Python 在抛出'；Xbak:：错误'；what（）：can'；保护不了

我正在尝试执行以下python代码

from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import RandomizedSearchCV
import pandas as pd
from sklearn.model_selection import train_test_split
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras import layers
def create_model(num_filters, kernel_size, vocab_size, embedding_dim, maxlen):
    model = Sequential()
    model.add(layers.Embedding(vocab_size, embedding_dim, input_length=maxlen))
    model.add(layers.Conv1D(num_filters, kernel_size, activation='relu'))
    model.add(layers.GlobalMaxPooling1D())
    model.add(layers.Dense(10, activation='relu'))
    model.add(layers.Dense(1, activation='sigmoid'))
    model.compile(optimizer='adam',
                  loss='binary_crossentropy',
                  metrics=['accuracy'])
    return model


filepath_dict = {'yelp':   'yelp_labelled.txt'}

df_list = []
for source, filepath in filepath_dict.items():
    df = pd.read_csv(filepath, names=['sentence', 'label'], sep='\t')
    df['source'] = source  # Add another column filled with the source name
    df_list.append(df)

df = pd.concat(df_list)
# Main settings
epochs = 20
embedding_dim = 50
maxlen = 100
output_file = 'output.txt'

# Run grid search for each source (yelp, amazon, imdb)
for source, frame in df.groupby('source'):
    print('Running grid search for data set :', source)
    sentences = df['sentence'].values
    y = df['label'].values

    # Train-test split
    sentences_train, sentences_test, y_train, y_test = train_test_split(
        sentences, y, test_size=0.25, random_state=1000)

    # Tokenize words
    tokenizer = Tokenizer(num_words=5000)
    tokenizer.fit_on_texts(sentences_train)
    X_train = tokenizer.texts_to_sequences(sentences_train)
    X_test = tokenizer.texts_to_sequences(sentences_test)

    # Adding 1 because of reserved 0 index
    vocab_size = len(tokenizer.word_index) + 1

    # Pad sequences with zeros
    X_train = pad_sequences(X_train, padding='post', maxlen=maxlen)
    X_test = pad_sequences(X_test, padding='post', maxlen=maxlen)

    # Parameter grid for grid search
    param_grid = dict(num_filters=[32, 64, 128],
                      kernel_size=[3, 5, 7],
                      vocab_size=[vocab_size],
                      embedding_dim=[embedding_dim],
                      maxlen=[maxlen])
    model = KerasClassifier(build_fn=create_model,
                            epochs=epochs, batch_size=10,
                            verbose=False)
    grid = RandomizedSearchCV(estimator=model, param_distributions=param_grid,
                              cv=4, verbose=1, n_iter=5)
    grid_result = grid.fit(X_train, y_train)
    # Evaluate testing set
    test_accuracy = grid.score(X_test, y_test)

    # Save and evaluate results
    prompt = input(f'finished {source}; write to file and proceed? [y/n]')
    if prompt.lower() not in {'y', 'true', 'yes'}:
        break
    with open(output_file, 'a') as f:
        s = ('Running {} data set\nBest Accuracy : '
             '{:.4f}\n{}\nTest Accuracy : {:.4f}\n\n')
        output_string = s.format(
            source,
            grid_result.best_score_,
            grid_result.best_params_,
            test_accuracy)
        print(output_string)
        f.write(output_string)

但是我得到了以下错误

Using TensorFlow backend.
2020-02-07 12:47:46.158272: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory
2020-02-07 12:47:46.158397: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory
2020-02-07 12:47:46.158417: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Running grid search for data set : yelp
Fitting 4 folds for each of 5 candidates, totalling 20 fits
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
2020-02-07 12:47:47.592085: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-02-07 12:47:47.598640: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
2020-02-07 12:47:47.598700: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (nsx-rasa): /proc/driver/nvidia/version does not exist
2020-02-07 12:47:47.599076: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2020-02-07 12:47:47.610322: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2194840000 Hz
2020-02-07 12:47:47.611554: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x79dcfe0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-02-07 12:47:47.611606: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
/image/env/lib/python3.6/site-packages/tensorflow_core/python/framework/indexed_slices.py:433: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
  "Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
terminate called after throwing an instance of 'Xbyak::Error'
  what():  can't protect
Aborted (core dumped)

我不知道这个错误。我试图在ubuntu虚拟机中执行这段代码

python--版本>>python 3.6.10

操作系统详细信息：
分发服务器ID:Ubuntu
说明：Ubuntu 16.04.2 LTS
发布日期：16.04
代号：xenial

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如果有人对此错误或如何避免此错误有任何线索，请提供帮助。提前谢谢。

有人能帮我解决这个错误吗？有人能帮我解决这个错误吗？