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tensorflow::ops::MaxPool3DGradGrad
#include <nn_ops.h>
Computes second-order gradients of the maxpooling function.
Summary
Arguments:
- scope: A Scope object
- orig_input: The original input tensor.
- orig_output: The original output tensor.
- grad: Output backprop of shape
[batch, depth, rows, cols, channels].
- ksize: 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have
ksize[0] = ksize[4] = 1.
- strides: 1-D tensor of length 5. The stride of the sliding window for each dimension of
input. Must have strides[0] = strides[4] = 1.
- padding: The type of padding algorithm to use.
Optional attributes (see Attrs):
- data_format: 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].
Returns:
Output: Gradients of gradients w.r.t. the input to max_pool.
Constructors and Destructors
|
MaxPool3DGradGrad(const ::tensorflow::Scope & scope, ::tensorflow::Input orig_input, ::tensorflow::Input orig_output, ::tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding)
|
MaxPool3DGradGrad(const ::tensorflow::Scope & scope, ::tensorflow::Input orig_input, ::tensorflow::Input orig_output, ::tensorflow::Input grad, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding, const MaxPool3DGradGrad::Attrs & attrs)
|
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
Attrs DataFormat(
StringPiece x
)
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Last updated 2020-04-20 UTC.
[null,null,["Last updated 2020-04-20 UTC."],[],[],null,["# tensorflow::ops::MaxPool3DGradGrad Class Reference\n\ntensorflow::ops::MaxPool3DGradGrad\n==================================\n\n`#include \u003cnn_ops.h\u003e`\n\nComputes second-order gradients of the maxpooling function.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- orig_input: The original input tensor.\n- orig_output: The original output tensor.\n- grad: [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop of shape `[batch, depth, rows, cols, channels]`.\n- ksize: 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have `ksize[0] = ksize[4] = 1`.\n- strides: 1-D tensor of length 5. The stride of the sliding window for each dimension of `input`. Must have `strides[0] = strides[4] = 1`.\n- padding: The type of padding algorithm to use.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1_1_attrs)):\n\n- data_format: 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\\].\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Gradients of gradients w.r.t. the input to `max_pool`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [MaxPool3DGradGrad](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a321b0af89e0d474f1c47e1b56a901da5)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_input, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_output, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, const gtl::ArraySlice\u003c int \u003e & ksize, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding)` ||\n| [MaxPool3DGradGrad](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a1ab771fc14377bbd003cf6a0eb96c2ad)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_input, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` orig_output, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, const gtl::ArraySlice\u003c int \u003e & ksize, const gtl::ArraySlice\u003c int \u003e & strides, StringPiece padding, const `[MaxPool3DGradGrad::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|---------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a3df083c1b8bff3fe07b796c995dbc1f5) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1aa69fe26b83a309417a0103b09488eafa) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|---------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1ac2acbdab5dde8105877b14badb46ccc7)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1ae8e6a0a8acc839a71d2353beb944e2fa)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a574f83f847b22b01963e9649f6fe60f5)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|\n| [DataFormat](#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1a6edaa5d5fd12c37d7a45ad75ea3719ea)`(StringPiece x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs#structtensorflow_1_1ops_1_1_max_pool3_d_grad_grad_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::MaxPool3DGradGrad::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/max-pool3-d-grad-grad/attrs) | Optional attribute setters for [MaxPool3DGradGrad](/versions/r2.0/api_docs/cc/class/tensorflow/ops/max-pool3-d-grad-grad#classtensorflow_1_1ops_1_1_max_pool3_d_grad_grad). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### MaxPool3DGradGrad\n\n```gdscript\n MaxPool3DGradGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input,\n ::tensorflow::Input orig_output,\n ::tensorflow::Input grad,\n const gtl::ArraySlice\u003c int \u003e & ksize,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding\n)\n``` \n\n### MaxPool3DGradGrad\n\n```gdscript\n MaxPool3DGradGrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input orig_input,\n ::tensorflow::Input orig_output,\n ::tensorflow::Input grad,\n const gtl::ArraySlice\u003c int \u003e & ksize,\n const gtl::ArraySlice\u003c int \u003e & strides,\n StringPiece padding,\n const MaxPool3DGradGrad::Attrs & attrs\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n``` \n\nPublic static functions\n-----------------------\n\n### DataFormat\n\n```text\nAttrs DataFormat(\n StringPiece x\n)\n```"]]
