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kirk86 / gist:915577ec7b1bb2f5f9ed1104883ee1b3
Created March 22, 2022 11:22 — forked from pcmoritz/gist:4b0e1be7f2dfcc4e51e2ace50426f67d
Powerpoint create slides for animations while retaining slide numbers
Option Explicit
Sub AddElements()
Dim shp As Shape
Dim i As Integer, n As Integer
n = ActivePresentation.Slides.Count
For i = 1 To n
Dim s As Slide
Set s = ActivePresentation.Slides(i)
@kirk86
kirk86 / akmtdfgen.py
Created August 26, 2017 06:24 — forked from timehaven/akmtdfgen.py
kmtdfgen: Keras multithreaded dataframe generator
"""akmtdfgen: A Keras multithreaded dataframe generator.
Works with Python 2.7 and Keras 2.x.
For Python 3.x, need to fiddle with the threadsafe generator code.
Test the generator_from_df() functions by running this file:
python akmtdfgen.py
"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code
class LSTM:
@staticmethod
def init(input_size, hidden_size, fancy_forget_bias_init = 3):
@kirk86
kirk86 / min-char-rnn.py
Created August 25, 2016 11:53 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
@kirk86
kirk86 / adam.py
Created June 27, 2016 18:44 — forked from skaae/adam.py
def adam(loss, all_params, learning_rate=0.0002, beta1=0.1, beta2=0.001,
epsilon=1e-8, gamma=1-1e-7):
"""
ADAM update rules
Default values are taken from [Kingma2014]
References:
[Kingma2014] Kingma, Diederik, and Jimmy Ba.
"Adam: A Method for Stochastic Optimization."
arXiv preprint arXiv:1412.6980 (2014).
@kirk86
kirk86 / adam.py
Created June 27, 2016 18:43 — forked from skaae/adam.py
def adam(loss, all_params, learning_rate=0.001, b1=0.9, b2=0.999, e=1e-8,
gamma=1-1e-8):
"""
ADAM update rules
Default values are taken from [Kingma2014]
References:
[Kingma2014] Kingma, Diederik, and Jimmy Ba.
"Adam: A Method for Stochastic Optimization."
arXiv preprint arXiv:1412.6980 (2014).
@kirk86
kirk86 / adam.py
Created June 27, 2016 18:29 — forked from Newmu/adam.py
Adam Optimizer
"""
The MIT License (MIT)
Copyright (c) 2015 Alec Radford
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
@kirk86
kirk86 / conv_deconv_variational_autoencoder.py
Created June 27, 2016 18:29 — forked from Newmu/conv_deconv_variational_autoencoder.py
Prototype code of conv/deconv variational autoencoder, probably not runable, lots of inter-dependencies with local codebase =/
import theano
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
from theano.tensor.signal.downsample import max_pool_2d
from theano.tensor.extra_ops import repeat
from theano.sandbox.cuda.dnn import dnn_conv
from time import time
import numpy as np
from matplotlib import pyplot as plt
@kirk86
kirk86 / simple_gan.py
Created June 27, 2016 18:28 — forked from Newmu/simple_gan.py
Simple Generative Adversarial Network Demo
import os
import numpy as np
from matplotlib import pyplot as plt
from time import time
from foxhound import activations
from foxhound import updates
from foxhound import inits
from foxhound.theano_utils import floatX, sharedX
import sys
sys.path.append('..')
import os
import json
from time import time
import numpy as np
from tqdm import tqdm
from matplotlib import pyplot as plt
from sklearn.externals import joblib