LeNet-5 architecture resolution (Geron Ch 12, morie.fn hmlnet)

Usage

morie_geron_lenet5(n_classes = 10, input_size = 32, in_channels = 1)

Arguments

n_classes: Outputs.
input_size: Square input size.
in_channels: Input channels.

Value

List with layers, total_parameters, output_shape, receptive_field, estimate, n, method.

Examples

morie_geron_lenet5()
#> $layers
#> $layers[[1]]
#> $layers[[1]]$name
#> [1] "C1"
#> 
#> $layers[[1]]$type
#> [1] "conv"
#> 
#> $layers[[1]]$output_shape
#> [1] 28 28  6
#> 
#> $layers[[1]]$parameters
#> [1] 156
#> 
#> 
#> $layers[[2]]
#> $layers[[2]]$name
#> [1] "S2"
#> 
#> $layers[[2]]$type
#> [1] "pool"
#> 
#> $layers[[2]]$output_shape
#> [1] 14 14  6
#> 
#> $layers[[2]]$parameters
#> [1] 0
#> 
#> 
#> $layers[[3]]
#> $layers[[3]]$name
#> [1] "C3"
#> 
#> $layers[[3]]$type
#> [1] "conv"
#> 
#> $layers[[3]]$output_shape
#> [1] 10 10 16
#> 
#> $layers[[3]]$parameters
#> [1] 2416
#> 
#> 
#> $layers[[4]]
#> $layers[[4]]$name
#> [1] "S4"
#> 
#> $layers[[4]]$type
#> [1] "pool"
#> 
#> $layers[[4]]$output_shape
#> [1]  5  5 16
#> 
#> $layers[[4]]$parameters
#> [1] 0
#> 
#> 
#> $layers[[5]]
#> $layers[[5]]$name
#> [1] "C5"
#> 
#> $layers[[5]]$type
#> [1] "conv"
#> 
#> $layers[[5]]$output_shape
#> [1]   1   1 120
#> 
#> $layers[[5]]$parameters
#> [1] 48120
#> 
#> 
#> $layers[[6]]
#> $layers[[6]]$name
#> [1] "F6"
#> 
#> $layers[[6]]$type
#> [1] "dense"
#> 
#> $layers[[6]]$output_shape
#> [1] 84
#> 
#> $layers[[6]]$parameters
#> [1] 10164
#> 
#> 
#> $layers[[7]]
#> $layers[[7]]$name
#> [1] "output"
#> 
#> $layers[[7]]$type
#> [1] "dense"
#> 
#> $layers[[7]]$output_shape
#> [1] 10
#> 
#> $layers[[7]]$parameters
#> [1] 850
#> 
#> 
#> 
#> $total_parameters
#> [1] 61706
#> 
#> $output_shape
#> [1] 10
#> 
#> $receptive_field
#> [1] 32
#> 
#> $convention
#> [1] "parameter-free pooling, fully-connected C3"
#> 
#> $estimate
#> [1] 61706
#> 
#> $n
#> [1] 7
#> 
#> $method
#> [1] "LeNet-5 architecture resolution"
#>