Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/fast_mnist
Shay Ben-Sasson shaybensasson
shaybensasson
/ mnist_nlp_seed.py
Last active
June 14, 2017 08:47
trying keras to be random seeded (with theano and/or tf)
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| ''' | |
| trying keras to be random seeded | |
| Switch backends by changin ~/.keras/keras.json: | |
| Theano: https://drive.google.com/open?id=0B-FcStylmYuVU1E5S25QX2JXcGs | |
| TensorFlow: https://drive.google.com/open?id=0B-FcStylmYuVNnpfZERoeUo0QnM | |
| Keras Backend: | |
| *Theano (1 epoch, GPU): | |
| Test loss: 0.111780489241 |
shaybensasson
/ Versions of everything.ipynb
Last active
September 15, 2018 17:50
Versions of everything - to compare two environments
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shaybensasson
/ PyCharm Tips and Tricks.ipynb
Last active
September 6, 2018 08:32
PyCharm Tips and Tricks.ipynb
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y0ast
/ Faster MNIST.md
Last active
May 30, 2021 21:01
y0ast
/ train_cifar.py
Last active
May 16, 2022 08:40
Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/minimal_cifar
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| # Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/minimal_cifar |
dariosky
/ dropbox_wise_ignore.py
Last active
February 17, 2023 19:30
A Python script to be run in a Dropbox folder - so it exclude all the node_modules and __pycache__ folders - we want them locally but not in the cloud
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| #!/usr/bin/env python3 | |
| import argparse | |
| import os | |
| import shutil | |
| from xattr import xattr | |
| top_folder = "." | |
| CACHE_FOLDERS = {"__pycache__", ".pytest_cache", ".cache"} |
A "Hello, world!" Prefect flow running on an ephemeral Dask Cluster on Kubernetes.
The Prefect Core docs suggest running flows on a Dask cluster via Dask Distributed and an article from the MET Office Informatics Lab demonstrates running an adaptive Dask cluster on k8s. This example is inspired by those sources, as well as the respective docs for the technologies used.
sujee
/ cnn-mnist-1-train-gpu-minimal.py
Last active
April 2, 2023 13:20
CNN model for mnist prediciton -- tweaked for Tensorflow2 GPU edition
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| #!/usr/bin/env python | |
| ## This CNN network to identify MNIST dataset | |
| import time | |
| import random | |
| import numpy as np | |
| from pprint import pprint | |
| import os, sys |