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#hide
from utils import *
Computer vision¶
cnn_learner¶
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model_meta[resnet50]
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{'cut': -2,
'split': <function fastai2.vision.learner._resnet_split(m)>,
'stats': ([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])}
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create_head(20,2)
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Sequential(
(0): AdaptiveConcatPool2d(
(ap): AdaptiveAvgPool2d(output_size=1)
(mp): AdaptiveMaxPool2d(output_size=1)
)
(1): full: False
(2): BatchNorm1d(20, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): Dropout(p=0.25, inplace=False)
(4): Linear(in_features=20, out_features=512, bias=False)
(5): ReLU(inplace=True)
(6): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(7): Dropout(p=0.5, inplace=False)
(8): Linear(in_features=512, out_features=2, bias=False)
)
unet_learner¶
Natural language processing¶
Tabular¶
Wrapping up architectures¶
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