awni

"""
A minimal, fast example generating text with Llama 3.1 in MLX.

To run, install the requirements:

    pip install -U mlx transformers fire

Then generate text with:

    python l3min.py "How tall is K2?"

kratsg

kratsg

import pyhf
pyhf.set_backend('pytorch', 'minuit')

nSig = 4.166929245
errSig = 4.166929245
nBkg = 0.11
errBkgUp = 0.20
errBkgDown = 0.11

model_json = {

ebarsoum

import numpy as np
from pynvml.smi import nvidia_smi
import pycuda.gpuarray as ga
import pycuda.driver as cuda

nvsmi = nvidia_smi.getInstance()

def getGPUMemoryUsage(gpu_index=0):
    return nvsmi.DeviceQuery("memory.used")["gpu"][gpu_index]['fb_memory_usage']['used']

johnhw

### JHW 2018
import numpy as np
import umap



# This code from the excellent module at:
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module
    
import random

HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

blepfo

TensorFlow Best Practices as of Q1 2018

By Adam Anderson

adam.b.anderson.96@gmail.com

Preface

This write-up assumes you have an general understanding of the TensorFlow programming model, but maybe you haven't kept up to date with the latest library features/standard practices.

LucaCappelletti94

Firing up LaTex on macOS 🔥

As I'm writing this small tutorial, I assume you've read my previous one about setting up macOS, so if for any tool I'll use without explanation, look to that other article.

MacTex

The full version IS NOT MANDATORY, as in the tutorial that follows I installed the smaller version of MacTeX and proceded installing every needed dependency. Installing the complete package is about ~3.5GB of download and ~5GB on disk, the smaller one is just about 80MBs.

Click here to download the complete version or here to download the smaller version.

Gnuplot

LucaCappelletti94

MacOs quick setup 🚀

Getting everything ready

1 - Xcode/Ruby/Command line tools

You need to have Xcode installed to proceed.

xcode-select --install
sudo xcodebuild -license accept

2 - Brew

damienpontifex

import argparse
import psutil
import tensorflow as tf
from typing import Dict, Any, Callable, Tuple

## Data Input Function
def data_input_fn(data_param,
                  batch_size:int=None,
                  shuffle=False) -> Callable[[], Tuple]:
    """Return the input function to get the test data.