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SigureMo authored Jun 14, 2022
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4 changes: 2 additions & 2 deletions docs/api/paddle/vision/models/ResNet_cn.rst
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.. py:class:: paddle.vision.models.ResNet(Block, depth=50, width=64, num_classes=1000, with_pool=True, groups=1)
ResNet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::
Expand All @@ -19,7 +19,7 @@ ResNet模型,来自论文 `"Deep Residual Learning for Image Recognition" <htt

返回
:::::::::
ResNet模型,Layer的实例
ResNet 模型,:ref:`api_fluid_dygraph_Layer` 的实例

代码示例
:::::::::
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7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnet101_cn.rst
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.. py:function:: paddle.vision.models.resnet101(pretrained=False, **kwargs)
101层的resnet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
101 层的 ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnet101模型,Layer的实例。

101 层的 ResNet 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnet101
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnet152_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnet152
.. py:function:: paddle.vision.models.resnet152(pretrained=False, **kwargs)
152层的resnet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
152 层的 ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnet152模型,Layer的实例。

152 层的 ResNet 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnet152
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnet18_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnet18
.. py:function:: paddle.vision.models.resnet18(pretrained=False, **kwargs)
18层的resnet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
18 层的 ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnet18模型,Layer的实例。

18 层的 ResNet 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnet18
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnet34_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnet34
.. py:function:: paddle.vision.models.resnet34(pretrained=False, **kwargs)
34层的resnet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
34 层的 ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnet34模型,Layer的实例。

34 层的 ResNet 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnet34
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnet50_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnet50
.. py:function:: paddle.vision.models.resnet50(pretrained=False, **kwargs)
50层的resnet模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。
50 层的 ResNet 模型,来自论文 `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnet50模型,Layer的实例。

50 层的 ResNet 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnet50
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext101_32x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext101_32x4d
.. py:function:: paddle.vision.models.resnext101_32x4d(pretrained=False, **kwargs)
ResNeXt-101 32x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-101 32x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext101_32x4d模型,Layer的实例。

ResNeXt-101 32x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext101_32x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext101_64x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext101_64x4d
.. py:function:: paddle.vision.models.resnext101_64x4d(pretrained=False, **kwargs)
ResNeXt-101 64x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-101 64x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext101_64x4d模型,Layer的实例。

ResNeXt-101 64x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext101_64x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext152_32x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext152_32x4d
.. py:function:: paddle.vision.models.resnext152_32x4d(pretrained=False, **kwargs)
ResNeXt-152 32x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-152 32x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext152_32x4d模型,Layer的实例。

ResNeXt-152 32x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext152_32x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext152_64x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext152_64x4d
.. py:function:: paddle.vision.models.resnext152_64x4d(pretrained=False, **kwargs)
ResNeXt-152 64x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-152 64x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext152_64x4d模型,Layer的实例。

ResNeXt-152 64x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext152_64x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext50_32x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext50_32x4d
.. py:function:: paddle.vision.models.resnext50_32x4d(pretrained=False, **kwargs)
ResNeXt-50 32x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-50 32x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext50_32x4d模型,Layer的实例。

ResNeXt-50 32x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext50_32x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/resnext50_64x4d_cn.rst
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Expand Up @@ -6,16 +6,19 @@ resnext50_64x4d
.. py:function:: paddle.vision.models.resnext50_64x4d(pretrained=False, **kwargs)
ResNeXt-50 64x4d模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。
ResNeXt-50 64x4d 模型,来自论文 `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
resnext50_64x4d模型,Layer的实例。

ResNeXt-50 64x4d 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.resnext50_64x4d
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/wide_resnet101_2_cn.rst
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Expand Up @@ -6,16 +6,19 @@ wide_resnet101_2
.. py:function:: paddle.vision.models.wide_resnet101_2(pretrained=False, **kwargs)
101层的wide_resnet模型,来自论文 `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ 。
Wide ResNet-101-2 模型,来自论文 `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
wide_resnet101_2模型,Layer的实例。

Wide ResNet-101-2 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.wide_resnet101_2
7 changes: 5 additions & 2 deletions docs/api/paddle/vision/models/wide_resnet50_2_cn.rst
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Expand Up @@ -6,16 +6,19 @@ wide_resnet50_2
.. py:function:: paddle.vision.models.wide_resnet50_2(pretrained=False, **kwargs)
50层的wide_resnet模型,来自论文 `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ 。
Wide ResNet-50-2 模型,来自论文 `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ 。

参数
:::::::::

- **pretrained** (bool,可选) - 是否加载在imagenet数据集上的预训练权重。默认值:False。

返回
:::::::::
wide_resnet50_2模型,Layer的实例。

Wide ResNet-50-2 模型,:ref:`cn_api_fluid_dygraph_Layer` 的实例。

代码示例
:::::::::

COPY-FROM: paddle.vision.models.wide_resnet50_2

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