---
_import: ../vgg16_compact.yaml
_gate:
    enable: true
    policy: parametric
    density: 0.6
    pool: avg
    regularizer:
        # l1: 0.00000001
        moe: 0.0
    threshold: online
_trainable: true
model:
    name: vgg16_bn
    layers:
        _gated_conv: &gated_conv
            type: gated_convolution
            gate_params: $(_gate)
        conv1_1: {<<: *gated_conv, trainable: $(_trainable)}
        conv1_2: {<<: *gated_conv, trainable: $(_trainable)}
        conv2_1: {<<: *gated_conv, trainable: $(_trainable)}
        conv2_2: {<<: *gated_conv, trainable: $(_trainable)}
        conv3_1: {<<: *gated_conv, trainable: $(_trainable)}
        conv3_2: {<<: *gated_conv, trainable: $(_trainable)}
        conv3_3: {<<: *gated_conv, trainable: $(_trainable)}
        conv4_1: {<<: *gated_conv, trainable: $(_trainable)}
        conv4_2: {<<: *gated_conv, trainable: $(_trainable)}
        conv4_3: {<<: *gated_conv, trainable: $(_trainable)}
        conv5_1: {<<: *gated_conv, trainable: $(_trainable)}
        conv5_2: {<<: *gated_conv, trainable: $(_trainable)}
        conv5_3: {<<: *gated_conv, trainable: $(_trainable)}
        fc6: {trainable: $(_trainable)}
        fc7: {trainable: $(_trainable)}
        fc8: {trainable: $(_trainable)}
