
Deep (stacked) RNN forward pass, bottom-up per time step (hmdrnn)
Source:R/geron_w4a_native.R
morie_geron_deep_rnn.RdDeep (stacked) RNN forward pass, bottom-up per time step (hmdrnn)
Usage
morie_geron_deep_rnn(
X,
hidden_sizes = 4,
n_layers = NULL,
weights = NULL,
seed = 0,
activation = "tanh"
)Examples
V <- c(1, 2, 3, 4, 5, 6, 7, 8)
morie_geron_deep_rnn(V)
#> $outputs
#> $outputs[[1]]
#> [1] -0.7231837 -0.6452206 0.8029629 0.5237606
#>
#> $outputs[[2]]
#> [1] -0.8729399 -0.8882050 0.8582650 0.7033403
#>
#> $outputs[[3]]
#> [1] -0.9736079 -0.9788004 0.9769558 0.8776618
#>
#> $outputs[[4]]
#> [1] -0.9947125 -0.9954971 0.9965273 0.9588968
#>
#> $outputs[[5]]
#> [1] -0.9990832 -0.9990659 0.9995916 0.9871970
#>
#> $outputs[[6]]
#> [1] -0.9998492 -0.9998019 0.9999546 0.9960179
#>
#> $outputs[[7]]
#> [1] -0.9999756 -0.9999575 0.9999950 0.9987580
#>
#> $outputs[[8]]
#> [1] -0.9999961 -0.9999909 0.9999995 0.9996121
#>
#>
#> $states
#> $states[[1]]
#> $states[[1]][[1]]
#> [1] -0.7231837 -0.6452206 0.8029629 0.5237606
#>
#> $states[[1]][[2]]
#> [1] -0.8729399 -0.8882050 0.8582650 0.7033403
#>
#> $states[[1]][[3]]
#> [1] -0.9736079 -0.9788004 0.9769558 0.8776618
#>
#> $states[[1]][[4]]
#> [1] -0.9947125 -0.9954971 0.9965273 0.9588968
#>
#> $states[[1]][[5]]
#> [1] -0.9990832 -0.9990659 0.9995916 0.9871970
#>
#> $states[[1]][[6]]
#> [1] -0.9998492 -0.9998019 0.9999546 0.9960179
#>
#> $states[[1]][[7]]
#> [1] -0.9999756 -0.9999575 0.9999950 0.9987580
#>
#> $states[[1]][[8]]
#> [1] -0.9999961 -0.9999909 0.9999995 0.9996121
#>
#>
#>
#> $final_states
#> $final_states[[1]]
#> [1] -0.9999961 -0.9999909 0.9999995 0.9996121
#>
#>
#> $layer_sizes
#> [1] 4
#>
#> $n_layers
#> [1] 1
#>
#> $n_params
#> [1] 24
#>
#> $state_norms
#> $state_norms[[1]]
#> [1] 1.363224 1.668004 1.905438 1.973073 1.992496 1.997815 1.999343 1.999799
#>
#>
#> $activation
#> [1] "tanh"
#>
#> $estimate
#> [1] -0.01219972
#>
#> $n
#> [1] 8
#>
#> $method
#> [1] "stacked RNN forward pass, bottom-up per time step"
#>