src/transformers/models/perceiver/modeling_perceiver.py/PerceiverForImageClassificationConvProcessing/__init__
class PerceiverForImageClassificationConvProcessing:    def __init__(self, config):
        super().__init__(config)

        fourier_position_encoding_kwargs_preprocessor = {
            "concat_pos": True,
            "max_resolution": (56, 56),
            "num_bands": 64,
            "sine_only": False,
        }
        trainable_position_encoding_kwargs_decoder = {"num_channels": config.d_latents, "index_dims": 1}

        self.num_labels = config.num_labels
        self.perceiver = PerceiverModel(
            config,
            input_preprocessor=PerceiverImagePreprocessor(
                config,
                prep_type="conv",
                spatial_downsample=1,
                position_encoding_type="fourier",
                fourier_position_encoding_kwargs=fourier_position_encoding_kwargs_preprocessor,
            ),
            decoder=PerceiverClassificationDecoder(
                config,
                num_channels=config.d_latents,
                trainable_position_encoding_kwargs=trainable_position_encoding_kwargs_decoder,
                use_query_residual=True,
            ),
        )

        # Initialize weights and apply final processing
        self.post_init()