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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _load(self):
 """ Loads a model into weights """

        if self._model_filename is None:
            raise ValueError('Model filename not specified')

        # read the input image
        self._graph = tf.Graph()
        with self._graph.as_default():
            # read in filenames
            reader = tf.train.NewCheckpointReader(self._model_filename)

            # load AlexNet weights
            weights = AlexNetWeights()
            weights.conv1W = tf.Variable(reader.get_tensor("Variable")) 
            weights.conv1b = tf.Variable(reader.get_tensor("Variable_1"))
            weights.conv2W = tf.Variable(reader.get_tensor("Variable_2"))
            weights.conv2b = tf.Variable(reader.get_tensor("Variable_3"))
            weights.conv3W = tf.Variable(reader.get_tensor("Variable_4"))
            weights.conv3b = tf.Variable(reader.get_tensor("Variable_5"))
            weights.conv4W = tf.Variable(reader.get_tensor("Variable_6"))
            weights.conv4b = tf.Variable(reader.get_tensor("Variable_7"))
            weights.conv5W = tf.Variable(reader.get_tensor("Variable_8"))
            weights.conv5b = tf.Variable(reader.get_tensor("Variable_9"))
            weights.fc6W = tf.Variable(reader.get_tensor("Variable_10"))
            weights.fc6b = tf.Variable(reader.get_tensor("Variable_11"))
            weights.fc7W = tf.Variable(reader.get_tensor("Variable_12"))
            weights.fc7b = tf.Variable(reader.get_tensor("Variable_13"))
            weights.fc8W = tf.Variable(reader.get_tensor("Variable_14"))
            weights.fc8b = tf.Variable(reader.get_tensor("Variable_15"))

            # form network
            self._input_node = tf.placeholder(tf.float32, (self._batch_size, self._im_height, self._im_width, self._num_channels))
            self._output_tensor = self.build_alexnet(weights)
            self._feature_tensor = self.build_alexnet(weights, output_layer=self._feature_layer)
            self._initialized = True