__init__.py 2.12 KB
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"""The models subpackage contains definitions for the following model
architectures:

-  `AlexNet`_
-  `VGG`_
-  `ResNet`_
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-  `SqueezeNet`_
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-  `DenseNet`_
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You can construct a model with random weights by calling its constructor:

.. code:: python

    import torchvision.models as models
    resnet18 = models.resnet18()
    alexnet = models.alexnet()
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    squeezenet = models.squeezenet1_0()
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    densenet = models.densenet_161()
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We provide pre-trained models for the ResNet variants and AlexNet, using the
PyTorch :mod:`torch.utils.model_zoo`. These can  constructed by passing
``pretrained=True``:

.. code:: python

    import torchvision.models as models
    resnet18 = models.resnet18(pretrained=True)
    alexnet = models.alexnet(pretrained=True)

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ImageNet 1-crop error rates (224x224)

======================== =============   =============
Network                  Top-1 error     Top-5 error
======================== =============   =============
ResNet-18                30.24           10.92
ResNet-34                26.70           8.58
ResNet-50                23.85           7.13
ResNet-101               22.63           6.44
ResNet-152               21.69           5.94
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Inception v3             22.55           6.44
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AlexNet                  43.45           20.91
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VGG-11                   30.98           11.37
VGG-13                   30.07           10.75
VGG-16                   28.41           9.62
VGG-19                   27.62           9.12
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SqueezeNet 1.0           41.90           19.58
SqueezeNet 1.1           41.81           19.38
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Densenet-121             25.35           7.83
Densenet-169             24.00           7.00
Densenet-201             22.80           6.43
Densenet-161             22.35           6.20
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======================== =============   =============


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.. _AlexNet: https://arxiv.org/abs/1404.5997
.. _VGG: https://arxiv.org/abs/1409.1556
.. _ResNet: https://arxiv.org/abs/1512.03385
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.. _SqueezeNet: https://arxiv.org/abs/1602.07360
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.. _DenseNet: https://arxiv.org/abs/1608.06993
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"""

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from .alexnet import *
from .resnet import *
from .vgg import *
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from .squeezenet import *
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from .inception import *
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from .densenet import *