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https://github.com/huggingface/pytorch-image-models.git
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* select_conv2d -> create_conv2d * added create_attn to create attention module from string/bool/module * factor padding helpers into own file, use in both conv2d_same and avg_pool2d_same * add some more test eca resnet variants * minor tweaks, naming, comments, consistency
31 lines
893 B
Python
31 lines
893 B
Python
""" Select AttentionFactory Method
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Hacked together by Ross Wightman
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"""
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import torch
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from .se import SEModule
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from .eca import EcaModule, CecaModule
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def create_attn(attn_type, channels, **kwargs):
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module_cls = None
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if attn_type is not None:
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if isinstance(attn_type, str):
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attn_type = attn_type.lower()
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if attn_type == 'se':
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module_cls = SEModule
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elif attn_type == 'eca':
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module_cls = EcaModule
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elif attn_type == 'eca':
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module_cls = CecaModule
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else:
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assert False, "Invalid attn module (%s)" % attn_type
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elif isinstance(attn_type, bool):
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if attn_type:
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module_cls = SEModule
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else:
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module_cls = attn_type
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if module_cls is not None:
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return module_cls(channels, **kwargs)
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return None
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