fix conv3d #4904
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fix conv3d #4904
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✅ This PR's description meets the template requirements! |
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感谢你贡献飞桨文档，文档预览构建中，Docs-New 跑完后即可预览，预览链接：http://preview-pr-4904.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
Ligoml
approved these changes
Jun 6, 2022
| @@ -37,7 +37,7 @@ conv3d | |||
| 参数 | |||
| :::::::::::: | |||
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| - **x** (Tensor) - 输入是形状为 :math:`[N, C, H, W]` 或 :math:`[N, H, W, C]` 的4-D Tensor，N是批尺寸，C是通道数，H是特征高度，W是特征宽度，数据类型为float16, float32或float64。 | |||
| - **x** (Tensor) - 输入是形状为 :math:`[N, C, D, H, W]` 或 :math:`[N, D, H, W, C]` 的5-D Tensor，N是批尺寸，C是通道数，D是特征层深度，H是特征高度，W是特征宽度，数据类型为float16, float32或float64。 | |||
| - **weight** (Tensor) - 形状为 :math:`[M, C/g, kH, kW]` 的卷积核（卷积核）。 M是输出通道数， g是分组的个数，kH是卷积核的高度，kW是卷积核的宽度。 | |||
| - **bias** (int|list|tuple) - 偏置项，形状为： :math:`[M,]` 。 | |||
| @@ -46,7 +46,7 @@ conv3d | |||
| - **groups** (int，可选) - 二维卷积层的组数。根据Alex Krizhevsky的深度卷积神经网络（CNN）论文中的成组卷积：当group=n，输入和卷积核分别根据通道数量平均分为n组，第一组卷积核和第一组输入进行卷积计算，第二组卷积核和第二组输入进行卷积计算，……，第n组卷积核和第n组输入进行卷积计算。默认值：1。 | |||
| - **weight_attr** (ParamAttr，可选) - 指定权重参数属性的对象。默认值为None，表示使用默认的权重参数属性。具体用法请参见 :ref:`cn_api_fluid_ParamAttr` 。 | |||
| - **bias_attr** （ParamAttr|bool，可选）- 指定偏置参数属性的对象。若 ``bias_attr`` 为bool类型，只支持为False，表示没有偏置参数。默认值为None，表示使用默认的偏置参数属性。具体用法请参见 :ref:`cn_api_fluid_ParamAttr` 。 | |||
| - **data_format** (str，可选) - 指定输入的数据格式，输出的数据格式将与输入保持一致，可以是"NCHW"和"NHWC"。N是批尺寸，C是通道数，H是特征高度，W是特征宽度。默认值："NCHW"。 | |||
| - **data_format** (str，可选) - 指定输入的数据格式，输出的数据格式将与输入保持一致，可以是"NCDHW"和"NDHWC"。N是批尺寸，C是通道数，D是特征层深度，H是特征高度，W是特征宽度。默认值："NCDHW"。 | |||
| - **name** (str，可选) – 具体用法请参见 :ref:`cn_api_guide_Name` ，一般无需设置，默认值：None。 | |||
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fix conv3d description