def preprocess()

in container/neo_template_image_classification.py [0:0]

• 28 lines of code
• 8 McCabe index (conditional complexity)

    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')

            if content_type in SUPPORTED_CONTENT_TYPE:
                try:
                    dtest = _load_image(payload, self.shape_info)
                    processed_batch_data.append(dtest)
                except Exception as e:
                    raise Exception('ClientError: Loading image data failed with exception:\n' +
                                    str(e))
            else:
                raise Exception('ClientError: Invalid content type. ' +
                                'Accepted content types are {}'.format(SUPPORTED_CONTENT_TYPE))

        return processed_batch_data