“AssertionError: 发现没有需要填充的字段；我们很惊讶你收到这个错误，请在 github 上打开一个问题”错误发生

问题描述

我遇到错误（“AssertionError：找不到需要填充的字段；我们很惊讶您收到此错误，请在 github 上打开一个问题”）。

"AssertionError: Found no field that needed padding; we are surprised you got this error,please open an issue on github"

我不知道为什么会出现这个错误。

我的配置文件在下面。

"""
{
    "dataset_reader": {
        "type": "tbmse_drop","answer_field_generators": {
            "arithmetic_answer": {
                "type": "arithmetic_answer_generator","special_numbers": [
                    100,1
                ]
            },"count_answer": {
                "type": "count_answer_generator"
            },"passage_span_answer": {
                "type": "span_answer_generator","text_type": "passage"
            },"question_span_answer": {
                "type": "span_answer_generator","text_type": "question"
            },"tagged_answer": {
                "type": "tagged_answer_generator","ignore_question": false,"labels": {
                    "I": 1,"O": 0
                }
            }
        },"answer_generator_names_per_type": {
            "date": [
                "arithmetic_answer","passage_span_answer","question_span_answer","tagged_answer"
            ],"multiple_span": [
                "tagged_answer"
            ],"number": [
                "arithmetic_answer","count_answer","single_span": [
                "tagged_answer","question_span_answer"
            ]
        },"is_training": true,"old_reader_behavior": true,"pickle": {
            "action": "load","file_name": "all_heads_IO_roberta-large","path": "../pickle/drop"
        },"tokenizer": {
            "type": "huggingface_transformers","pretrained_model": "roberta-large"
        }
    },"model": {
        "type": "multi_head","dataset_name": "drop","head_predictor": {
            "activations": [
                "relu","linear"
            ],"dropout": [
                0.1,0
            ],"hidden_dims": [
                1024,5
            ],"input_dim": 2048,"num_layers": 2
        },"heads": {
            "arithmetic": {
                "type": "arithmetic_head","output_layer": {
                    "activations": [
                        "relu","linear"
                    ],"dropout": [
                        0.1,0
                    ],"hidden_dims": [
                        1024,3
                    ],"num_layers": 2
                },"special_embedding_dim": 1024,1
                ],"training_style": "soft_em"
            },"count": {
                "type": "count_head","max_count": 10,11
                    ],"input_dim": 1024,"num_layers": 2
                }
            },"multi_span": {
                "type": "multi_span_head","decoding_style": "at_least_one","O": 0
                },2
                    ],"prediction_method": "viterbi","passage_span": {
                "type": "passage_span_head","end_output_layer": {
                    "activations": "linear","hidden_dims": 1,"num_layers": 1
                },"start_output_layer": {
                    "activations": "linear","question_span": {
                "type": "question_span_head","end_output_layer": {
                    "activations": [
                        "relu",1
                    ],"training_style": "soft_em"
            }
        },"passage_summary_vector_module": {
            "activations": "linear","num_layers": 1
        },"pretrained_model": "roberta-large","question_summary_vector_module": {
            "activations": "linear","num_layers": 1
        }
    },"train_data_path": "drop_data/drop_dataset_train.json","validation_data_path": "drop_data/drop_dataset_dev.json","trainer": {
        "num_epochs": 15,"optimizer": {
            "type": "adam","lr": 5e-06
        },"patience": 10,"validation_metric": "+f1"
    },"data_loader": {
        "batch_sampler": {
            "type": "bucket","batch_size": 1
        }
    },"distributed": {
        "cuda_devices": [
            0,1
        ]
    },"validation_dataset_reader": {
        "type": "tbmse_drop","is_training": false,"pretrained_model": "roberta-large"
        }
    }
}
"""

我使用了 allennlp 2.0.1 & 2.0.2（两个版本都出现了同样的错误。）

解决方法

您的数据集读取器是否可能根本不生成任何实例？或者，它产生的实例中是否可能没有字段（即完全为空）？在这两种情况下，都会发生此错误。

如果这些都没有发生，请尝试将 sorting_keys 的 batch_sampler 设置为实例中最长的字段。