# 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
from towhee.operator import Operator


class ImageEmbeddingOperatorTemplate(Operator):
    """
    An operator class that implements image embedding.
    
    Args:
        model_name (`str`):
            Embedding the image withe the specific model.
    """
    def __init__(self, model_name: str, framework: str = 'pytorch') -> None:
        """
        Initialize some parameters and load the model.
        """
        super().__init__()
        # please define Model class and declare model object, and initialize with the model_name
        # if framework == 'pytorch':
        #     from pytorch import Model
        self.model = Model(model_name)

    def __call__(self, img_tensor: torch.Tensor) -> NamedTuple('Outputs', [('feature_vector', numpy.ndarray)]):
        """
        Call it when use this class.
        
        Args:
            img_tensor (`torch.Tensor`):
                The image tensor, you can generate it with TransformImageOperatorClass.
        Returns:
            (`numpy.ndarray`)
                The image embedding.
        """
        # call model with the img_tensor parameter
        result = self.model(img_tensor)
        Outputs = NamedTuple('Outputs', [('feature_vector', numpy.ndarray)])
        return Outputs(result)