Python FailedPremissionError(回溯见上文):尝试使用未初始化的值rnn/gru_cell/gates/kernel
我使用tensorflow运行下面的代码,并得到错误:Python FailedPremissionError(回溯见上文):尝试使用未初始化的值rnn/gru_cell/gates/kernel,python,tensorflow,Python,Tensorflow,我使用tensorflow运行下面的代码,并得到错误: tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value rnn/gru_cell/gates/kernel [[Node: rnn/gru_cell/gates/kernel/read = Identity[T=DT_FLOAT, _device="/job:localhost/replic
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value rnn/gru_cell/gates/kernel
[[Node: rnn/gru_cell/gates/kernel/read = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](rnn/gru_cell/gates/kernel)]]
我在网站上搜索了类似的错误,但是我的代码不能很好地工作
train.py:
if __name__ == '__main__':
q = np.array([[1,2,3,1,4],[2,3,4,1,0],[3,4,1,2,1]])
f = np.ones((3,2,5))
y = np.array([[1,0,0,0],[0,0,0,1],[0,0,1,0]])
#init = tf.initialize_all_variables()
with tf.Session() as sess:
m = model.Readers_Model(3,0.01,5,5,2,5,5)
sess.run(m.init_op)
loss,_ = sess.run([m.input_()],
{m.question_placeholder:q,m.fact_placeholder:f,
m.label_placeholder:y,m.dropout_placeholder:0.1})
print ('loss is %f'%loss)
model.py:
class Readers_Model(object):
def __init__(self,batch_size,lr,max_q_len,max_f_len,num_doc,hidden_size,vocub_size):
self.init_op = tf.global_variables_initializer()
self.embedding_size = hidden_size #word embedding
self.word_embeddings = tf.get_variable('embedding',[self.vocabulary_size, self.embedding_size],
initializer=tf.random_normal_initializer(mean=0, stddev=1))
self.label_placeholder = tf.placeholder(tf.int32, shape=(self.batch_size,self.num_class))
self.fact_placeholder = tf.placeholder(tf.int32, shape=(self.batch_size, self.num_doc, self.max_f_len))
self.dropout_placeholder = tf.placeholder(tf.float32)
self.question_placeholder = tf.placeholder(tf.int32, shape=(self.batch_size, self.max_q_len),name='question')
def quesiton_encoding_layer(self):
input = tf.nn.embedding_lookup(self.word_embeddings, self.question_placeholder)
gru_cell = tf.contrib.rnn.GRUCell(self.hidden_size)
output, last_state = tf.nn.dynamic_rnn(gru_cell,
input,
dtype=np.float32,
)
#shape:[batch_size, GRU_hidden_size]
'''
last_state = tf.nn.dropout(last_state, self.dropout_placeholder)
'''
last_hidden_unit = last_state[1]
return output,last_state
看看上面的代码,我在会话开始时运行了tf.initalize_all_variables(),还初始化了名为embbedding的tf.variables。那么错误的原因是什么呢 创建所有变量后,应实例化操作
tf.global\u variables\u initializer()
。例如,以下代码段产生了一个FailedPremissionError:试图使用未初始化的值
:
import tensorflow as tf
init = tf.global_variables_initializer()
a = tf.Variable(1)
with tf.Session() as sess:
sess.run(init)
print(sess.run(a))
请注意,在
Readers\u模型中,
您在self.word\u嵌入之前实例化了self.init\u op
,可能也在gru单元之前。
您在哪里调用quesiton\u编码层
?