DNC Tensorflow example

gistfile1.txt

# coding: utf-8

# # DNC Tensorflow example
# running deepminds dnc implementation via "tf.nn.dynamic_rnn"
# 
# needed dependencies (python3.6):
# https://github.com/deepmind/dnc
# numpy,
# tensorflow,
# sonnet
# 
# place this file in the folder of dnc.py
# 
# results are random
# 
# MIT licensed (if it matters???)

# In[1]:


import dnc
import tensorflow as tf
import numpy as np
import random


# In[2]:


access_config = {
      "memory_size": 10,
      "word_size": 4,
      "num_reads": 1,
      "num_writes": 1,
  }
controller_config = {
      "hidden_size": 2,
  }
dataset_target_size = 10


# In[3]:


xor = [[0,0,0],
       [0,1,1],
       [1,0,1],
       [1,1,0]]
xorset = random.choices(xor,k=10)
xorset = np.array(xorset,dtype='float64').reshape(1,10,3)

dataset = xorset[:,:,0:2]
print("dataset=\n" + str(dataset))

labels = xorset[:,:,2]
print("labels=\n" + str(labels))

batch_size = 1


# In[4]:


tf.reset_default_graph()

dncs = dnc.DNC(access_config,controller_config, dataset_target_size)

outputs, last_states = tf.nn.dynamic_rnn(
    cell=dncs,
    initial_state=dncs.initial_state(batch_size,dtype='float64'),
    inputs=dataset)


# In[5]:


result = tf.contrib.learn.run_n(
    {"outputs": outputs, "last_states": last_states},
    n=1,
    feed_dict=None)

print(result[0]["outputs"])