def format_row(self, pa_table: pa.Table) -> Mapping:
        row = self.numpy_arrow_extractor().extract_row(pa_table)
        row = self.python_features_decoder.decode_row(row)
        return self.recursive_tensorize(row)

    def format_column(self, pa_table: pa.Table) -> "torch.Tensor":
        column = self.numpy_arrow_extractor().extract_column(pa_table)
        column = self.python_features_decoder.decode_column(column, pa_table.column_names[0])
        column = self.recursive_tensorize(column)
        column = self._consolidate(column)
        return column

    def format_batch(self, pa_table: pa.Table) -> Mapping:
        batch = self.numpy_arrow_extractor().extract_batch(pa_table)
        batch = self.python_features_decoder.decode_batch(batch)
        batch = self.recursive_tensorize(batch)
        for column_name in batch:
            batch[column_name] = self._consolidate(batch[column_name])
        return batch