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Constructs a ShuffleNetV2 architecture with 0.5x output channels, as described in
`ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
`__.
Args:
weights (:class:`~torchvision.models.ShuffleNet_V2_X0_5_Weights`, optional): The
pretrained weights to use. See
:class:`~torchvision.models.ShuffleNet_V2_X0_5_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.shufflenetv2.ShuffleNetV2``
base class. Please refer to the `source code
`_
for more details about this class.
.. autoclass:: torchvision.models.ShuffleNet_V2_X0_5_Weights
:members:
ra ra ) 0 ` )r verifyr r r r s r) r r s, 4 )//8G (I7N YRX YYr+ c R t j | } t | |g dg dfi |S )a
Constructs a ShuffleNetV2 architecture with 1.0x output channels, as described in
`ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
`__.
Args:
weights (:class:`~torchvision.models.ShuffleNet_V2_X1_0_Weights`, optional): The
pretrained weights to use. See
:class:`~torchvision.models.ShuffleNet_V2_X1_0_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.shufflenetv2.ShuffleNetV2``
base class. Please refer to the `source code
`_
for more details about this class.
.. autoclass:: torchvision.models.ShuffleNet_V2_X1_0_Weights
:members:
r )r t r i r )r r r r s r) r r > , 4 )//8G (I7P [TZ [[r+ c R t j | } t | |g dg dfi |S )a
Constructs a ShuffleNetV2 architecture with 1.5x output channels, as described in
`ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
`__.
Args:
weights (:class:`~torchvision.models.ShuffleNet_V2_X1_5_Weights`, optional): The
pretrained weights to use. See
:class:`~torchvision.models.ShuffleNet_V2_X1_5_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.shufflenetv2.ShuffleNetV2``
base class. Please refer to the `source code
`_
for more details about this class.
.. autoclass:: torchvision.models.ShuffleNet_V2_X1_5_Weights
:members:
r )r i` i r )r r r r s r) r r ] r r+ c R t j | } t | |g dg dfi |S )a
Constructs a ShuffleNetV2 architecture with 2.0x output channels, as described in
`ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
`__.
Args:
weights (:class:`~torchvision.models.ShuffleNet_V2_X2_0_Weights`, optional): The
pretrained weights to use. See
:class:`~torchvision.models.ShuffleNet_V2_X2_0_Weights` below for
more details, and possible values. By default, no pre-trained
weights are used.
progress (bool, optional): If True, displays a progress bar of the
download to stderr. Default is True.
**kwargs: parameters passed to the ``torchvision.models.shufflenetv2.ShuffleNetV2``
base class. Please refer to the `source code
`_
for more details about this class.
.. autoclass:: torchvision.models.ShuffleNet_V2_X2_0_Weights
:members:
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