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[Doctest]fix No.163,164,166, test=docs_preview #56527

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Sep 1, 2023
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[Doctest]fix No.163,164,166, test=docs_preview #56527

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[Doctest]fix No.163,164,166, test=docs_preview
liyongchao911 Aug 22, 2023
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update
liyongchao911 Aug 22, 2023
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Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
liyongchao911 Aug 27, 2023
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update
liyongchao911 Aug 27, 2023
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liyongchao911 Aug 29, 2023
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liyongchao911 Aug 31, 2023
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60 changes: 30 additions & 30 deletions python/paddle/vision/models/squeezenet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,20 +90,20 @@ class SqueezeNet(nn.Layer):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import SqueezeNet
>>> import paddle
>>> from paddle.vision.models import SqueezeNet

# build v1.0 model
model = SqueezeNet(version='1.0')
>>> # build v1.0 model
>>> model = SqueezeNet(version='1.0')

# build v1.1 model
# model = SqueezeNet(version='1.1')
>>> # build v1.1 model
>>> # model = SqueezeNet(version='1.1')

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""

def __init__(self, version, num_classes=1000, with_pool=True):
Expand Down Expand Up @@ -233,20 +233,20 @@ def squeezenet1_0(pretrained=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import squeezenet1_0
>>> import paddle
>>> from paddle.vision.models import squeezenet1_0

# build model
model = squeezenet1_0()
>>> # build model
>>> model = squeezenet1_0()

# build model and load imagenet pretrained weight
# model = squeezenet1_0(pretrained=True)
>>> # build model and load imagenet pretrained weight
>>> # model = squeezenet1_0(pretrained=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
return _squeezenet('squeezenet1_0', '1.0', pretrained, **kwargs)

Expand All @@ -267,19 +267,19 @@ def squeezenet1_1(pretrained=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import squeezenet1_1
>>> import paddle
>>> from paddle.vision.models import squeezenet1_1

# build model
model = squeezenet1_1()
>>> # build model
>>> model = squeezenet1_1()

# build model and load imagenet pretrained weight
# model = squeezenet1_1(pretrained=True)
>>> # build model and load imagenet pretrained weight
>>> # model = squeezenet1_1(pretrained=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
return _squeezenet('squeezenet1_1', '1.1', pretrained, **kwargs)
100 changes: 50 additions & 50 deletions python/paddle/vision/models/vgg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,21 +46,21 @@ class VGG(nn.Layer):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import VGG
from paddle.vision.models.vgg import make_layers
>>> import paddle
>>> from paddle.vision.models import VGG
>>> from paddle.vision.models.vgg import make_layers

vgg11_cfg = [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M']
>>> vgg11_cfg = [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M']

features = make_layers(vgg11_cfg)
>>> features = make_layers(vgg11_cfg)

vgg11 = VGG(features)
>>> vgg11 = VGG(features)

x = paddle.rand([1, 3, 224, 224])
out = vgg11(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = vgg11(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""

def __init__(self, features, num_classes=1000, with_pool=True):
Expand Down Expand Up @@ -212,20 +212,20 @@ def vgg11(pretrained=False, batch_norm=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import vgg11
>>> import paddle
>>> from paddle.vision.models import vgg11

# build model
model = vgg11()
>>> # build model
>>> model = vgg11()

# build vgg11 model with batch_norm
model = vgg11(batch_norm=True)
>>> # build vgg11 model with batch_norm
>>> model = vgg11(batch_norm=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
model_name = 'vgg11'
if batch_norm:
Expand All @@ -249,20 +249,20 @@ def vgg13(pretrained=False, batch_norm=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import vgg13
>>> import paddle
>>> from paddle.vision.models import vgg13

# build model
model = vgg13()
>>> # build model
>>> model = vgg13()

# build vgg13 model with batch_norm
model = vgg13(batch_norm=True)
>>> # build vgg13 model with batch_norm
>>> model = vgg13(batch_norm=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
model_name = 'vgg13'
if batch_norm:
Expand All @@ -286,20 +286,20 @@ def vgg16(pretrained=False, batch_norm=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import vgg16
>>> import paddle
>>> from paddle.vision.models import vgg16

# build model
model = vgg16()
>>> # build model
>>> model = vgg16()

# build vgg16 model with batch_norm
model = vgg16(batch_norm=True)
>>> # build vgg16 model with batch_norm
>>> model = vgg16(batch_norm=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
model_name = 'vgg16'
if batch_norm:
Expand All @@ -323,20 +323,20 @@ def vgg19(pretrained=False, batch_norm=False, **kwargs):
Examples:
.. code-block:: python

import paddle
from paddle.vision.models import vgg19
>>> import paddle
>>> from paddle.vision.models import vgg19

# build model
model = vgg19()
>>> # build model
>>> model = vgg19()

# build vgg19 model with batch_norm
model = vgg19(batch_norm=True)
>>> # build vgg19 model with batch_norm
>>> model = vgg19(batch_norm=True)

x = paddle.rand([1, 3, 224, 224])
out = model(x)
>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

print(out.shape)
# [1, 1000]
>>> print(out.shape)
[1, 1000]
"""
model_name = 'vgg19'
if batch_norm:
Expand Down
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