Machine Learning AI machinelearning147

How to deploy a Python application as a zip file

Create a file __main__.py containing:

print "Hello world from Python"

Zip up the Python files (in this case just this one file) into app.zip by typing:

	"""Script to illustrate usage of tf.estimator.Estimator in TF v1.3"""
	import tensorflow as tf

	from tensorflow.examples.tutorials.mnist import input_data as mnist_data
	from tensorflow.contrib import slim
	from tensorflow.contrib.learn import ModeKeys
	from tensorflow.contrib.learn import learn_runner


	# Show debugging output

	import tensorflow as tf

	filenames = ["hdfs://10.152.104.73:8020/sogou/train_data/1_final.feature_transform"]

	dataset = tf.data.TextLineDataset(filenames)

	iterator = dataset.make_one_shot_iterator()

	next_batch = iterator.get_next()

	import numpy as np
	import tensorflow as tf

	__author__ = "Sangwoong Yoon"

	def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
	"""
	Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
	For supervised learning, feed training inputs to X and training labels to Y.
	For unsupervised learning, only feed training inputs to X, and feed None to Y.

	"""
	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)