How to use efficientNet as backbone CNN model for feature extraction, so that embeddings of images can be generated.Most of example on GitHub use 4 layer ConvNet so I can not understand how to use same thing for large CNN model. Like there are implementation of efficient-net for Torch, so what steps I need to use them as feature extractor?
I am using this efficient net code which implemented network in PyTorch -
  

      github.com
  

  
    lukemelas/EfficientNet-PyTorch/blob/master/efficientnet_pytorch/model.py 13


    """model.py - Model and module class for EfficientNet.
   They are built to mirror those in the official TensorFlow implementation.
"""

# Author: lukemelas (github username)
# Github repo: https://github.com/lukemelas/EfficientNet-PyTorch
# With adjustments and added comments by workingcoder (github username).

import torch
from torch import nn
from torch.nn import functional as F
from .utils import (
    round_filters,
    round_repeats,
    drop_connect,
    get_same_padding_conv2d,
    get_model_params,
    efficientnet_params,
    load_pretrained_weights,
    Swish,



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