tensorflow_similarity/architectures/efficientnet.py [128:143]:
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    if include_top:
        x = GeneralizedMeanPooling2D(p=gem_p, name="gem_pool")(x)
        if l2_norm:
            outputs = MetricEmbedding(embedding_size)(x)
        else:
            outputs = layers.Dense(embedding_size)(x)
    else:
        if pooling == "gem":
            x = GeneralizedMeanPooling2D(p=gem_p, name="gem_pool")(x)
        elif pooling == "avg":
            x = layers.GlobalAveragePooling2D(name="avg_pool")(x)
        elif pooling == "max":
            x = layers.GlobalMaxPooling2D(name="max_pool")(x)
        outputs = x

    return SimilarityModel(inputs, outputs)
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tensorflow_similarity/architectures/resnet50.py [88:103]:
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    if include_top:
        x = GeneralizedMeanPooling2D(p=gem_p, name="gem_pool")(x)
        if l2_norm:
            outputs = MetricEmbedding(embedding_size)(x)
        else:
            outputs = layers.Dense(embedding_size)(x)
    else:
        if pooling == "gem":
            x = GeneralizedMeanPooling2D(p=gem_p, name="gem_pool")(x)
        elif pooling == "avg":
            x = layers.GlobalAveragePooling2D(name="avg_pool")(x)
        elif pooling == "max":
            x = layers.GlobalMaxPooling2D(name="max_pool")(x)
        outputs = x

    return SimilarityModel(inputs, outputs)
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