Adding PairNorm support #418
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Signed-off-by: achiverram28 <ramsamarth21bcs24@iiitkottayam.ac.in>
| # Implementation of normalization layers for GraphNeuralNetworks | ||
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| @doc raw""" | ||
| PairNorm(scale_value; [scale_individually]) |
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| PairNorm(scale_value; [scale_individually]) | |
| PairNorm(scale_value; scale_individually=false) |
| @doc raw""" | ||
| PairNorm(scale_value; [scale_individually]) | ||
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| PairNorm layer from paper [PairNorm: Tackling Oversmoothing in GNNs](https://arxiv.org/abs/1909.12223) |
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| PairNorm layer from paper [PairNorm: Tackling Oversmoothing in GNNs](https://arxiv.org/abs/1909.12223) | |
| PairNorm layer from paper [PairNorm: Tackling Oversmoothing in GNNs](https://arxiv.org/abs/1909.12223). |
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| PairNorm layer from paper [PairNorm: Tackling Oversmoothing in GNNs](https://arxiv.org/abs/1909.12223) | ||
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| Performs the operation(normalization) |
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| Performs the operation(normalization) | |
| Performs the operation |
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| \mathbf{x}_i^c &= \mathbf{x}_i - \frac{1}{n} | ||
| \sum_{i=1}^n \mathbf{x}_i \\ | ||
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| \mathbf{x}_i^{\prime} &= s \cdot | ||
| \frac{\mathbf{x}_i^c}{\sqrt{\frac{1}{n} \sum_{i=1}^n | ||
| {\| \mathbf{x}_i^c \|}^2_2}} |
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| \mathbf{x}_i^c &= \mathbf{x}_i - \frac{1}{n} | |
| \sum_{i=1}^n \mathbf{x}_i \\ | |
| \mathbf{x}_i^{\prime} &= s \cdot | |
| \frac{\mathbf{x}_i^c}{\sqrt{\frac{1}{n} \sum_{i=1}^n | |
| {\| \mathbf{x}_i^c \|}^2_2}} | |
| \mathbf{x}_i^c &= \mathbf{x}_i - \frac{1}{n} | |
| \sum_{i=1}^n \mathbf{x}_i \\ | |
| \mathbf{x}_i^{\prime} &= s \cdot | |
| \frac{\mathbf{x}_i^c}{\sqrt{\frac{1}{n} \sum_{i=1}^n | |
| {\| \mathbf{x}_i^c \|}^2_2}} |
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| The input to this layer is the output from GNN layers | ||
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| The input to this layer is the output from GNN layers |
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| # Arguments | ||
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| - `scale_value`: Scaling factor `s` used in normalisation. Default `1.0` |
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| - `scale_value`: Scaling factor `s` used in normalisation. Default `1.0` | |
| - `scale_value`: Scaling factor `s` used in normalisation. Default `1.0`. |
| ``` | ||
| Default `false` | ||
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| - `ϵ` : Small value added in the denominator for numerical stability. Default `1f-5` |
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| - `ϵ` : Small value added in the denominator for numerical stability. Default `1f-5` | |
| - `ϵ` : Small value added in the denominator for numerical stability. Default `1f-5`. |
This should be mentioned in the first line fo the docstring.
| @functor PairNorm | ||
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| function PairNorm(scale_value::Real=1.0f0; scale_individually::Bool=false, eps::Real=1f-5, ϵ=nothing) | ||
| ε = _greek_ascii_depwarn(ϵ => eps, :BatchNorm, "ϵ" => "eps") |
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| ε = _greek_ascii_depwarn(ϵ => eps, :BatchNorm, "ϵ" => "eps") |
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| @functor PairNorm | ||
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| function PairNorm(scale_value::Real=1.0f0; scale_individually::Bool=false, eps::Real=1f-5, ϵ=nothing) |
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| function PairNorm(scale_value::Real=1.0f0; scale_individually::Bool=false, eps::Real=1f-5, ϵ=nothing) | |
| function PairNorm(scale_value::Real=1.0f0; scale_individually::Bool=false, eps::Real=1f-5) |
| return PairNorm(scale_value, ε, scale_individually) | ||
| end | ||
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| function (PN::PairNorm)(x::AbstractArray) |
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| function (PN::PairNorm)(x::AbstractArray) | |
| function (pn::PairNorm)(x::AbstractArray) | |
| eps = ofeltype(x, pn.ϵ) | |
| s = ofeltype(pn.scale_value) |
| end | ||
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| function (PN::PairNorm)(x::AbstractArray) | ||
| xm = mean(x, dims=1) |
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all dimensions are wrong here and belowe. The node dimension is the secnd dimension, the feature dimension is the first
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| xm = mean(x, dims=1) | |
| xm = mean(x, dims=2) |
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Addressing #405
Adding a new
normalise.jl