## PyTorch ## RNN Layer使用 主讲人：龙良曲 ## Folded model [batch, feature len]@[hidden len, feature len] $ ^{T} $ +[batch, hidden len]@[hidden len, hidden len] $ ^{T} $ [0,0,0 ... ] $$ x_{t}@w_{xh} + h_{t}@w_{hh} h0) x: [seq len, b, word vec] h0/ht: [num layers, b, h dim] out: [seq len, b, h dim] ## Single layer RNN ## ☐ ☐ ☐ rnn = nn.RNN(input_size=100, hidden_size=20, num_layers=1) print(rnn) x = torch.randn(10 h_{t}^{2}@w_{hh}^{2} $$ [0,0,0 ... ] $$ x_{t}@w_{xh}^{1} + h_{t}^{1}@w_{hh}^{1} $$ feature ## 2 layer RNN ## ☐ ☐ ☐ In [17]: rnn=nn.RNN(100, 10, num_layers=2) In [18]: rnn.__parameters.keys() Out[18]:

Default: 1 ### LSTM.forward() - out, (ht, ct) = lstm(x, [ht_1, ct_1]) x: [seq, b, vec] h/c: [num_layer, b, h] out: [seq, b, h] ## ☐ ☐ ☐ 1 lstm = nn.LSTM(input_size=100, hidden_size=20, num_layers=4) LSTMCell.forward() ■ ht, ct = lstmcell(xt, [ht_1, ct_1]) xt: [b, vec] - ht/ct: [b, h] print('one layer lstm') cell = nn.LSTMCell(input_size=100, hidden_size=20) h = torch.zeros(3, 20) c = torch shape, c.shape) torch.Size([3, 20]) torch.Size([3, 20]) ## Single layer ## ☀️ ☁️ ☁️ ## Two Layers ## ☐ ☐ ☐ print('two layer lstm') cell1 = nn.LSTMCell(input_size=100, hidden_size=30) cell2

in Conan C++ Package Manager DIEGO RODRIGUEZ-LOSADA GONZALEZ  ### CONAN 2.0 C/C++ Package Manager ## Outline - Introduction

Copper, L2, Bot) Layer selection Tool 10 D Code selection (hight light items that use this dcode) fmt: mm X4.6 Y4.6 no LZ Info about Gerber file options loaded in the current layer ### 4. Left toolbar Miscellaneous  Hide Layers Manager  Options  Clear Layer  Text Editor •

Django documentation 1.1 Getting help 1.2 First steps 1.3 The model layer 1.4 The view layer 1.5 The template layer 1.6 Forms 1.7 The development process 1.8 The admin 1.9 Security to write reusable apps | Writing your first patch for Django ### 1.3 The model layer Django provides an abstraction layer (the “models”) for structuring and manipulating the data of your Web application Providing initial data | Optimize database access | PostgreSQL specific features ### 1.4 The view layer Django has the concept of “views” to encapsulate the logic responsible for processing a user’s request

. . . . . . . . . . . . . 2 1.4 The model layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.5 The view layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.6 The template layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.7 Forms . . . . . . . . . . . . How to write reusable apps | Writing your first patch for Django 1.4 The model layer Django provides an abstraction layer (the “models”) for structuring and manipulating the data of your Web application

CakePHP at a Glance • Conventions Over Configuration • The Model Layer • The View Layer • The Controller Layer • CakePHP Request Cycle • Just the Start • Additional System ○ Example Event Usage ○ Accessing Event Managers ■ Global Event Manager ■ Tracking Events ○ Core Events ○ Registering Listeners ■ The conventions chapter covers the various conventions that CakePHP uses. ## The Model Layer The Model layer represents the part of your application that implements the business logic. It is responsible

15 3.4.3 Goal ..... 15 3.4.4 Implementation ..... 16 L1 Kernel Layer ..... 16 L2 Feature Layer ..... 16 L3 Ecosystem Layer ..... 17 Features ..... 18 4.1 DB Compatibility ..... 18 4.1.1 above multi-model databases. It focuses on how to reuse existing databases and their respective upper layer, rather than creating a new database. The concepts at the core of the project are Link, Enhance and ShardingSphere-JDBC defines itself as a lightweight Java framework that provides extra services at the Java JDBC layer. With the client end connecting directly to the database, it provides services in the form of a jar

Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) Batch Normalization ## Batch Norm Layer Norm  Batch normalization on $z^{i}$ ## ☀️ ☁️ ☁️ In [9]: x=torch.randn(100,16)+0.5 In [10]: layer=torch.nn.BatchNorm1d(16) In [11]: layer.running_mean, layer.running_var (tensor([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0 tensor([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])) In [12]: out=layer(x) In [13]: layer.running_mean, layer.running_var (tensor([0.0625, 0.0752, 0.0589, 0.0358, 0.0662, 0.0651, 0.0572,

CakePHP at a Glance • Conventions Over Configuration • The Model Layer • The View Layer • The Controller Layer • CakePHP Request Cycle • Just the Start • Additional Rendering Events System Example Event Usage Accessing Event Managers Global Event Manager Tracking Events Core Events Registering Listeners Registering Anonymous Listeners The conventions chapter covers the various conventions that CakePHP uses. ## The Model Layer The Model layer represents the part of your application that implements the business logic. It is responsible