python train.py 报错，麻烦帮看下啥问题

[georgewangchn]

Some layers from the model checkpoint at pre_models were not used when initializing TFBertModel: ['mlm___cls', 'nsp___cls']

• This IS expected if you are initializing TFBertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing TFBertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
  All the layers of TFBertModel were initialized from the model checkpoint at pre_models.
  If your task is similar to the task the model of the checkpoint was trained on, you can already use TFBertModel for predictions without further training.
  2021-01-29 19:33:57.271548: W tensorflow/core/framework/op_kernel.cc:1767] OP_REQUIRES failed at einsum_op_impl.h:714 : Resource exhausted: OOM when allocating tensor with shape[64,12,218,218] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu
  Traceback (most recent call last):
  File "train.py", line 6, in
  training_files="data",
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/train.py", line 109, in train
  loop,
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/utils/common.py", line 308, in run_in_loop
  result = loop.run_until_complete(f)
  File "uvloop/loop.pyx", line 1456, in uvloop.loop.Loop.run_until_complete
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/train.py", line 174, in train_async
  finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/train.py", line 353, in _train_async_internal
  finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/train.py", line 396, in _do_training
  finetuning_epoch_fraction=finetuning_epoch_fraction,
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/train.py", line 818, in _train_nlu_with_validated_data
  **additional_arguments,
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/train.py", line 116, in train
  interpreter = trainer.train(training_data, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/model.py", line 209, in train
  updates = component.train(working_data, self.config, **context)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 814, in train
  batch_docs = self._get_docs_for_batch(batch_messages, attribute)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 767, in _get_docs_for_batch
  batch_token_ids, batch_tokens, batch_examples, attribute, inference_mode
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 685, in _get_model_features_for_batch
  batch_attention_mask, padded_token_ids
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 537, in _compute_batch_sequence_features
  np.array(padded_token_ids), attention_mask=np.array(batch_attention_mask)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 901, in call
  training=inputs["training"],
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 694, in call
  training=inputs["training"],
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 452, in call
  hidden_states, attention_mask, head_mask[i], output_attentions, training=training
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 418, in call
  hidden_states, attention_mask, head_mask, output_attentions, training=training
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 354, in call
  input_tensor, attention_mask, head_mask, output_attentions, training=training
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 985, in call
  outputs = call_fn(inputs, *args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/transformers/models/bert/modeling_tf_bert.py", line 288, in call
  attention_scores = tf.einsum("aecd,abcd->acbe", key_layer, query_layer)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
  return target(*args, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/ops/special_math_ops.py", line 684, in einsum
  return _einsum_v2(equation, *inputs, **kwargs)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/ops/special_math_ops.py", line 1113, in _einsum_v2
  return gen_linalg_ops.einsum(inputs, resolved_equation)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/ops/gen_linalg_ops.py", line 1088, in einsum
  _ops.raise_from_not_ok_status(e, name)
  File "/root/anaconda3/envs/rasa/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 6843, in raise_from_not_ok_status
  six.raise_from(core._status_to_exception(e.code, message), None)
  File "", line 3, in raise_from
  tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[64,12,218,218] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu [Op:Einsum]

[Dustyposa]

你用的模型文件是？