print(r)# sequence_loss的结果是0.563261687518082 求loss值 logits=[[1.0,2.0][1.0,2.0][1.0,2.0][1.0,2.0]]logits=[[1.0,2.0][1.0,2.0][1.0,2.0][1.0,2.0]] target=[0.01.01.01.0]target=[0.01.01.01.0] cost=sequence_loss(logits=logits,targets=targets,weights=tf.oneslike(targets,dtype=tf.floa...
tensorflow sequence_loss sequence_loss是nlp算法中非常重要的一个函数.rnn,lstm,attention都要用到这个函数.看下面代码: # coding: utf-8import numpy as np import tensorflow as tf from tensorflow.contrib.seq2seq import sequence_loss logits_np = np.array([ [[0.5,0.5,0.5,0.5], [0.5,0.5,0.5,0.5]...
注:由于tensorflow版本的不同,这个函数所在的模块可能不同,如:tf.nn.seq2seq.sequence_loss_by_example和tf.contrib.legacy_seq2seq.sequence_loss_by_example 在正式进入sequence_loss_by_example()函数的计算过程之前,需要先复习下两个基本的知识点,softmax的计算和交叉熵的计算。... 查看原文 TensorFlow中seq2...
#tf.contrib.seq2seq.sequence_loss example:seqence loss 实例代码#!/usr/bin/env python# -*- coding: utf-8 -*-importtensorflowastfimportnumpyasnpparams=np.random.normal(loc=0.0,scale=1.0,size=[10,10])encoder_inputs=tf.placeholder(dtype=tf.int32,shape=[10,10])decoder_inputs=tf.placeholder...
2. Sequence-to-Sequence Loss:序列到序列损失主要用于解决输入和输出都是文本序列的问题，如机器翻译、...
tf.contrib.seq2seq.sequence_loss example:seqence loss 实例代码 #!/usr/bin/env python # -*- coding: utf-8 -*- import tensorflow as tf import numpy as np params=np.random.normal(loc=0.0,scale=1.0,size=[10,10]) encoder_inputs=tf.placeholder(dtype=tf.int32,shape=[10,10]) ...
示例1: sequence_loss ▲点赞 3▼ # 需要导入模块: from tensorflow.python.ops import seq2seq [as 别名]# 或者: from tensorflow.python.ops.seq2seq importsequence_loss[as 别名]defsequence_loss(self, y_pred, y_true):''' Loss function for the seq2seq RNN. Reshape predicted and true (label...
示例1: generate_sequence_output ▲點讚 5▼ # 需要導入模塊: from tensorflow.contrib import legacy_seq2seq [as 別名]# 或者: from tensorflow.contrib.legacy_seq2seq importsequence_loss_by_example[as 別名]defgenerate_sequence_output(num_encoder_symbols, ...
Boosting Algorithm with Sequence-Loss Cost Function for Structured Prediction[C]//Proceedings of International Conference on Hybrid Artificial Intelligence Systems. 2010: 573-580.Kajdanowicz T., Kazienko P., Kraszewski J.: Boosting Algorithm with Sequence-Loss Cost Function for Structured Prediction. ...
网络不同时拉紧钢丝束应力损失 网络释义 1. 不同时拉紧钢丝束应力损失 建筑词汇英语翻译... ... sequence of prestressing 预应力工序sequence stressing loss不同时拉紧钢丝束应力损失series 群列 ... www.zftrans.com|基于21个网页