{ "editor.insertSpaces": true, "editor.fontFamily": "JetBrains Mono, Cascadia Code PL, Droid Sans Mono", "editor.fontLigatures": true, "editor.minimap.showSlider": "always", "editor.multiCursorModifier": "ctrlCmd", "editor.renderControlCharacters": true, "editor.renderIndentGuides": true, "editor.renderWhitespace": "boundary", "editor.rulers": [100],
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import time | |
counter = 0 | |
while counter < 10: | |
print(f'\r{counter}', end='') | |
time.sleep(1.0) | |
counter += 1 | |
print("Done.") |
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<!DOCTYPE HTML><html lang="en"><head><title>Sampler1</title><meta charset="utf-8" /><meta name="viewport" content="width=device-width,initial-scale=1,user-scalable=no" /><meta name="description" content="A sampler1" /><meta property="og:site_name" content="Sampler1" /><meta property="og:title" content="Sampler1" /><meta property="og:type" content="website" /><meta property="og:description" content="A sampler1" /><meta property="og:image" content="https://asampler1.carrd.co/assets/images/card.jpg?v82476884724951" /><meta property="og:image:type" content="image/jpeg" /><meta property="og:image:width" content="1280" /><meta property="og:image:height" content="800" /><meta property="og:url" content="https://asampler1.carrd.co" /><meta property="twitter:card" content="summary_large_image" /><style>html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,img,ins,kbd,q,s,samp,small,strike,strong,sub,sup,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,f |
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list_column_a = [1, 11, 22, 33] | |
list_column_b = ['one', 'eleven', 'twenty two', 'thirty three'] | |
list_column_c = ['exciting', 'blah', 'somewhat ok', 'fishy'] | |
for idx, a in enumerate(list_column_a): | |
print(f"{a}, {list_column_b[idx]}, {list_column_c[idx]}") | |
for a, b, c in zip(list_column_a, list_column_b, list_column_c): | |
print(f"{a}, {b}, {c}") |
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from tensorflow import keras | |
import numpy as np | |
from IPython import embed | |
INPUT_SHAPE = (3, 3, 1) | |
CONV_SIZE = 3 | |
model_name = 'test_model' | |
def create_model(): |
TFRecord files using tf.data The tf.data module also provides tools for reading and writing data in TensorFlow.
The easiest way to get the data into a dataset is to use the from_tensor_slices method.
Applied to an array, it returns a dataset of scalars:
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/* | |
NOTE: This code had a bug which I edited in the browser to fix. UNTESTED. | |
Code to set up 8 pins for output to an LCD display. | |
This code sets up the 8 pins and turns on Port C, 6 | |
#NEWBIEHACK | |
RL 03-01-2022 |
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# Source | |
Original source no longer exists but was apparently: | |
http://www.efg2.com/Lab/Library/ImageProcessing/DHALF.TXT, | |
based on a stackoverflow discussion: | |
https://stackoverflow.com/a/9150427/2184122 | |
There are several authors. I am capturing the file because I think it is of great value. However, I am happy to remove it if requested. | |
The authors are: Lee Daniel Crocker, Paul Boulay, and Mike Morra | |
The original file is: https://gist.github.com/robertlugg/f0b618587c2981b744716999573c5b65
DHALF.TXT June 20, 1991
Original name: DITHER.TXT Original date: January 2, 1989
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