This function list all layer names of a keras model.
Examples
keras_model <- try(get_keras_model("vss_phn_32"))
if (!inherits(keras_model, "try-error")) {
keras_wrapper(keras_model)$list_layer_name()
}
#> [1] "input_1" "tf.__operators__.getitem"
#> [3] "tf.nn.bias_add" "grey_scale"
#> [5] "block1_conv1" "batch_normalization"
#> [7] "activation" "block1_conv2"
#> [9] "batch_normalization_1" "activation_1"
#> [11] "block1_pool" "dropout"
#> [13] "block2_conv1" "batch_normalization_2"
#> [15] "activation_2" "block2_conv2"
#> [17] "batch_normalization_3" "activation_3"
#> [19] "block2_pool" "dropout_1"
#> [21] "block3_conv1" "batch_normalization_4"
#> [23] "activation_4" "block3_conv2"
#> [25] "batch_normalization_5" "activation_5"
#> [27] "block3_conv3" "batch_normalization_6"
#> [29] "activation_6" "block3_pool"
#> [31] "dropout_2" "block4_conv1"
#> [33] "batch_normalization_7" "activation_7"
#> [35] "block4_conv2" "batch_normalization_8"
#> [37] "activation_8" "block4_conv3"
#> [39] "batch_normalization_9" "activation_9"
#> [41] "block4_pool" "dropout_3"
#> [43] "block5_conv1" "batch_normalization_10"
#> [45] "activation_10" "block5_conv2"
#> [47] "batch_normalization_11" "activation_11"
#> [49] "block5_conv3" "batch_normalization_12"
#> [51] "activation_12" "block5_pool"
#> [53] "dropout_4" "global_max_pooling2d"
#> [55] "additional_input" "concatenate"
#> [57] "dense" "dropout_5"
#> [59] "activation_13" "dense_1"