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OpenDAS
vision
Commits
6eb1798f
Commit
6eb1798f
authored
Jul 05, 2019
by
ekka
Committed by
Francisco Massa
Jul 05, 2019
Browse files
Update docs of MnasNet (#1092)
This PR updates the docs of MnasNet
parent
d762537c
Changes
1
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28 additions
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4 deletions
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-4
torchvision/models/mnasnet.py
torchvision/models/mnasnet.py
+28
-4
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torchvision/models/mnasnet.py
View file @
6eb1798f
...
...
@@ -152,7 +152,13 @@ def _load_pretrained(model_name, model, progress):
def
mnasnet0_5
(
pretrained
=
False
,
progress
=
True
,
**
kwargs
):
""" MNASNet with depth multiplier of 0.5. """
"""MNASNet with depth multiplier of 0.5 from
`"MnasNet: Platform-Aware Neural Architecture Search for Mobile"
<https://arxiv.org/pdf/1807.11626.pdf>`_.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
progress (bool): If True, displays a progress bar of the download to stderr
"""
model
=
MNASNet
(
0.5
,
**
kwargs
)
if
pretrained
:
_load_pretrained
(
"mnasnet0_5"
,
model
,
progress
)
...
...
@@ -160,7 +166,13 @@ def mnasnet0_5(pretrained=False, progress=True, **kwargs):
def
mnasnet0_75
(
pretrained
=
False
,
progress
=
True
,
**
kwargs
):
""" MNASNet with depth multiplier of 0.75. """
"""MNASNet with depth multiplier of 0.75 from
`"MnasNet: Platform-Aware Neural Architecture Search for Mobile"
<https://arxiv.org/pdf/1807.11626.pdf>`_.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
progress (bool): If True, displays a progress bar of the download to stderr
"""
model
=
MNASNet
(
0.75
,
**
kwargs
)
if
pretrained
:
_load_pretrained
(
"mnasnet0_75"
,
model
,
progress
)
...
...
@@ -168,7 +180,13 @@ def mnasnet0_75(pretrained=False, progress=True, **kwargs):
def
mnasnet1_0
(
pretrained
=
False
,
progress
=
True
,
**
kwargs
):
""" MNASNet with depth multiplier of 1.0. """
"""MNASNet with depth multiplier of 1.0 from
`"MnasNet: Platform-Aware Neural Architecture Search for Mobile"
<https://arxiv.org/pdf/1807.11626.pdf>`_.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
progress (bool): If True, displays a progress bar of the download to stderr
"""
model
=
MNASNet
(
1.0
,
**
kwargs
)
if
pretrained
:
_load_pretrained
(
"mnasnet1_0"
,
model
,
progress
)
...
...
@@ -176,7 +194,13 @@ def mnasnet1_0(pretrained=False, progress=True, **kwargs):
def
mnasnet1_3
(
pretrained
=
False
,
progress
=
True
,
**
kwargs
):
""" MNASNet with depth multiplier of 1.3. """
"""MNASNet with depth multiplier of 1.3 from
`"MnasNet: Platform-Aware Neural Architecture Search for Mobile"
<https://arxiv.org/pdf/1807.11626.pdf>`_.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
progress (bool): If True, displays a progress bar of the download to stderr
"""
model
=
MNASNet
(
1.3
,
**
kwargs
)
if
pretrained
:
_load_pretrained
(
"mnasnet1_3"
,
model
,
progress
)
...
...
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