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[Enhancement] Support BoolTensor and LongTensor on Ascend NPU (#1011)
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@ -1,16 +1,26 @@
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# Copyright (c) OpenMMLab. All rights reserved.
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import itertools
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from collections.abc import Sized
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from typing import List, Union
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from typing import Any, List, Union
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import numpy as np
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import torch
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from mmengine.device import get_device
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from .base_data_element import BaseDataElement
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IndexType = Union[str, slice, int, list, torch.LongTensor,
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torch.cuda.LongTensor, torch.BoolTensor,
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torch.cuda.BoolTensor, np.ndarray]
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BoolTypeTensor: Union[Any]
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LongTypeTensor: Union[Any]
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if get_device() == 'npu':
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BoolTypeTensor = Union[torch.BoolTensor, torch.npu.BoolTensor]
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LongTypeTensor = Union[torch.LongTensor, torch.npu.LongTensor]
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else:
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BoolTypeTensor = Union[torch.BoolTensor, torch.cuda.BoolTensor]
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LongTypeTensor = Union[torch.LongTensor, torch.cuda.LongTensor]
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IndexType: Union[Any] = Union[str, slice, int, list, LongTypeTensor,
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BoolTypeTensor, np.ndarray]
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# Modified from
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@ -156,6 +166,7 @@ class InstanceData(BaseDataElement):
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Returns:
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:obj:`InstanceData`: Corresponding values.
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"""
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assert isinstance(item, IndexType.__args__)
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if isinstance(item, list):
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item = np.array(item)
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if isinstance(item, np.ndarray):
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@ -165,9 +176,6 @@ class InstanceData(BaseDataElement):
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# More details in https://github.com/numpy/numpy/issues/9464
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item = item.astype(np.int64) if item.dtype == np.int32 else item
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item = torch.from_numpy(item)
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assert isinstance(
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item, (str, slice, int, torch.LongTensor, torch.cuda.LongTensor,
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torch.BoolTensor, torch.cuda.BoolTensor))
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if isinstance(item, str):
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return getattr(self, item)
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@ -183,7 +191,7 @@ class InstanceData(BaseDataElement):
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if isinstance(item, torch.Tensor):
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assert item.dim() == 1, 'Only support to get the' \
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' values along the first dimension.'
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if isinstance(item, (torch.BoolTensor, torch.cuda.BoolTensor)):
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if isinstance(item, BoolTypeTensor.__args__):
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assert len(item) == len(self), 'The shape of the ' \
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'input(BoolTensor) ' \
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f'{len(item)} ' \
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@ -202,8 +210,7 @@ class InstanceData(BaseDataElement):
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v, (str, list, tuple)) or (hasattr(v, '__getitem__')
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and hasattr(v, 'cat')):
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# convert to indexes from BoolTensor
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if isinstance(item,
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(torch.BoolTensor, torch.cuda.BoolTensor)):
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if isinstance(item, BoolTypeTensor.__args__):
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indexes = torch.nonzero(item).view(
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-1).cpu().numpy().tolist()
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else:
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