Briefly, this error occurs when the input data provided for text classification in Elasticsearch is not in the expected format. This could be due to incorrect data types, missing fields, or improper structure. To resolve this issue, you can: 1) Verify the structure and format of your input data, ensuring it matches the expected format. 2) Check if all required fields are present in the input data. 3) Ensure that the data types of the fields in your input data are correct. 4) If you’re using a batch processing method, ensure the batch size is appropriate.
This guide will help you check for common problems that cause the log ” Unexpected batch input for text classification ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “Unexpected batch input for text classification” class name is TextClassificationProcessor.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
} } Map> windowedSeq = tokenization.getTokensBySequenceId(); // TODO adjust logic when batch is allowed if (windowedSeq.size() > 1) { throw new ElasticsearchStatusException("Unexpected batch input for text classification"; RestStatus.INTERNAL_SERVER_ERROR); } double[] normalizedScores = new double[labels.size()]; for (int i = 0; i < pyTorchResult.getInferenceResult()[0].length; i++) { double[] scores = NlpHelpers.convertToProbabilitiesBySoftMax(pyTorchResult.getInferenceResult()[0][i]); InferenceHelpers.sumDoubleArrays(normalizedScores; scores);