AttributeError: 'MirroredStrategy' object has no attribute 'experimental_run_v2'

[theashworld]

running the code as is in colab, I get this error:

Traceback (most recent call last):
  File "run_ust.py", line 147, in <module>
    train_model(max_seq_length, X_train, y_train, X_test, y_test, X_unlabeled, model_dir, tokenizer, sup_batch_size=sup_batch_size, unsup_batch_size=unsup_batch_size, unsup_size=unsup_size, sample_size=sample_size, TFModel=TFModel, Config=Config, pt_teacher_checkpoint=pt_teacher_checkpoint, sample_scheme=sample_scheme, T=T, alpha=alpha, valid_split=valid_split, sup_epochs=sup_epochs, unsup_epochs=unsup_epochs, N_base=N_base, dense_dropout=dense_dropout, attention_probs_dropout_prob=attention_probs_dropout_prob, hidden_dropout_prob=hidden_dropout_prob)
  File "/content/UST/ust.py", line 180, in train_model
    y_mean, y_var, y_pred, y_T = mc_dropout_evaluate(model, gpus, len(labels), X_unlabeled_sample, T=T)
  File "/content/UST/ust.py", line 59, in mc_dropout_evaluate
    pred = distributed_eval_step(batch)
  File "/content/UST/ust.py", line 56, in distributed_eval_step
    return strategy.experimental_run_v2(eval_step, args=(dataset_inputs,))
AttributeError: 'MirroredStrategy' object has no attribute 'experimental_run_v2'

tf version is 2.5.0 (provided by colab)

I tried changing the tf version to 1.x but in that case, I get

INFO:filelock:Lock 140358422112272 released on /root/.cache/huggingface/transformers/3c61d016573b14f7f008c02c4e51a366c67ab274726fe2910691e2a761acf43e.37395cee442ab11005bcd270f3c34464dc1704b715b5d7d52b1a461abe3b9e4e.lock
Traceback (most recent call last):
  File "run_ust.py", line 147, in <module>
    train_model(max_seq_length, X_train, y_train, X_test, y_test, X_unlabeled, model_dir, tokenizer, sup_batch_size=sup_batch_size, unsup_batch_size=unsup_batch_size, unsup_size=unsup_size, sample_size=sample_size, TFModel=TFModel, Config=Config, pt_teacher_checkpoint=pt_teacher_checkpoint, sample_scheme=sample_scheme, T=T, alpha=alpha, valid_split=valid_split, sup_epochs=sup_epochs, unsup_epochs=unsup_epochs, N_base=N_base, dense_dropout=dense_dropout, attention_probs_dropout_prob=attention_probs_dropout_prob, hidden_dropout_prob=hidden_dropout_prob)
  File "/content/UST/ust.py", line 113, in train_model
    model = models.construct_teacher(TFModel, Config, pt_teacher_checkpoint, max_seq_length, len(labels), dense_dropout=dense_dropout, attention_probs_dropout_prob=attention_probs_dropout_prob, hidden_dropout_prob=hidden_dropout_prob)
  File "/content/UST/models.py", line 20, in construct_teacher
    encoder = TFModel.from_pretrained(pt_teacher_checkpoint, config=config, from_pt=True, name="teacher")
  File "/usr/local/lib/python3.7/dist-packages/transformers/utils/dummy_tf_objects.py", line 404, in from_pretrained
    requires_backends(cls, ["tf"])
  File "/usr/local/lib/python3.7/dist-packages/transformers/file_utils.py", line 612, in requires_backends
    raise ImportError("".join([BACKENDS_MAPPING[backend][1].format(name) for backend in backends]))
ImportError: 
TFBertModel requires the TensorFlow library but it was not found in your environment. Checkout the instructions on the
installation page: https://www.tensorflow.org/install and follow the ones that match your environment.

[theashworld]

my bad, requirements.txt to the rescue