Skip to content

Instantly share code, notes, and snippets.

pannous

Block or report user

Report or block pannous

Hide content and notifications from this user.

Learn more about blocking users

Contact Support about this user’s behavior.

Learn more about reporting abuse

Report abuse
View GitHub Profile
View keras_mnist.py
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
num_classes = 10
width, height = 28, 28
(x_train, y_train), (x_test, y_test) = mnist.load_data()
View keras_test.py
import numpy as np
from keras.models import Sequential
from keras.layers.core import Dense, Activation
xoder={
(0,0):0,
(0,1):1,
(1,0):1,
(1,1):0
}
@pannous
pannous / hello_sequence.py
Last active Mar 22, 2018
Simple "Hello World" for tensorflow seq2seq model
View hello_sequence.py
"""Sequence-to-sequence model with an attention mechanism."""
# see https://www.tensorflow.org/versions/r0.10/tutorials/seq2seq/index.html
# compare https://github.com/tflearn/tflearn/blob/master/examples/nlp/seq2seq_example.py
from __future__ import print_function
import numpy as np
import tensorflow as tf
vocab_size=256 # We are lazy, so we avoid fency mapping and just use one *class* per character/byte
target_vocab_size=vocab_size
learning_rate=0.1
@pannous
pannous / tensorflow-densenet.py
Last active Jul 30, 2017
Implementation of DenseNet: Densely Connected Convolutional Networks https://arxiv.org/abs/1608.06993 in tensorflow
View tensorflow-densenet.py
#!/usr/bin/python
from __future__ import print_function
import os
import numpy as np
import tensorflow as tf
from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
# mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
mnist = read_data_sets("/tmp/data/", one_hot=True)
@pannous
pannous / tensorflow_autoencoder.py
Created Feb 5, 2016
A simple MNIST classifer AND autoencoder in one
View tensorflow_autoencoder.py
"""A simple MNIST classifer AND autoencoder in one
"""
# Import data
import input_data
mnist = input_data.read_data_sets("/data/mnist/", one_hot=True)
import tensorflow as tf
sess = tf.InteractiveSession()
@pannous
pannous / tensorflow_xor_hello_world.py
Created Nov 11, 2015
A simple neural network learning the XOR function with the tensorflow framework
View tensorflow_xor_hello_world.py
#!/usr/bin/env PYTHONIOENCODING="utf-8" python
"""
A simple neural network learning the XOR function
"""
import tensorflow as tf
sess = tf.InteractiveSession()
# Desired input output mapping of XOR function:
x_ = [[0, 0], [0, 1], [1, 0], [1, 1]] # input
#labels=[0, 1, 1, 0] # output =>
You can’t perform that action at this time.