product_matching/euclidean_intersection.py [89:102]:
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        return Lambda(func)

    def intersection_layer(self,x):
        all_pairs = []
        for ind1 in tqdm(range(x[0].shape[1])):
            for ind2 in range(ind1, x[1].shape[1]):
                box1_center = self.crop_box(ind1,0,self._params["box_dim"]//2)(x[0])
                box1_offset = self.crop_box(ind1,self._params["box_dim"]//2,None)(x[0])
                box2_center = self.crop_box(ind2,0,self._params["box_dim"]//2)(x[1])
                box2_offset = self.crop_box(ind2,self._params["box_dim"]//2,None)(x[1])
                concat_center = Concatenate()([box1_center,box2_center])
                reshape_concat_center = Reshape((2,self._params["box_dim"]//2))(concat_center)
                center = SelfAttention(return_sequences=True)(reshape_concat_center)
                center = Dense(self._params["box_dim"]//2)(center)
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product_matching/hyperboloid.py [134:148]:
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        return Lambda(func)

    def intersection_layer(self,x):
	# Intersection Layer with Attention on centers and Minimum on offsets
        all_pairs = []
        for ind1 in tqdm(range(x[0].shape[1])):
            for ind2 in range(ind1, x[1].shape[1]):
                box1_center = self.crop_box(ind1,0,self._params["box_dim"]//2)(x[0])
                box1_offset = self.crop_box(ind1,self._params["box_dim"]//2,None)(x[0])
                box2_center = self.crop_box(ind2,0,self._params["box_dim"]//2)(x[1])
                box2_offset = self.crop_box(ind2,self._params["box_dim"]//2,None)(x[1])
                concat_center = Concatenate()([box1_center,box2_center])
                reshape_concat_center = Reshape((2,self._params["box_dim"]//2))(concat_center)
                center = SelfAttention(return_sequences=True)(reshape_concat_center)
                center = Dense(self._params["box_dim"]//2)(center)
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