Instance Normalization as described in the paper.
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#include </home/runner/work/iganet/iganet/include/layer.hpp>
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torch::nn::functional::InstanceNormFuncOptions | options_ |
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virtual const std::string & | name () const noexcept |
| Returns the full qualified name of the object.
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at::optional< std::string > | name_ |
| String storing the full qualified name of the object.
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Instance Normalization as described in the paper.
Instance Normalization: The Missing Ingredient for Fast Stylization, https://arxiv.org/abs/1607.08022
◆ InstanceNorm() [1/2]
iganet::InstanceNorm::InstanceNorm |
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torch::nn::functional::InstanceNormFuncOptions |
options = {} | ) |
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inlineexplicit |
◆ InstanceNorm() [2/2]
iganet::InstanceNorm::InstanceNorm |
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const torch::Tensor & |
running_mean, |
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const torch::Tensor & |
running_var, |
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const torch::Tensor & |
weight, |
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const torch::Tensor & |
bias, |
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double |
eps, |
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double |
momentum, |
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bool |
use_input_stats = true |
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inlineexplicit |
◆ ~InstanceNorm()
iganet::InstanceNorm::~InstanceNorm |
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overridedefault |
◆ apply()
torch::Tensor iganet::InstanceNorm::apply |
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const torch::Tensor & |
input | ) |
const |
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inlineoverridevirtual |
◆ options() [1/2]
torch::nn::functional::InstanceNormFuncOptions & iganet::InstanceNorm::options |
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inline |
Returns non-constant reference to options.
◆ options() [2/2]
const torch::nn::functional::InstanceNormFuncOptions & iganet::InstanceNorm::options |
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const |
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inline |
Returns constant reference to options.
◆ pretty_print()
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inlineoverridevirtualnoexcept |
◆ read()
torch::serialize::InputArchive & iganet::InstanceNorm::read |
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torch::serialize::InputArchive & |
archive, |
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const std::string & |
key = "instance_norm" |
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) |
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inlineoverridevirtual |
◆ write()
torch::serialize::OutputArchive & iganet::InstanceNorm::write |
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torch::serialize::OutputArchive & |
archive, |
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const std::string & |
key = "instance_norm" |
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) |
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inlineoverridevirtual |
◆ options_
torch::nn::functional::InstanceNormFuncOptions iganet::InstanceNorm::options_ |
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private |
The documentation for this class was generated from the following file: