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View Code? Open in Web Editor NEW用于存储NLP常用模型
用于存储NLP常用模型
I see you using open source dataset and label pinyin for every dataset, but we all know label pinyin has muti-tone issue. So how can I reduce error when labeling pinyin for other sentences.
ctc decode阶段,会不会出现内存泄漏的问题,网上有人说r1 = tfk.get_value(r[0][0])这个存在内存泄漏,有没有遇到相似问题?求解,多谢!
RT
def cnn_cell (size, x, pool=True):
x = norm(conv2d(size)(x))
x = norm(conv2d(size)(x))
if pool:
x = maxpool(x)
return x
load your trained model file,but not right
如何修改得到汉字的结果呢
如题,经过代码分析,默认情况下
self.batch_size =self.q_size;
gpu_num=1;
sample_nums = self.batch_size * gpu_num;
而遍历循环代码for j in range(self.q_size // sample_nums)中:
self.q_size // sample_nums 不就等价于1//gpu_num么?那这个循环j始终为range(1)啊,
求解是不是应该改成 sample_nums = self.batch_size // gpu_num?
附上代码片段:
‘‘’
“#” 开始迭代,使用Adam优化的随机梯度下降法,并将结果输出到日志文件
print('training------')
index_list = [i for i in range(self.q_size)]
sample_nums = self.batch_size * gpu_num
for i in range(self.epoch_steps):
total_loss = 0
total_accuracy = 0
for j in range(self.q_size // sample_nums): # 默认情况:batch_size == q_size
if self.is_sample:
sample_list = simple_sampling(index_list, sample_nums)
q_set = []
t_set = []
q_actual_length = []
t_actual_length = []
for index in sample_list:
q_set.append(self.q_set[index])
t_set.append(self.t_set[index])
q_actual_length.append(self.q_actual_length[index])
t_actual_length.append(self.t_actual_length[index])
‘’’
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