Tensorflow SOM implementation

tf_som_classifier.py

# coding: utf-8

# In[1]:


from tensorflow.examples.tutorials.mnist import input_data


# In[2]:


mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)


# In[3]:


import tensorflow as tf


# In[9]:


x = tf.placeholder(tf.float32, [1,784])


# In[10]:


weights = tf.Variable(tf.zeros([10,784]))


# In[16]:


closest_weight_index = tf.argmin(tf.reduce_mean(tf.squared_difference(x,weights),axis=1))


# In[12]:


learning_rate = tf.constant(0.5)


# In[20]:


weights = tf.concat(axis=0, values=[weights[:closest_weight_index], weights[closest_weight_index] + learning_rate*(x-weights[closest_weight_index]), weights[closest_weight_index+1:]])

Work in progress