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错误展示
new_model = load_model(“model.h5”)
报错：
1、keras load_model valueerror: unknown layer :crf
2、keras load_model valueerror: unknown loss function:crf_loss
错误修改
1、load_model修改源码：custom_objects = none 改为 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，即可运行。
补充知识：用keras搭建bilstm crf
使用 实现的crf layer，
安装 keras-contrib
pip install git+https://www.github.com/keras-team/keras-contrib.git
code example：
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# 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():
"""
带embedding的双向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：
如果执行build模型报错，则很可能是keras版本的问题。在keras-contrib==2.0.8且keras==2.0.8时，上面代码不会报错。
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