noparade noparade

## mnist_tfdata.py
"""An example of how to use tf.Dataset in Keras Model"""
import tensorflow as tf   # only work from tensorflow==1.9.0-rc1 and after

_EPOCHS      = 5
_NUM_CLASSES = 10
_BATCH_SIZE  = 128

def training_pipeline():
  # #############
  # Load Dataset

## classifier_from_little_data_script_2.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
	"""An example of how to use tf.Dataset in Keras Model"""
	import tensorflow as tf # only work from tensorflow==1.9.0-rc1 and after

	_EPOCHS = 5
	_NUM_CLASSES = 10
	_BATCH_SIZE = 128

	def training_pipeline():
	# #############
	# Load Dataset
	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats