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src/convnets/convnext.jl

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@@ -33,13 +33,8 @@ Creates the layers for a ConvNeXt model.
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- `depths`: list with configuration for depth of each block
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- `planes`: list with configuration for number of output channels in each block
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- `stochastic_depth_prob`: Stochastic depth probability.
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- `layerscale_init`: Initial value for [`LayerScale`](@ref)
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- `drop_path_rate`: Stochastic depth rate.
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- `layerscale_init`: Initial value for [`Metalhead.LayerScale`](@ref)
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>>>>>>> 5ac81ce (Use `@autodocs` and fix references)
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([reference](https://arxiv.org/abs/2103.17239))
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- `inchannels`: number of input channels.
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- `nclasses`: number of output classes
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- `inchannels`: number of input channels
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- `nclasses`: number of output classes
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!!! warning
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`ConvNeXt` does not currently support pretrained weights.
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See also [`Metalhead.convnext`](@ref).
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"""
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struct ConvNeXt

src/convnets/resnets/core.jl

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- `revnorm`: set to `true` to place the normalisation layer before the convolution
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- `drop_block`: the drop block layer
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- `drop_path`: the drop path layer
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- `attn_fn`: the attention function to use. See [`squeeze_excite`](@ref) for an example.
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- `attn_fn`: the attention function to use. See [`Metalhead.squeeze_excite`](@ref) for an example.
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"""
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function bottleneck(inplanes::Integer, planes::Integer; stride::Integer,
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cardinality::Integer = 1, base_width::Integer = 64,
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resnet_stem(; stem_type = :default, inchannels::Integer = 3, replace_stem_pool = false,
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norm_layer = BatchNorm, activation = relu)
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Builds a stem to be used in a ResNet model. See the `stem` argument of [`resnet`](@ref) for details
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Builds a stem to be used in a ResNet model. See the `stem` argument of [`Metalhead.resnet`](@ref) for details
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on how to use this function.
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# Arguments

src/convnets/resnets/resnet.jl

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- `inchannels`: The number of input channels.
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- `nclasses`: The number of output classes
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Advanced users who want more configuration options will be better served by using [`resnet`](@ref).
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Advanced users who want more configuration options will be better served by using [`Metalhead.resnet`](@ref).
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"""
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struct WideResNet
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layers::Any

src/convnets/resnets/seresnet.jl

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@@ -58,11 +58,7 @@ Creates a SEResNeXt model with the specified depth, cardinality, and base width.
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`SEResNeXt` does not currently support pretrained weights.
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Advanced users who want more configuration options will be better served by using [`resnet`](@ref).
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Advanced users who want more configuration options will be better served by using [`Metalhead.resnet`](@ref).
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"""
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struct SEResNeXt
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layers::Any

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