ludwig/features/category_feature.py [294:342]:
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        if output_feature[LOSS]['class_similarities_temperature'] > 0:
            if 'class_similarities' in output_feature[LOSS]:
                similarities = output_feature[LOSS]['class_similarities']
                temperature = output_feature[LOSS][
                    'class_similarities_temperature']

                curr_row = 0
                first_row_length = 0
                is_first_row = True
                for row in similarities:
                    if is_first_row:
                        first_row_length = len(row)
                        is_first_row = False
                        curr_row += 1
                    else:
                        curr_row_length = len(row)
                        if curr_row_length != first_row_length:
                            raise ValueError(
                                'The length of row {} of the class_similarities '
                                'of {} is {}, different from the length of '
                                'the first row {}. All rows must have '
                                'the same length.'.format(
                                    curr_row,
                                    output_feature['name'],
                                    curr_row_length,
                                    first_row_length
                                )
                            )
                        else:
                            curr_row += 1
                all_rows_length = first_row_length

                if all_rows_length != len(similarities):
                    raise ValueError(
                        'The class_similarities matrix of {} has '
                        '{} rows and {} columns, '
                        'their number must be identical.'.format(
                            output_feature['name'],
                            len(similarities),
                            all_rows_length
                        )
                    )

                if all_rows_length != output_feature['num_classes']:
                    raise ValueError(
                        'The size of the class_similarities matrix of {} is '
                        '{}, different from the number of classe ({}). '
                        'Check the metadata JSON file to see the classes '
                        'and their order and '
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ludwig/features/sequence_feature.py [291:339]:
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        if output_feature[LOSS]['class_similarities_temperature'] > 0:
            if 'class_similarities' in output_feature[LOSS]:
                similarities = output_feature[LOSS]['class_similarities']
                temperature = output_feature[LOSS][
                    'class_similarities_temperature']

                curr_row = 0
                first_row_length = 0
                is_first_row = True
                for row in similarities:
                    if is_first_row:
                        first_row_length = len(row)
                        is_first_row = False
                        curr_row += 1
                    else:
                        curr_row_length = len(row)
                        if curr_row_length != first_row_length:
                            raise ValueError(
                                'The length of row {} of the class_similarities '
                                'of {} is {}, different from the length of '
                                'the first row {}. All rows must have '
                                'the same length.'.format(
                                    curr_row,
                                    output_feature['name'],
                                    curr_row_length,
                                    first_row_length
                                )
                            )
                        else:
                            curr_row += 1
                all_rows_length = first_row_length

                if all_rows_length != len(similarities):
                    raise ValueError(
                        'The class_similarities matrix of {} has '
                        '{} rows and {} columns, '
                        'their number must be identical.'.format(
                            output_feature['name'],
                            len(similarities),
                            all_rows_length
                        )
                    )

                if all_rows_length != output_feature['num_classes']:
                    raise ValueError(
                        'The size of the class_similarities matrix of {} is '
                        '{}, different from the number of classe ({}). '
                        'Check the metadata JSON file to see the classes '
                        'and their order and '
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