sequential

I was told here that: The order of generate is not guaranteed => depending on the implementation I have looked up gcc's implementation of generate : for (; __first != __last; ++__first) *__first = __gen(); And Visual Studio implements it identically to that. This is a relief to me as using a lambda in generate that reads and writes to a capture could have undeterministic results: int foo[] = {1, 0, 13}; vector<int> bar(3); generate(bar.begin(), bar.end(), [&]() { static auto i = 0; static auto total = 0; total += foo[i]; return foo[i] / total; }); I expect bar to contain {1, 0, 0} . If I am

Keras是一套基于Tensorflow、Theano及CNTK后端的高层神经网络API，可以非常友好地支持快速实验，本文从零开始介绍了如何使用Keras搭建MLP并给出两个示例。 基于Ubuntu安装Keras 具体安装过程在官方中英文文档中有详细说明 中文 https://keras-cn.readthedocs.io/en/latest/for_beginners/keras_linux/ 英文 https://keras.io/#installation Keras基础知识 Sequential models 可以认为Keras中的所谓模型(models)就是某个具体的网络结构，如MLP、CNN、LSTM等，在Keras中它们被分为两种：序贯模型(Sequential)和函数式模型(Model)。 Sequential模型就是一个直接由若干网络层线性堆叠起来的网络，使用如下代码创建一个Sequential对象： from keras.models import Sequential model = Sequential() Sequential的构造函数可以接收一个由layer组成的list，用以初始化该model model = Sequential([ Dense(32, input_shape=(784,)),#一个Dense层 Activation('relu'),

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Consider this code Object found = collection.stream() .filter( s -> myPredicate1(s)) .filter( s -> myPredicate2(s)) .findAny() Will it process entire stream, and call both myPredicate1 and myPredicate2 for all elements of the collection? Or will as many predicates be called as are needed to actually find the value? 回答1: Yes it is, as the Stream.findAny() documentation states: This is a short-circuiting terminal operation. It's a common misconception that objects in stream are "pushed" towards consuming operation. It's actually the other way

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I am trying to merge two Sequential models In Keras 2.0, using the following line: merged_model.add(Merge([model1, model2], mode='concat')) This still works fine, but gives a warning: "The `Merge` layer is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc." However, studying the Keras documentation and trying add, Add(), has not resulted in something that works. I have read several posts from people with the same problem, but found no solution that works in my case

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I read that java volatile are sequential consistent but not atomic. For atomicity java provides different library. Can someone explain difference between two, in simple english ? (I believe the question scope includes C/C++ and hence adding those language tags to get bigger audience.) 回答1: Imagine those two variables in a class: int i = 0 ; volatile int v = 0 ; And those two methods void write () { i = 5 ; v = 2 ; } void read () { if ( v == 2 ) { System . out . println ( i ); } } The volatile semantics guarantee that read will

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I'm having newsequentialid() learning problems in sql server management studio. Create a table with a uniqueidentifier column 'UniqueID', and set the default to newsequentialid(). Step 1. saving the design: 'Table_1' table - Error validating the default for column 'UniqueID'. Save it anyway. Step 2. view the sql: CREATE TABLE [ dbo ].[ Table_1 ]( [ ID ] [ int ] IDENTITY ( 1 , 1 ) NOT NULL , [ Name ] [ nvarchar ]( 50 ) NOT NULL , [ UniqueID ] [ uniqueidentifier ] NOT NULL ) ON [ PRIMARY ] GO ALTER TABLE [ dbo ].[ Table_1 ] ADD