TimeStamp(UnifiedSplit, data.Dataset):
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"""The timestamp dataset."""
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def __init__(
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self,
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min_timestamp: float = 0.0,
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max_timestamp: float = 1.0,
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num: int = 100,
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mode: Optional[str] = None,
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):
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self._min_timestamp = min_timestamp
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self._max_timestamp = max_timestamp
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self._interval = (max_timestamp - min_timestamp) / (float(num) - 1)
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self._total_num = num
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UnifiedSplit.__init__(self, self._total_num, mode)
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@property
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def min_timestamp(self):
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return self._min_timestamp
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@property
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def max_timestamp(self):
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return self._max_timestamp
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def __iter__(self):
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self._iter_num = 0
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return self
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def __next__(self):
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if self._iter_num >= len(self):
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raise StopIteration
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self._iter_num += 1
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return self.__getitem__(self._iter_num - 1)
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def __getitem__(self, index):
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assert 0 <= index < len(self), "{:} is not in [0, {:})".format(index, len(self))
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index = self._indexes[index]
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timestamp = self._min_timestamp + self._interval * index
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return index, timestamp
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def __len__(self):
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return len(self._indexes)
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def __repr__(self):
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return "{name}({cur_num:}/{total} elements)".format(
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name=self.__class__.__name__,
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cur_num=len(self),
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total=self._total_num,
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)
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