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from transformers import PretrainedConfig
class InternImageConfig(PretrainedConfig):
model_type = "intern_image"
def __init__(
self,
core_op='DCNv3_pytorch',
channels=64,
depths=(4, 4, 18, 4),
groups=(4, 8, 16, 32),
num_classes=1000,
mlp_ratio=4.,
drop_rate=0.,
drop_path_rate=0.1,
drop_path_type='linear',
act_layer='GELU',
norm_layer='LN',
layer_scale=None,
offset_scale=1.0,
post_norm=False,
cls_scale=1.5,
with_cp=False,
**kwargs,
):
self.core_op = core_op
self.channels = channels
self.depths = depths
self.groups = groups
self.num_classes = num_classes
self.mlp_ratio = mlp_ratio
self.drop_rate = drop_rate
self.drop_path_rate = drop_path_rate
self.drop_path_type = drop_path_type
self.act_layer = act_layer
self.norm_layer = norm_layer
self.layer_scale = layer_scale
self.offset_scale = offset_scale
self.post_norm = post_norm
self.cls_scale = cls_scale
self.with_cp = with_cp
super().__init__(**kwargs)
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