Leon Fedden fedden

Contributor License Agreement

The following terms are used throughout this agreement:

You - the person or legal entity including its affiliates asked to accept this agreement. An affiliate is any entity that controls or is controlled by the legal entity, or is under common control with it.
Project - is an umbrella term that refers to any and all open source projects owned by Leon Fedden related to machine learning and poker.
Contribution - any type of work that is submitted to a Project, including any modifications or additions to existing work.
Submitted - conveyed to a Project via a pull request, commit, issue, or any form of electronic, written, or verbal communication with Leon Fedden, contributors or maintainers.

	sudo apt-get update -y

	wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb
	wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb
	wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libcudnn7-dev_7.0.5.15-1+cuda9.0_amd64.deb
	wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libnccl2_2.1.4-1+cuda9.0_amd64.deb
	wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/libnccl-dev_2.1.4-1+cuda9.0_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu1604_9.0.176-1_amd64.deb
	sudo dpkg -i libcudnn7_7.0.5.15-1+cuda9.0_amd64.deb
	sudo dpkg -i libcudnn7-dev_7.0.5.15-1+cuda9.0_amd64.deb

	import dlib
	from PIL import Image
	from skimage import io
	from skimage.transform import resize


	def detect_faces(image):
	"""Get face border positions for all the faces in the image.

	Params:

	# Create the model.
	network = CharRNN(dataset.vocabulary_size,
	dataset.sequence_length,
	dropout_rate=0.5,
	batch_size=512,
	rnn_size=256,
	amount_layers=3,
	embedding_size=512,
	learning_rate=0.001,
	clip_norm=5.0)

	male_bios = ... # Downloaded bios as a list of strings.

	# Create the dataset.
	dataset = SequenceDataset(sequence_length=50)

	# Create token sequences from the bios.
	dataset.add_sequences_from_bios(male_bios)

	class SequenceDataset():

	def __init__(self, sequence_length):
	"""Initialises the dataset class that contains the sequences that will be trained on.

	Params:
	sequence_length: int - the length of a sequence that will be fed to the RNN.
	"""

	self.sequence_length = sequence_length