karpathy

"""
stable diffusion dreaming
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:

$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

to stitch together the images, e.g.:
$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

nigeljyng

class AttentionWithContext(Layer):
    """
    Attention operation, with a context/query vector, for temporal data.
    Supports Masking.
    Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf]
    "Hierarchical Attention Networks for Document Classification"
    by using a context vector to assist the attention
    # Input shape
        3D tensor with shape: `(samples, steps, features)`.
    # Output shape

kastnerkyle

# Stacked LSTMs
# Author: Kyle Kastner
# Based on script from /u/siblbombs
# License: BSD 3-Clause
import tensorflow as tf
from tensorflow.models.rnn import rnn
from tensorflow.models.rnn.rnn_cell import LSTMCell
import numpy as np
import time

rduplain

"Serve a Flask app on a sub-url during localhost development."

from flask import Flask


APPLICATION_ROOT = '/spam'


app = Flask(__name__)
app.config.from_object(__name__)