About me 2 6 ways for implementing math expressions calculator, Amir Kirsh Lecturer Academic College of Tel-Aviv-Yaffo and Tel-Aviv University Developer Advocate at Member of the Israeli ISO C++ NB NB Co-Organizer of the CoreCpp conference and meetup group3 6 ways for implementing math expressions calculator, Amir Kirsh Suffering from slow builds? It’s not just waste of time It affects your dev for implementing math expressions calculator, Amir KirshSuccess Stories 5 6 ways for implementing math expressions calculator, Amir KirshSuccess Stories 6 6 ways for implementing math expressions calculator

................ 212 23. ES6 − MATH ..................................................................................................................... 214 Math Properties ...................... ............ 214 Math- E ............................................................................................................................................... 214 Math- LN2 ............. ............. 214 Math- LN10 ......................................................................................................................................... 215 Math- LOG2E .............

. 17 Citation rendering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Math rendering in HTML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Options for wrapper . 32 Citation rendering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Math rendering in HTML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Options for wrapper Variables for HTML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Variables for HTML math . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Variables for HTML slides . . . . . . .

amount: Math.floor((Math.random() * 10) + 1), category: "Food", location: "Mcdonald", spendOn: new Date(2020, 4, Math.floor((Math floor((Math.random() * 30) + 1), 10, 10, 10), createdOn: new Date(2020, 4, Math.floor((Math.random() * 30) + 1), 10, 10, 10) }, { id: 1, amount: Math.floor((Math.random() * 10) + 1), category: "Food", location: "KFC", spendOn: new Date(2020, 4, Math.floor((Math.random()

com/catchorg/Catch2 Frameworks Part 0: Basics 9auto abs(int x) -> int; math.hpp math.cpp test_math.cpp #include #include "math.hpp" TEST_CASE("Absolute value tests"){ CHECK( abs( 4 Frameworks Part 0: Basics 10auto abs(int x) -> int; math.hpp math.cpp test_math.cpp #include #include "math.hpp" TEST_CASE("Absolute value tests"){ CHECK( abs( │ └── math │ ├── math.cpp │ └── math.hpp └── test ├── stuff │ └── test_stuff.cpp ├── things │ └── test_things.cpp └── math └── test_math.cpp Where

. . . . . . . 31 E Discussion About Pre-Training Data Debiasing 32 F Additional Evaluations on Math and Code 33 G Evaluation Formats 34 3 1. Introduction In the past few years, Large Language Models pre-training corpus. Then, we collect 1.5M conversational sessions, which encompass various domains such as math, code, writing, reasoning, safety, and more, to perform Supervised Fine-Tuning (SFT) for DeepSeek-V2 datasets include CHID (Zheng et al., 2019) and CCPM (Li et al., 2021). Math datasets include GSM8K (Cobbe et al., 2021), MATH (Hendrycks et al., 2021), and CMath (Wei et al., 2023). Code datasets include

django_q.tasks import async_task, result # create the task async_task('math.copysign', 2, -2) # or with import and storing the id import math.copysign task_id = async_task(copysign, 2, -2) # get the result task_result = result(task_id, 200) # but in most cases you will want to use a hook: async_task('math.modf', 2.5, hook='hooks.print_result') # hooks.py (continues on next page) 18 Chapter 1. Features call: # Async options in a dict opts = {'hook': 'hooks.print_result', 'group': 'math', 'timeout': 30} async_task('math.modf', 2.5, q_options=opts) Please note that this will override any other option

django_q.tasks import async_task, result # create the task async_task('math.copysign', 2, -2) # or with import and storing the id import math.copysign task_id = async_task(copysign, 2, -2) # get the result task_result = result(task_id, 200) # but in most cases you will want to use a hook: async_task('math.modf', 2.5, hook='hooks.print_result') # hooks.py def print_result(task): print(task.result) async_task() call: # Async options in a dict opts = {'hook': 'hooks.print_result', 'group': 'math', 'timeout': 30} async_task('math.modf', 2.5, q_options=opts) Please note that this will override any other option

Multiplication // Mul is a GPU version of math.Mat[T].Mul method and it multiplies // two matrices m1 and m2 and returns the result. func Mul[T math.Type](m1, m2 math.Mat[T]) math.Mat[T] { // 1. Allocate GPU Pointer(&m1.Data[0]), uintptr(math.TypeSize[T] ()*len(m1.Data)), mtl.ResourceStorageModeShared) defer a.Release() b := device.MakeBuffer(unsafe.Pointer(&m2.Data[0]), uintptr(math.TypeSize[T] ()*len(m2 mtl.ResourceStorageModeShared) defer b.Release() out := device.MakeBuffer(nil, uintptr(math.TypeSize[T]()*m1.Row*m2.Col), mtl.ResourceStorageModeShared) defer out.Release() dp :=

from django_q.tasks import async, result # create the task async('math.copysign', 2, -2) # or with import and storing the id import math.copysign task_id = async(copysign, 2, -2) # get the result task_result for it task_result = result(task_id, 200) # but in most cases you will want to use a hook: async('math.modf', 2.5, hook='hooks.print_result') # hooks.py def print_result(task): print(task.result) async() call: # Async options in a dict opts = {'hook': 'hooks.print_result', 'group': 'math', 'timeout': 30} async('math.modf', 2.5, q_options=opts) Please note that this will override any other option keywords