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import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layers import SelectAdaptivePool2d
from .gem import GeM
def create_pool2d_layer(name, **kwargs):
assert name in ["avg", "max", "fast", "avgmax", "catavgmax", "gem"]
if name != "gem":
pool2d_layer = SelectAdaptivePool2d(pool_type=name, flatten=True)
elif name == "gem":
pool2d_layer = GeM(dim=2, **kwargs)
return pool2d_layer