{
    "module": "keras_hub.src.models.efficientnet.efficientnet_backbone",
    "class_name": "EfficientNetBackbone",
    "config": {
        "name": "efficient_net_backbone",
        "trainable": true,
        "width_coefficient": 1.0,
        "depth_coefficient": 1.1,
        "dropout": 0,
        "depth_divisor": 8,
        "min_depth": null,
        "activation": "swish",
        "input_shape": [
            null,
            null,
            3
        ],
        "stackwise_kernel_sizes": [
            3,
            3,
            5,
            3,
            5,
            5,
            3
        ],
        "stackwise_num_repeats": [
            1,
            2,
            2,
            3,
            3,
            4,
            1
        ],
        "stackwise_input_filters": [
            32,
            16,
            24,
            40,
            80,
            112,
            192
        ],
        "stackwise_output_filters": [
            16,
            24,
            40,
            80,
            112,
            192,
            320
        ],
        "stackwise_expansion_ratios": [
            1,
            6,
            6,
            6,
            6,
            6,
            6
        ],
        "stackwise_squeeze_and_excite_ratios": [
            0.25,
            0.25,
            0.25,
            0.25,
            0.25,
            0.25,
            0.25
        ],
        "stackwise_strides": [
            1,
            2,
            2,
            2,
            1,
            2,
            1
        ],
        "stackwise_block_types": [
            "v1",
            "v1",
            "v1",
            "v1",
            "v1",
            "v1",
            "v1"
        ],
        "include_stem_padding": true,
        "use_depth_divisor_as_min_depth": true,
        "cap_round_filter_decrease": true,
        "stem_conv_padding": "valid",
        "batch_norm_momentum": 0.9,
        "batch_norm_epsilon": 1e-05
    },
    "registered_name": "keras_hub>EfficientNetBackbone"
}