TensorFlow Question-Answering example fails to run (cardinality error)

Environment info

• transformers version: 4.4.0.dev0
• Platform: Linux-4.15.0-111-generic-x86_64-with-Ubuntu-18.04-bionic
• Python version: 3.6.8
• PyTorch version (GPU?): 1.7.1 (False)
• Tensorflow version (GPU?): 2.2.0 (False)
• Using GPU in script?: No
• Using distributed or parallel set-up in script?: No

Information

Model I am using (Bert, XLNet …): bert-base-uncased or roberta-base

The problem arises when using:

• the official example scripts: question-answering (run_tf_squad.py)

Error message: Instructions for updating: back_prop=False is deprecated. Consider using tf.stop_gradient instead. Instead of: results = tf.map_fn(fn, elems, back_prop=False) Use: results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems)) 87599it [01:00, 1437.03it/s] 10570it [00:11, 958.83it/s] convert squad examples to features: 2%|_ | 1697/87599 [00:13<10:43, 133.40it/s][WARNING|squad.py:118] 2021-02-17 22:20:03,736 >> Could not find answer: ‘municipal building and’ vs. ‘a municipal building’ convert squad examples to features: 50%|_____ | 43393/87599 [05:04<05:04, 145.24it/s][WARNING|squad.py:118] 2021-02-17 22:24:55,103 >> Could not find answer: ‘message stick,’ vs. ‘a message stick’ convert squad examples to features: 100%|| 87599/87599 [10:10<00:00, 143.59it/s] add example index and unique id: 100%|| 87599/87599 [00:00<00:00, 784165.53it/s] convert squad examples to features: 100%|| 10570/10570 [01:14<00:00, 140.99it/s] add example index and unique id: 100%|| 10570/10570 [00:00<00:00, 510000.04it/s] [WARNING|integrations.py:60] 2021-02-17 22:31:16,214 >> Using the WAND_DISABLED environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none). [INFO|trainer_tf.py:125] 2021-02-17 22:31:16,214 >> To use comet_ml logging, run pip/conda install comet_ml see https://www.comet.ml/docs/python-sdk/huggingface/ Traceback (most recent call last): File “run_tf_squad.py”, line 256, in <module> main() File “run_tf_squad.py”, line 250, in main trainer.train() File “/home/transformers/src/transformers/trainer_tf.py”, line 457, in train train_ds = self.get_train_tfdataset() File “/home/transformers/src/transformers/trainer_tf.py”, line 141, in get_train_tfdataset self.num_train_examples = self.train_dataset.cardinality().numpy() AttributeError: ‘_AssertCardinalityDataset’ object has no attribute ‘cardinality’

The tasks I am working on is:

• an official GLUE/SQUaD task: SQUaD v1

To reproduce

1. Use the latest master from huggingface/transformers
2. Go to examples/question-answering
3. Run WANDB_DISABLED=true python run_tf_squad.py --model_name_or_path roberta-base --output_dir model --max_seq_length 384 --num_train_epochs 2 --per_device_train_batch_size 8 --per_device_eval_batch_size 16 --do_train --do_eval --logging_dir logs --logging_steps 10 --learning_rate 3e-5 --no_cuda=True --doc_stride 128

Could you take a look @sgugger?

[jeehunkang]

Hello, I am getting the same error.

It says “AttributeError: ‘Dataset’ object has no attribute ‘cardinality’” when I train it. Does anyone know how I should address this issue?

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