Denys Melnychenko chelicerae

chelicerae / load_for_fit.py

Created January 8, 2019 09:35

	def load_from_dir(imgs_dir, height, width):
	img_names = os.listdir(imgs_dir)
	res = []
	filenames = []
	for img_name in img_names:
	if img_name == '.DS_Store': continue
	img_dir = imgs_dir + '/' + img_name

	x = image.load_img(img_dir, target_size=(height, width))
	x = image.img_to_array(x)

chelicerae / deep_MNIST_for_experts.py

Created September 9, 2018 15:17 — forked from saitodev/deep_MNIST_for_experts.py

Tensorflow tutorial "Deep MNIST for Experts"

	from __future__ import print_function

	from tensorflow.examples.tutorials.mnist import input_data
	mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

	import tensorflow as tf

	def weight_variable(shape):
	initial = tf.truncated_normal(shape, stddev=0.1)
	return tf.Variable(initial)

chelicerae / tf.py

Created September 6, 2018 11:05 — forked from koaning/tf.py

tensorflow layer example

	import tensorflow as tf
	import numpy as np
	import uuid

	x = tf.placeholder(shape=[None, 3], dtype=tf.float32)
	nn = tf.layers.dense(x, 3, activation=tf.nn.sigmoid)
	nn = tf.layers.dense(nn, 5, activation=tf.nn.sigmoid)
	encoded = tf.layers.dense(nn, 2, activation=tf.nn.sigmoid)
	nn = tf.layers.dense(encoded, 5, activation=tf.nn.sigmoid)
	nn = tf.layers.dense(nn, 3, activation=tf.nn.sigmoid)