butla

"""
MIT License

Copyright (c) 2017 Michał Bultrowicz

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is

toonetown

###########
# Checks if the given cask needs to be upgraded.
#
#!/bin/bash
set -o pipefail
source /etc/profile

if [ $# -eq 0 ]; then
    ARGS=($(brew cask list))
else

michelkana

from keras.layers import Conv2D, BatchNormalization, Input, GlobalAveragePooling2D, Dense
from keras.models import Model
from keras.layers.advanced_activations import LeakyReLU

# function for building the discriminator layers
def build_discriminator(start_filters, spatial_dim, filter_size):
    
    # function for building a CNN block for downsampling the image
    def add_discriminator_block(x, filters, filter_size):
      x = Conv2D(filters, filter_size, padding='same')(x)

jacksmith15

"""A set of helpers for reversing urls, similar to Django ``reverse``.

Usage:

.. code:: python

    @router.get("/class/{class_id}")
    async def get_class(request: Request, class_id: int = Path(...)):
        student_route = get_route(request.app, "list_students")
        class_students_url = URLFactory(student_route).get_path(class_id=class_id)

Linerre

• TL;DR
• Zsh initializations
  • Zsh way of $PATH
  • the special macOS
• /usr/libexec/path_helper
  • What is it?
  • What does it do?
  • What does it break?
  • Situation explained

• The .*shrc file

SMUsamaShah

Browser Based

1. Web Wormhole https://webwormhole.io/ https://github.com/saljam/webwormhole
2. ToffeeShare https://toffeeshare.com/
3. FilePizza https://file.pizza/
4. ShareDrop sharedrop.io https://github.com/szimek/sharedrop (SOLD, not recommended, use one of the forks)
   1. A clone SnapDrop snapdrop.net https://github.com/RobinLinus/snapdrop (SOLD, not recommended, use one of the forks)
      1. A fork PairDrop https://pairdrop.net/ https://github.com/schlagmichdoch/pairdrop
5. Instant.io https://instant.io/
6. FileTC https://file.tc/

folkengine

• Open linux env

To start with I am using Multipass.

Install Host Packages

https://docs.yoctoproject.org/brief-yoctoprojectqs/index.html#build-host-packages

$> sudo apt install gawk wget git diffstat unzip texinfo gcc build-essential chrpath socat cpio python3 python3-pip python3-pexpect xz-utils debianutils iputils-ping python3-git python3-jinja2 python3-sphinx libegl1-mesa libsdl1.2-dev python3-subunit mesa-common-dev zstd liblz4-tool file locales libacl1

dannguyen

Extracting financial disclosure reports and police blotter narratives using OpenAI's Structured Output

tl;dr this demo shows how to call OpenAI's gpt-4o-mini model, provide it with URL of a screenshot of a document, and extract data that follows a schema you define. The results are pretty solid even with little effort in defining the data — and no effort doing data prep. OpenAI's API could be a cost-efficient tool for large scale data gathering projects involving public documents.

OpenAI announced Structured Outputs for its API, a feature that allows users to specify the fields and schema of extracted data, and guarantees that the JSON output will follow that specification.

For example, given a Congressional financial disclosure report, with assets defined in a table like this: