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tensorflow::ops::Conv::Attrs
#include <nn_ops.h>
Optional attribute setters for Conv.
Summary
Public functions
|
BatchDims(int64 x)
|
A positive integer specifying the number of batch dimensions for the input tensor.
|
DataFormat(StringPiece x)
|
Used to set the data format.
|
Dilations(const gtl::ArraySlice< int > & x)
|
1-D tensor of length N+2.
|
ExplicitPaddings(const gtl::ArraySlice< int > & x)
|
If padding is "EXPLICIT", the list of explicit padding amounts.
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Groups(int64 x)
|
A positive integer specifying the number of groups in which the input is split along the channel axis.
|
Public attributes
batch_dims_
int64 tensorflow::ops::Conv::Attrs::batch_dims_ = 1
StringPiece tensorflow::ops::Conv::Attrs::data_format_ = "CHANNELS_LAST"
dilations_
gtl::ArraySlice< int > tensorflow::ops::Conv::Attrs::dilations_ = {}
explicit_paddings_
gtl::ArraySlice< int > tensorflow::ops::Conv::Attrs::explicit_paddings_ = {}
groups_
int64 tensorflow::ops::Conv::Attrs::groups_ = 1
Public functions
BatchDims
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::BatchDims(
int64 x
)
A positive integer specifying the number of batch dimensions for the input tensor.
Should be less than the rank of the input tensor.
Defaults to 1
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::DataFormat(
StringPiece x
)
Used to set the data format.
By default CHANNELS_FIRST, uses NHWC (2D) / NDHWC (3D) or if CHANNELS_LAST, uses NCHW (2D) / NCDHW (3D).
Defaults to "CHANNELS_LAST"
Dilations
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Dilations(
const gtl::ArraySlice< int > & x
)
1-D tensor of length N+2.
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 channels_last_format, see above for details. Dilations in the batch and depth dimensions must be 1.
Defaults to []
ExplicitPaddings
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::ExplicitPaddings(
const gtl::ArraySlice< int > & x
)
If padding is "EXPLICIT", the list of explicit padding amounts.
For the ith dimension, the amount of padding inserted before and after the dimension is explicit_paddings[2 * i] and explicit_paddings[2 * i + 1], respectively. If padding is not "EXPLICIT", explicit_paddings must be empty.
Defaults to []
Groups
TF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Groups(
int64 x
)
A positive integer specifying the number of groups in which the input is split along the channel axis.
Each group is convolved separately with filters / groups filters. The output is the concatenation of all the groups results along the channel axis. Input channels and filters must both be divisible by groups.
Defaults to 1
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::Conv::Attrs Struct Reference\n\ntensorflow::ops::Conv::Attrs\n============================\n\n`#include \u003cnn_ops.h\u003e`\n\nOptional attribute setters for [Conv](/api_docs/cc/class/tensorflow/ops/conv#classtensorflow_1_1ops_1_1_conv).\n\nSummary\n-------\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------------------|--------------------------|\n| [batch_dims_](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a9ea9bdd5e248ff009ef531bbfe458e46)` = 1` | `int64` |\n| [data_format_](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1aff55695e98f834da10a285550804803b)` = \"CHANNELS_LAST\"` | `StringPiece` |\n| [dilations_](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a4db909083b6f27df6a69054889526a7b)` = {}` | `gtl::ArraySlice\u003c int \u003e` |\n| [explicit_paddings_](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a465c3aa7dc1f13dedb38a57ff159bd19)` = {}` | `gtl::ArraySlice\u003c int \u003e` |\n| [groups_](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a3c434b7123f5e61eefd679a18acbfa71)` = 1` | `int64` |\n\n| ### Public functions ||\n|----------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [BatchDims](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1ab5b8710f807f79223170880f93680a2d)`(int64 