錯誤展示

new_model = load_model(“model.h5”)

報錯：

1、keras load_model valueError: Unknown Layer :CRF

2、keras load_model valueError: Unknown loss function:crf_loss

錯誤修改

1、load_model修改源碼：custom_objects = None 改為 def load_model(filepath, custom_objects, compile=True)：

2、new_model = load_model(“model.h5”,custom_objects={‘CRF': CRF,‘crf_loss': crf_loss,‘crf_viterbi_accuracy': crf_viterbi_accuracy}

以上修改后，即可運行。

補充知識：用keras搭建bilstm crf

安裝 keras-contrib

pip install git+https://www.github.com/keras-team/keras-contrib.git

Code Example：

# coding: utf-8

from keras.models import Sequential

from keras.layers import Embedding

from keras.layers import LSTM

from keras.layers import Bidirectional

from keras.layers import Dense

from keras.layers import TimeDistributed

from keras.layers import Dropout

from keras_contrib.layers.crf import CRF

from keras_contrib.utils import save_load_utils

VOCAB_SIZE = 2500

EMBEDDING_OUT_DIM = 128

TIME_STAMPS = 100

HIDDEN_UNITS = 200

DROPOUT_RATE = 0.3

NUM_CLASS = 5

def build_embedding_bilstm2_crf_model():

"""

帶embedding的雙向LSTM + crf

"""

model = Sequential()

model.add(Embedding(VOCAB_SIZE, output_dim=EMBEDDING_OUT_DIM, input_length=TIME_STAMPS))

model.add(Bidirectional(LSTM(HIDDEN_UNITS, return_sequences=True)))

model.add(Dropout(DROPOUT_RATE))

model.add(Bidirectional(LSTM(HIDDEN_UNITS, return_sequences=True)))

model.add(Dropout(DROPOUT_RATE))

model.add(TimeDistributed(Dense(NUM_CLASS)))

crf_layer = CRF(NUM_CLASS)

model.add(crf_layer)

model.compile('rmsprop', loss=crf_layer.loss_function, metrics=[crf_layer.accuracy])

return model

def save_embedding_bilstm2_crf_model(model, filename):

save_load_utils.save_all_weights(model,filename)

def load_embedding_bilstm2_crf_model(filename):

model = build_embedding_bilstm2_crf_model()

save_load_utils.load_all_weights(model, filename)

return model

if __name__ == '__main__':

model = build_embedding_bilstm2_crf_model()

注意：

如果執行build模型報錯，則很可能是keras版本的問題。在keras-contrib==2.0.8且keras==2.0.8時，上面代碼不會報錯。

以上這篇keras 解決加載lstm+crf模型出錯的問題就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支持。

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