位置编码(Positional Encoding)是自然语言处理中用于向模型提供序列中元素顺序信息的一种技术。在处理序列数据时,如文本或时间序列,元素的位置是非常重要的,因为它可以影响到句子的意义。例如,“狗咬了人”和“人咬了狗”虽然包含相同的单词,但因为词序不同,意义完全不同。 传统的神经网络架构,比如循环神经网络(RNN)...
sr =16000x = torch.arange(0,20).float()# between [-6,6]y = torch.cos(2* math.pi * x) +3* torch.sin(math.pi * x) +2* torch.cos(x)# between [-2^30, 2^30]y = (y /6* (1<<30)).long()# clear the last 16 bits because they aren't used anywaysy = ((y >>16)...
Positional Encoding对序列中每个物品,以及每个物品对应的Embedding的每个位置,进行了处理,如下: 上式中$pos$指的是某个会话里面item位于第几个位置位置, 取值范围是$[0, max_len]$,i指的是词向量的某个维度, 取值范围是$[0, embed _ dim]$, 上面有$sin$和$cos$一组公式, 也就是对应着$embed _ dim$...
self.sess_bias_embedding = self.add_weight('sess_bias_encoding', shape=(self.sess_max_count, 1, 1), initializer=tf.keras.initializers.TruncatedNormal(mean=0.0, stddev=0.0001, seed=self.seed)) #截断产生正态随机树 self.seq_bias_embedding = self.add_weight('sess_bias_encoding', shape=(1,...
positional_signal = tf.concat([tf.sin(scaled_time), tf.cos(scaled_time)], axis=1)# Pad the signal tensor, if neededpad_size = depth %2ifpad_size !=0: tf.pad(tensor=positional_signal, paddings=[[0,0], [0, pad_size]])# Reshape the signal to make it compatible with the target...
On another front, Sacsin localizes to the mitochondria, as validated by experiments performed on hippocampal neurons, Cos-7 and HeLa cells, primary neurons, ARSACS patient fibroblasts,SACSknockout mice, and organotypic mice brain slice cultures [15]. Sacsin mitochondrial localization plays a seminal...
(np.pi - theta) * (1.+2.* tf.cos(theta) **2) 开发者ID:vincentadam87,项目名称:GPflow,代码行数:12,代码来源:kernels.py 示例5: tl_net ▲点赞 1▼ deftl_net(self, inputs):foriinrange(jishu):ifi <8: self.arg[i]=tf.Variable(tf.random_normal((self.data.num_input,2)), traina...
cosine to even columns and sin to odds.position[:, 0::2] = np.sin(position[:, 0::2])# dim 2iposition[:, 1::2] = np.cos(position[:, 1::2])# dim 2i+1self.position = self.create_parameter(shape=[max_seq_len,self.d_model], default_initializer=paddle.nn.initializer.Assign(...
signal = K.concatenate([K.sin(scaled_time), K.cos(scaled_time)], axis=1)returnK.expand_dims(signal, axis=0) 开发者ID:kpot,项目名称:keras-transformer,代码行数:27,代码来源:position.py 示例3: call ▲点赞 6▼ # 需要导入模块: from keras import backend [as 别名]# 或者: from keras.ba...
positional_signal = tf.concat([tf.sin(scaled_time), tf.cos(scaled_time)], axis=1)# Pad the signal tensor, if neededpad_size = depth %2ifpad_size !=0: tf.pad(tensor=positional_signal, paddings=[[0,0], [0, pad_size]])# Reshape the signal to make it compatible with the target...