x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv/attrs#structtensorflow_1_1ops_1_1_conv_1_1_attrs) A positive integer specifying the number of batch dimensions for the input tensor. |\n| [DataFormat](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a804484932bce8c99d7845a8896aa8205)`(StringPiece x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv/attrs#structtensorflow_1_1ops_1_1_conv_1_1_attrs) Used to set the data format. |\n| [Dilations](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a82a108d5827ee742f96fc944ad7a533f)`(const gtl::ArraySlice\u003c int \u003e & x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv/attrs#structtensorflow_1_1ops_1_1_conv_1_1_attrs) 1-D tensor of length `N+2`. |\n| [ExplicitPaddings](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a602efcc50b119951e0ed1af441521f28)`(const gtl::ArraySlice\u003c int \u003e & x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv/attrs#structtensorflow_1_1ops_1_1_conv_1_1_attrs) If `padding` is `\"EXPLICIT\"`, the list of explicit padding amounts. |\n| [Groups](#structtensorflow_1_1ops_1_1_conv_1_1_attrs_1a244d82ecbf3be1e1abaf581a15fc546c)`(int64 x)` | `TF_MUST_USE_RESULT `[Attrs](/api_docs/cc/struct/tensorflow/ops/conv/attrs#structtensorflow_1_1ops_1_1_conv_1_1_attrs) A positive integer specifying the number of groups in which the input is split along the channel axis. |\n\nPublic attributes\n-----------------\n\n### batch_dims_\n\n```scdoc\nint64 tensorflow::ops::Conv::Attrs::batch_dims_ = 1\n``` \n\n### data_format_\n\n```scdoc\nStringPiece tensorflow::ops::Conv::Attrs::data_format_ = \"CHANNELS_LAST\"\n``` \n\n### dilations_\n\n```scdoc\ngtl::ArraySlice\u003c int \u003e tensorflow::ops::Conv::Attrs::dilations_ = {}\n``` \n\n### explicit_paddings_\n\n```scdoc\ngtl::ArraySlice\u003c int \u003e tensorflow::ops::Conv::Attrs::explicit_paddings_ = {}\n``` \n\n### groups_\n\n```scdoc\nint64 tensorflow::ops::Conv::Attrs::groups_ = 1\n``` \n\nPublic functions\n----------------\n\n### BatchDims\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::BatchDims(\n int64 x\n)\n``` \nA positive integer specifying the number of batch dimensions for the input tensor.\n\nShould be less than the rank of the input tensor.\n\nDefaults to 1 \n\n### DataFormat\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::DataFormat(\n StringPiece x\n)\n``` \nUsed to set the data format.\n\nBy default `CHANNELS_FIRST`, uses `NHWC (2D) / NDHWC (3D)` or if `CHANNELS_LAST`, uses `NCHW (2D) / NCDHW (3D)`.\n\nDefaults to \"CHANNELS_LAST\" \n\n### Dilations\n\n```gdscript\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Dilations(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \n1-D tensor of length `N+2`.\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 `channels_last_format`, see above for details. Dilations in the batch and depth dimensions must be 1.\n\nDefaults to \\[\\] \n\n### ExplicitPaddings\n\n```gdscript\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::ExplicitPaddings(\n const gtl::ArraySlice\u003c int \u003e & x\n)\n``` \nIf `padding` is `\"EXPLICIT\"`, the list of explicit padding amounts.\n\nFor the ith dimension, the amount of padding inserted before and after the dimension is `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If `padding` is not `\"EXPLICIT\"`, `explicit_paddings` must be empty.\n\nDefaults to \\[\\] \n\n### Groups\n\n```scdoc\nTF_MUST_USE_RESULT Attrs tensorflow::ops::Conv::Attrs::Groups(\n int64 x\n)\n``` \nA positive integer specifying the number of groups in which the input is split along the channel axis.\n\nEach group is convolved separately with `filters / groups` filters. The output is the concatenation of all the groups results along the channel axis. [Input](/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input) channels and filters must both be divisible by groups.\n\nDefaults to 1"]]
