@@ -286,9 +286,9 @@ Create an Inceptionv4 model.
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# Arguments
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- - inchannels: number of input channels.
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- - dropout: rate of dropout in classifier head.
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- - nclasses: the number of output classes.
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+ - ` inchannels` : number of input channels.
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+ - ` dropout` : rate of dropout in classifier head.
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+ - ` nclasses` : the number of output classes.
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"""
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function inceptionv4 (; inchannels = 3 , dropout = 0.0 , nclasses = 1000 )
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body = Chain (conv_bn ((3 , 3 ), inchannels, 32 ; stride = 2 )... ,
@@ -326,9 +326,9 @@ Creates an Inceptionv4 model.
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# Arguments
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- `pretrain`: set to `true` to load the pre-trained weights for ImageNet
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- - inchannels: number of input channels.
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- - dropout: rate of dropout in classifier head.
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- - nclasses: the number of output classes.
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+ - ` inchannels` : number of input channels.
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+ - ` dropout` : rate of dropout in classifier head.
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+ - ` nclasses` : the number of output classes.
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!!! warning
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@@ -426,9 +426,9 @@ Creates an InceptionResNetv2 model.
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# Arguments
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- - inchannels: number of input channels.
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- - dropout: rate of dropout in classifier head.
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- - nclasses: the number of output classes.
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+ - ` inchannels` : number of input channels.
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+ - ` dropout` : rate of dropout in classifier head.
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+ - ` nclasses` : the number of output classes.
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"""
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function inceptionresnetv2 (; inchannels = 3 , dropout = 0.0 , nclasses = 1000 )
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body = Chain (conv_bn ((3 , 3 ), inchannels, 32 ; stride = 2 )... ,
@@ -459,9 +459,9 @@ Creates an InceptionResNetv2 model.
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# Arguments
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- `pretrain`: set to `true` to load the pre-trained weights for ImageNet
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- - inchannels: number of input channels.
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- - dropout: rate of dropout in classifier head.
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- - nclasses: the number of output classes.
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+ - ` inchannels` : number of input channels.
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+ - ` dropout` : rate of dropout in classifier head.
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+ - ` nclasses` : the number of output classes.
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!!! warning
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@@ -496,12 +496,12 @@ Create an Xception block.
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# Arguments
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- - inchannels: number of input channels.
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- - outchannels: number of output channels.
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- - nrepeats: number of repeats of depthwise separable convolution layers.
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- - stride: stride by which to downsample the input.
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- - start_with_relu: if true, start the block with a ReLU activation.
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- - grow_first: if true, increase the number of channels at the first convolution.
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+ - ` inchannels` : number of input channels.
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+ - ` outchannels` : number of output channels.
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+ - ` nrepeats` : number of repeats of depthwise separable convolution layers.
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+ - ` stride` : stride by which to downsample the input.
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+ - ` start_with_relu` : if true, start the block with a ReLU activation.
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+ - ` grow_first` : if true, increase the number of channels at the first convolution.
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"""
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function xception_block (inchannels, outchannels, nrepeats; stride = 1 ,
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start_with_relu = true ,
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