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tensorflow::ops::Conv3D::Attrs
#include <nn_ops.h>
Optional attribute setters for Conv3D.
Summary
Public functions
|
DataFormat(StringPiece x)
|
The data format of the input and output data.
|
Dilations(const gtl::ArraySlice< int > & x)
|
1-D tensor of length 5.
|
Public attributes
StringPiece tensorflow::ops::Conv3D::Attrs::data_format_ = "NDHWC"
dilations_
gtl::ArraySlice< int > tensorflow::ops::Conv3D::Attrs::dilations_ = Default_dilations()
Public functions
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3D::Attrs::DataFormat(
StringPiece x
)
The data format of the input and output data.
With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].
Defaults to "NDHWC"
Dilations
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3D::Attrs::Dilations(
const gtl::ArraySlice< int > & x
)
1-D tensor of length 5.
The dilation factor for each dimension of input. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of data_format, see above for details. Dilations in the batch and depth dimensions must be 1.
Defaults to [1, 1, 1, 1, 1]
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Last updated 2021-11-15 UTC.
[null,null,["Last updated 2021-11-15 UTC."],[],[],null,["# tensorflow::ops::Conv3D::Attrs Struct Reference\n\ntensorflow::ops::Conv3D::Attrs\n==============================\n\n`#include \u003cnn_ops.h\u003e`\n\nOptional attribute setters for [Conv3D](/api_docs/cc/class/tensorflow/ops/conv3-d#classtensorflow_1_1ops_1_1_conv3_d).\n\nSummary\n-------\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------------------------------|--------------------------|\n| [data_format_](#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs_1aed2017811fa48a9095b4329677adea1d)` = \"NDHWC\"` | `StringPiece` |\n| [dilations_](#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs_1a41ef9508f16643fccb3cb6b78b120a54)` = Default_dilations()` | `gtl::ArraySlice\u003c int \u003e` |\n\n| ### Public functions ||\n|------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs_1a8c135a3b483a824e4ae79d3574ae0037)`(StringPiece x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs) The data format of the input and output data. |\n| [Dilations](#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs_1a86d275095e5694eccb3ed56c1e366e1f)`(const gtl::ArraySlice\u003c int \u003e & x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv3-d/attrs#structtensorflow_1_1ops_1_1_conv3_d_1_1_attrs) 1-D tensor of length 5. |\n\nPublic attributes\n-----------------\n\n### data_format_\n\n```scdoc\nStringPiece tensorflow::ops::Conv3D::Attrs::data_format_ = \"NDHWC\"\n``` \n\n### dilations_\n\n```scdoc\ngtl::ArraySlice\u003c int \u003e tensorflow::ops::Conv3D::Attrs::dilations_ = Default_dilations()\n``` \n\nPublic functions\n----------------\n\n### DataFormat\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3D::Attrs::DataFormat(\n StringPiece x\n)\n``` \nThe data format of the input and output data.\n\nWith the default format \"NDHWC\", the data is stored in the order of: \\[batch, in_depth, in_height, in_width, in_channels\\]. Alternatively, the format could be \"NCDHW\", the data storage order is: \\[batch, in_channels, in_depth, in_height, in_width\\].\n\nDefaults to \"NDHWC\" \n\n### Dilations\n\n```gdscript\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv3D::Attrs::Dilations(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \n1-D tensor of length 5.\n\nThe dilation factor for each dimension of `input`. If set to k \\\u003e 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1.\n\nDefaults to \\[1, 1, 1, 1, 1\\]"]]
