# Copyright 2021 Zilliz. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


from typing import NamedTuple

import numpy
import torch
from efficientnet_pytorch import EfficientNet


class Model():
    """
    PyTorch model class
    """
    def __init__(self, model_name: str, weights_path: str):
        super().__init__()
        self._model = EfficientNet.from_pretrained(model_name=model_name, weights_path=weights_path)
        self._avg_pooling = torch.nn.AdaptiveAvgPool2d((1, 1))
        self._model.eval()

    def __call__(self, img_tensor: torch.Tensor):
        features = self._model.extract_features(img_tensor)
        return self._avg_pooling(features).flatten().detach().numpy()

    def train(self):
        """
        For training model
        """
        pass