forked from PulseFocusPlatform/PulseFocusPlatform
70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
class NameAdapter(object):
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"""Fix the backbones variable names for pretrained weight"""
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def __init__(self, model):
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super(NameAdapter, self).__init__()
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self.model = model
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@property
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def model_type(self):
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return getattr(self.model, '_model_type', '')
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@property
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def variant(self):
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return getattr(self.model, 'variant', '')
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def fix_conv_norm_name(self, name):
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if name == "conv1":
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bn_name = "bn_" + name
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else:
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bn_name = "bn" + name[3:]
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# the naming rule is same as pretrained weight
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if self.model_type == 'SEResNeXt':
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bn_name = name + "_bn"
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return bn_name
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def fix_shortcut_name(self, name):
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if self.model_type == 'SEResNeXt':
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name = 'conv' + name + '_prj'
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return name
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def fix_bottleneck_name(self, name):
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if self.model_type == 'SEResNeXt':
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conv_name1 = 'conv' + name + '_x1'
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conv_name2 = 'conv' + name + '_x2'
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conv_name3 = 'conv' + name + '_x3'
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shortcut_name = name
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else:
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conv_name1 = name + "_branch2a"
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conv_name2 = name + "_branch2b"
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conv_name3 = name + "_branch2c"
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shortcut_name = name + "_branch1"
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return conv_name1, conv_name2, conv_name3, shortcut_name
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def fix_basicblock_name(self, name):
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if self.model_type == 'SEResNeXt':
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conv_name1 = 'conv' + name + '_x1'
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conv_name2 = 'conv' + name + '_x2'
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shortcut_name = name
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else:
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conv_name1 = name + "_branch2a"
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conv_name2 = name + "_branch2b"
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shortcut_name = name + "_branch1"
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return conv_name1, conv_name2, shortcut_name
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def fix_layer_warp_name(self, stage_num, count, i):
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name = 'res' + str(stage_num)
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if count > 10 and stage_num == 4:
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if i == 0:
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conv_name = name + "a"
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else:
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conv_name = name + "b" + str(i)
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else:
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conv_name = name + chr(ord("a") + i)
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if self.model_type == 'SEResNeXt':
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conv_name = str(stage_num + 2) + '_' + str(i + 1)
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return conv_name
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def fix_c1_stage_name(self):
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return "res_conv1" if self.model_type == 'ResNeXt' else "conv1"
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