Jinja2 Documentation Release 2.10 November 08, 2017 Contents I Jinja2 Documentation 1 1 Introduction 3 2 API 7 3 Sandbox 39 4 Native Python Types 45 5 Template Designer Documentation 47 6 Extensions Changelog 125 i ii Part I JINJA2 DOCUMENTATION 1 2 CHAPTER 1 Introduction This is the documentation for the Jinja2 general purpose templating language. Jinja2 is a library for Python that is designed home with Jinja2. It’s both designer and developer friendly by sticking to Python’s principles and adding functionality useful for tem- plating environments. 1.1 Prerequisites Jinja2 works with Python

Hello 算法 Python 语言版 靳宇栋（Krahets） Release 1.0.0b2 2023‑03‑30 序 两年前，我在力扣上分享了《剑指 Offer》系列题解，受到了很多小伙伴的喜爱与支持。在此期间，我也回复 了许多读者的评论问题，遇到最多的问题是“如何入门学习算法”。我渐渐也对这个问题好奇了起来。 两眼一抹黑地刷题应该是最受欢迎的方式，简单粗暴且有效。然而，刷题就如同玩“扫雷”游戏，自学能力强 qualifier1024, Cathay‑Chen, Guanngxu, xBLACKICEx, what‑is‑me, L‑Super, Slone123c, mgisr, longranger2, xiongsp, WSL0809, Wonderdch, a16su, hpstory, JeffersonHuang, xjr7670, MolDuM, XC‑Zero, DullSword, 1.3. 小结 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 复杂度分析 12 2.1. 算法效率评估 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

FPGA 助力 Python 加速计算 陈志勇 高级技术市场经理 安富利电子科技 2019年9月21日， 上海 2 Ø Python 语言：易学易读易用、可扩展性、可移植性等。 Ø Python 开发工具：库丰富、效率高、调试方便 Ø Python 的应用： 人工智能、数据分析等 Ø Python 的生态环境：软件平台、硬件平台、方案合作伙伴等 Ø 用 Python 如何开发嵌入式产品？如何实现 Engines High Speed Connectivity Video Codec 8K4K (15fps) 4K2K (60fps) High Speed Peripherals Key Interfaces Graphics Processor ARM Mali-400MP2 Memory Subsystem High Bandwidth Low Latency Ø 是一种从 C -> 借用硬件设计的思路 高层次综合工具 （Vivado HLS) 11 赛灵思 openCV 库：xFopencv - HW Accelerated OpenCV Functions Level 1 Level 2 Level 3 Absolute difference Channel combine Box Scale/Resize Histogram of Oriented Gradients (HOG)

Int8 (TPU, tf.bfloat16) (tf.float32) (GPU, tf.float16) 低精度浮点数的优点 1.节约内存/显存的使用（FP16为原来的1/2，int8为原来的1/4） 2.特殊的硬件专门用于低精度浮点数的计算加速（TensorCore） Model Speedup BERT Q&A 3.3X speedup GNMT 1.7X speedup NCF speedup FP16浮点数（E5M10）的表示范围 FP16模型的训练方法 Int8模型的推断过程 2 TensorFlow的FP16模型 实数的16-bit半精度浮点数和8-bit定点数表示 使用低精度的意义 TensorCores适用条件 1. 卷积：K（输入通道），C（输出通道） 2. 通用矩阵乘法（GEMM）：MxK，KxN，（M，N，K） FP16: 大小为8x Int8: 大小为16x layers.Conv2D(32, (3,3), 1, "same", dtype=tf.float16) ret_fp16 = conv1(input_fp16) ret = tf.cast(ret_fp16, dtype=tf.float32) s = tf.Session() s.run(tf.global_variables_initializer()) r1, r2 = s.run([ret

开始实现 1989/12 v0.9.0 1991/2 v1.0.0 1994/1 v2.0 2000/10 v2.5 2006/9 v2.6 2008/10 v3.0 2008/12 v2.7 2010/7 v3.7 2018/6 AWS发展时间线 2019/10 开始实现 1989/12 v0.9.0 1991/2 v1.0.0 1994/1 v2.0 2000/10 2008/12 v2.7 2010/7 v3.7 2018/6 贝索斯开始思考 微服务 2000 Amazon S3 2006/3 Amazon SQS 2006/7 Amazon EC2 2006/8 开始研发 2004 AWS Lambda 2014/11 2019/10 22个区域 165项服务 Python被称为“瑞士军刀” • Web开发 • AI / 机器学习 运行在AWS上 Source: Nucleus Research, November 2018 自由切换环境 - TensorFlow 切换到Python3上的TensorFlow和Keras 2 启动 iPython 终端 运行 TensorFlow 程序 已切换环境 自由切换环境 - PyTorch 具有 CUDA 10 和 MKL-DNN 的 Python 3 上的 PyTorch

another database, there are many DB-API 2.0-compatible drivers out there, such as pymysql or psycopg2 for MySQL and Postgres respectively. Cython [http://cython.org/]: used for various speedups. Can give 'pets' ... for pet in person.pets: ... print ' ', pet.name, pet.animal_type ... Bob 2 pets Kitty cat Fido dog Grandma L. 0 pets Herb 1 pets Mittens Jr cat Once again we’ve 'pets' ... for pet in person.pets: ... print ' ', pet.name, pet.animal_type ... Bob 2 pets Kitty cat Fido dog Grandma L. 0 pets Herb 1 pets Mittens Jr cat Even though we

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 2 Note 209 3 Indices and tables 211 i ii peewee Documentation, Release 2.10.2 Peewee is a simple module that contains special/custom field types. Contents 1 peewee Documentation, Release 2.10.2 2 Contents CHAPTER 1 Contents: 1.1 Installing and Testing Most users will want to simply install the another database, there are many DB-API 2.0-compatible drivers out there, such as pymysql or psycopg2 for MySQL and Postgres respectively. • Cython: used for various speedups. Can give a big boost to certain

another database, there are many DB-API 2.0-compatible drivers out there, such as pymysql or psycopg2 for MySQL and Postgres respectively. Cython [http://cython.org/]: used for various speedups. Can give for person in Person.select(): print person.name, person.pets.count(), 'pets' # prints: # Bob 2 pets # Grandma L. 0 pets # Herb 1 pets Once again we’ve run into a classic example of N+1 query behavior attribute on the returned model instances. print person.name, person.pet_count, 'pets' # prints: # Bob 2 pets # Grandma L. 0 pets # Herb 1 pets Now let’s list all the people and the names of all their pets

another database, there are many DB-API 2.0-compatible drivers out there, such as pymysql or psycopg2 for MySQL and Postgres respectively. Cython [http://cython.org/]: used for various speedups. Can give for person in Person.select(): print(person.name, person.pets.count(), 'pets') # prints: # Bob 2 pets # Grandma L. 0 pets # Herb 1 pets Once again we’ve run into a classic example of N+1 query behavior attribute on the returned model instances. print(person.name, person.pet_count, 'pets') # prints: # Bob 2 pets # Grandma L. 0 pets # Herb 1 pets Now let’s list all the people and the names of all their pets

0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 2 Note 269 3 Indices and tables 271 i ii peewee Documentation, Release 3.5.0 Attention: Peewee 3 module that contains special/custom field types. Contents 1 peewee Documentation, Release 3.5.0 2 Contents CHAPTER 1 Contents: 1.1 Installing and Testing Most users will want to simply install the another database, there are many DB-API 2.0-compatible drivers out there, such as pymysql or psycopg2 for MySQL and Postgres respectively. • Cython: used for various speedups. Can give a big boost to certain