SunMarc

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

nmwsharp

Pretty print tables summarizing properties of tensor arrays in numpy, pytorch, jax, etc.

Now on pip! `pip install arrgh` https://github.com/nmwsharp/arrgh

kinoc

#  So now you want to finetune that GPT-J-6B on a 3090/TITAN GPU ... okay 
#  More exploratory coding. It uses the Huggingface model port, deepspeed and reads all text/md files from a target directory
#  It is a fragment of a larger system with remote editing, but that's another story
#  This is the raw, training tester. Items to look out for:
#  - uses DeepSpeed and has a DS config
#  - to save space uses SGD instead of ADAM
#  - uses gradient checkpointing
#  - freezes 25% of the layers to fit

# Assumes you can already run https://gist.github.com/kinoc/2d636a68876cd3de7b6e9c9452b61089

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

gravitylow

If you are getting this in gdb on macOS while trying to run a program:

Unable to find Mach task port for process-id 57573: (os/kern) failure (0x5).
 (please check gdb is codesigned - see taskgated(8))

1. Open Keychain Access
2. In menu, open Keychain Access > Certificate Assistant > Create a certificate
3. Give it a name (e.g. gdbc)

peterroelants

"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3"""
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data as mnist_data
from tensorflow.contrib import slim
from tensorflow.contrib.learn import ModeKeys
from tensorflow.contrib.learn import learn_runner


# Show debugging output

0x4D31

Transforming Code into Beautiful, Idiomatic Python

Notes from Raymond Hettinger's talk at pycon US 2013 video, slides.

The code examples and direct quotes are all from Raymond's talk. I've reproduced them here for my own edification and the hopes that others will find them as handy as I have!

Looping over a range of numbers

for i in [0, 1, 2, 3, 4, 5]:

Tushar-N

import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

seqs = ['gigantic_string','tiny_str','medium_str']

# make <pad> idx 0
vocab = ['<pad>'] + sorted(set(''.join(seqs)))

# make model

ilblackdragon

import logging

import numpy as np
import tensorflow as tf
from tensorflow.contrib import layers


GO_TOKEN = 0
END_TOKEN = 1
UNK_TOKEN = 2

rtqichen

## Weight norm is now added to pytorch as a pre-hook, so use that instead :)

import torch
import torch.nn as nn
from torch.nn import Parameter
from functools import wraps

class WeightNorm(nn.Module):
    append_g = '_g'
    append_v = '_v'