container/neo_template_mxnet_byom.py [116:136]:
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        self.initialized = True

    def preprocess(self, batch_data):
        assert self._batch_size == len(batch_data), \
            'Invalid input batch size: expected {} but got {}'.format(self._batch_size,
                                                                      len(batch_data))
        processed_batch_data = []

        for k in range(len(batch_data)):
            req_body = batch_data[k]
            content_type = self._context.get_request_header(k, 'Content-type')
            if content_type is None:
                content_type = self._context.get_request_header(k, 'Content-Type')
                if content_type is None:
                    raise Exception('Content type could not be deduced')

            payload = batch_data[k].get('data')
            if payload is None:
                payload = batch_data[k].get('body')
            if payload is None:
                raise Exception('Nonexistent payload')
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container/neo_template_xgboost.py [32:52]:
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        self.initialized = True

    def preprocess(self, batch_data):
        assert self._batch_size == len(batch_data), \
            'Invalid input batch size: expected {} but got {}'.format(self._batch_size,
                                                                      len(batch_data))
        processed_batch_data = []

        for k in range(len(batch_data)):
            req_body = batch_data[k]
            content_type = self._context.get_request_header(k, 'Content-type')
            if content_type is None:
                content_type = self._context.get_request_header(k, 'Content-Type')
                if content_type is None:
                    raise Exception('Content type could not be deduced')

            payload = batch_data[k].get('data')
            if payload is None:
                payload = batch_data[k].get('body')
            if payload is None:
                raise Exception('Nonexistent payload')
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