Error creating and exporting TFLite after fine-tuning (using run_squad_v1.py/run_squad_v2.py)

[manojpreveen]

python -m albert.run_squad_v1
--albert_config_file=albert/assets/albert_config.json
--output_dir=albert/output
--train_file=albert/train-v1.1.json
--predict_file=albert/dev-v1.1.json
--train_feature_file=albert/output/train.tfrecord
--predict_feature_file=albert/output/dev.tfrecord
--predict_feature_left_file=albert/output/pred_left_file_example.pkl
--albert_hub_module_handle=https://tfhub.dev/google/albert_base/1
--spm_model_file=albert/assets/30k-clean.model
--do_lower_case
--max_seq_length=384
--doc_stride=128
--max_query_length=64
--do_train=true
--do_predict=false
--train_batch_size=16
--predict_batch_size=8
--learning_rate=5e-5
--num_train_epochs=2.0
--warmup_proportion=.1
--save_checkpoints_steps=5000
--n_best_size=20
--max_answer_length=128
--export_dir=albert/modelite

The above is the command I ran to finetune Albert-Base on SQuAD1.1 The finetune was successful and I got both tensorflow checkpoints and the model in saved_model format.

When the Conversion of saved_model to TFLite Model step starts, it's throwing out an error as below :

File "/usr/local/share/anaconda3/lib/python3.7/site-packages/tensorflow_core/lite/python/convert_saved_model.py", line 194, in freeze_saved_model raise ValueError("SavedModels with assets/ directory are not supported.") ValueError: SavedModels with assets/ directory are not supported.

Is it just happening for me or is it not supported by tensorflow itself yet. Is there any workaround to create TFLite model. Please Help.

Thanks.

[taylorshin]

I'm having a similar problem. We would greatly appreciate some help/guidance!

[PantherYan]

We also meet this issue, any solutions?