Error in exporting custom trained RE model

[Tanmay98]

I am able to produce evaluations using the best_model model files for my custom trained RE model but when I try to export it I get the following error. I have also attached the config .yml file for my RE model.

Traceback (most recent call last): File "tools/export_model.py", line 256, in main() File "tools/export_model.py", line 252, in main model, arch_config, save_path, logger, input_shape=input_shape) File "tools/export_model.py", line 172, in export_single_model paddle.jit.save(model, save_path) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/jit.py", line 631, in wrapper func(layer, path, input_spec, configs) File "", line 2, in save File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/wrapped_decorator.py", line 25, in impl return wrapped_func(*args, *kwargs) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/base.py", line 51, in impl return func(args, kwargs) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/jit.py", line 861, in save inner_input_spec, with_hook=with_hook) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/program_translator.py", line 528, in concrete_program_specify_input_spec *desired_input_spec, with_hook=with_hook) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/program_translator.py", line 436, in get_concrete_program concrete_program, partial_program_layer = self._program_cache[cache_key] File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/program_translator.py", line 801, in getitem self._caches[item_id] = self._build_once(item) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/program_translator.py", line 790, in _build_once cache_key.kwargs) File "", line 2, in from_func_spec File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/wrapped_decorator.py", line 25, in impl return wrapped_func(*args, *kwargs) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/base.py", line 51, in impl return func(args, kwargs) File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/program_translator.py", line 740, in from_func_spec error_data.raise_new_exception() File "/usr/local/lib/python3.7/dist-packages/paddle/fluid/dygraph/dygraph_to_static/error.py", line 336, in raise_newexception six.exec("raise new_exception from None") File "", line 1, in IndexError: In transformed code:

File "/content/drive/MyDrive/PaddleOCR/ppocr/modeling/architectures/base_model.py", line 86, in forward
x = self.backbone(x)
File "/content/drive/MyDrive/PaddleOCR/ppocr/modeling/backbones/vqa_layoutlm.py", line 234, in forward
        head_mask=None,
        labels=None,
        entities=x[5],
        ~~~~~~~~~~~~~~ <--- HERE
        relations=x[6])
    return x

IndexError: list index out of range

Global: use_gpu: True epoch_num: &epoch_num 130 log_smooth_window: 10 print_batch_step: 10 save_model_dir: ./output/re_vi_layoutxlm_mca save_epoch_step: 2000

evaluation is run every 10 iterations after the 0th iteration

eval_batch_step: [ 0, 19 ] cal_metric_during_train: False save_inference_dir: use_visualdl: False seed: 2022 infer_img: ppstructure/docs/kie/input/temp.jpg save_res_path: ./output/re/mca/with_gt kie_rec_model_dir: kie_det_model_dir:

Architecture: model_type: kie algorithm: &algorithm "LayoutXLM" Transform: Backbone: name: LayoutXLMForRe pretrained: True mode: vi checkpoints:

Loss: name: LossFromOutput key: loss reduction: mean

Optimizer: name: AdamW beta1: 0.9 beta2: 0.999 clip_norm: 10 lr: learning_rate: 0.00005 warmup_epoch: 10 regularizer: name: L2 factor: 0.00000

PostProcess: name: VQAReTokenLayoutLMPostProcess

Metric: name: VQAReTokenMetric main_indicator: hmean

Train: dataset: name: SimpleDataSet data_dir: train_data/mca/mca_train/image label_file_list:

• train_data/mca/mca_train/train.json ratio_list: [ 1.0 ] transforms:
• DecodeImage: # load image img_mode: RGB channel_first: False
• VQATokenLabelEncode: # Class handling label contains_re: True algorithm: *algorithm class_path: &class_path train_data/mca/class_list_mca.txt use_textline_bbox_info: &use_textline_bbox_info True order_method: &order_method "tb-yx"
• VQATokenPad: max_seq_len: &max_seq_len 512 return_attention_mask: True
• VQAReTokenRelation:
• VQAReTokenChunk: max_seq_len: *max_seq_len
• Resize: size: [224,224]
• NormalizeImage: scale: 1 mean: [ 123.675, 116.28, 103.53 ] std: [ 58.395, 57.12, 57.375 ] order: 'hwc'
• ToCHWImage:
• KeepKeys: keep_keys: [ 'input_ids', 'bbox','attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order loader: shuffle: True drop_last: False batch_size_per_card: 2 num_workers: 4 collate_fn: ListCollator

Eval: dataset: name: SimpleDataSet data_dir: train_data/mca/mca_val/image label_file_list:

• train_data/mca/mca_val/val.json transforms:
• DecodeImage: # load image img_mode: RGB channel_first: False
• VQATokenLabelEncode: # Class handling label contains_re: True algorithm: algorithm class_path: class_path use_textline_bbox_info: use_textline_bbox_info order_method: order_method
• VQATokenPad: max_seq_len: *max_seq_len return_attention_mask: True
• VQAReTokenRelation:
• VQAReTokenChunk: max_seq_len: *max_seq_len
• Resize: size: [224,224]
• NormalizeImage: scale: 1 mean: [ 123.675, 116.28, 103.53 ] std: [ 58.395, 57.12, 57.375 ] order: 'hwc'
• ToCHWImage:
• KeepKeys: keep_keys: [ 'input_ids', 'bbox', 'attention_mask', 'token_type_ids', 'image', 'entities', 'relations'] # dataloader will return list in this order loader: shuffle: False drop_last: False batch_size_per_card: 8 num_workers: 8 collate_fn: ListCollator

[Tanmay98]

Also, just to mention,

• model training and inference worked for SER with the same dataset.
• And while inference with the xfund pretrained RE model I am getting this error

[littletomatodonkey]

hi , you need to upgrade paddlenlp to 2.4.1

pip install paddlenlp==2.4.1

[Tanmay98]

Thanks @littletomatodonkey !, both of the above issues were resolved by updating paddlenlp to 2.4.1 from 2.3 version