
Traceback (most recent call last):


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/bin/clip-train", line 33, in <module>

sys.exit(load_entry_point('clip', 'console_scripts', 'clip-train')())


 "/mnt/beegfs/home/lerner/CLIP/clip/train.py", line 196, in main

trainer.train(**config.get("checkpoint", {}))


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer.py", line 983, in train

self._maybe_log_save_evaluate(tr_loss, model, trial, epoch)


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer.py", line 1058, in _maybe_log_save_evaluate

metrics = self.evaluate()


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer_seq2seq.py", line 74, in evaluate

return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer.py", line 1513, in evaluate

metric_key_prefix=metric_key_prefix,


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer.py", line 1644, in prediction_loop

preds_gatherer.add_arrays(self._gather_and_numpify(preds_host, "eval_preds"))


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer_pt_utils.py", line 330, in add_arrays

self._storage = nested_new_like(arrays, self.total_samples, padding_index=self.padding_index)


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/transformers/trainer_pt_utils.py", line 238, in nested_new_like

return np.full_like(arrays, padding_index, shape=(num_samples, *arrays.shape[1:]))


 "<__array_function__ internals>", line 6, in full_like


 "/mnt/beegfs/home/lerner/anaconda3/envs/transformers/lib/python3.7/site-packages/numpy/core/numeric.py", line 382, in full_like

res = empty_like(a, dtype=dtype, order=order, subok=subok, shape=shape)


 "<__array_function__ internals>", line 6, in empty_like
MemoryError: Unable to allocate 2.77 TiB for an array with shape (200206, 77, 49408) and data type float32

Traceback (most recent call last):


 "main.py", line 19, in <module>

tf.set_random_seed(1234)
AttributeError: module 'tensorflow' has no attribute 'set_random_seed'`
