#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('pylab', 'inline')


# In[2]:


import sys
sys.version
sys.path += ["/usr/local/lib/python2.7/dist-packages"]


# In[3]:


import clstm
import numpy


# In[4]:


inputs = clstm.Sequence()
outputs = clstm.Sequence()
targets = clstm.Sequence()


# In[5]:


a = array(randn(100,11,7),'f')
clstm.sequence_of_array(inputs,a)
print inputs.size(), inputs.depth(), inputs.batchsize()
#clstm.array_of_sequence(b,inputs)
#print b.shape


# In[6]:


b = numpy.empty_like(a)
clstm.array_of_sequence(b,inputs)


# In[7]:


b = numpy.empty((1,1,1),'f')
clstm.array_of_sequence(b,inputs)
b.shape


# In[8]:


net = clstm.make_net_init("bidi","ninput=11:nhidden=20:noutput=13")
net


# In[9]:


print clstm.network_info(net)


# In[10]:


temp = clstm.make_layer("LSTM")
temp


# In[11]:


clstm.sequence_of_array(net.inputs, a)
print net.inputs.size(), net.inputs.depth(), net.inputs.batchsize()


# In[12]:


print net.outputs.size(), net.outputs.depth(), net.outputs.batchsize()
net.forward()
print net.outputs.size(), net.outputs.depth(), net.outputs.batchsize()


# In[13]:


deltas = zeros(0,'f')
clstm.array_of_sequence(deltas,net.outputs)
deltas *= 0
clstm.sequence_of_array(net.d_outputs,deltas)


# In[14]:


print net.d_inputs.size(), net.d_inputs.depth(), net.d_inputs.batchsize()
net.backward()
print net.d_inputs.size(), net.d_inputs.depth(), net.d_inputs.batchsize()


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