changed numpy imports to one common form

benchmark/autoencoder/aa_numpy.py

 #!/usr/bin/env python
 from __future__ import absolute_import, print_function, division
-import numpy as N
+import numpy as np
 import sys
 import time
 from six.moves import xrange
@@ -10,7 +10,7 @@ from six.moves import xrange
 neg, nout, nhid, niter = [int(a) for a in sys.argv[1:]]
 lr = 0.01
 
-rng = N.random.RandomState(342)
+rng = np.random.RandomState(342)
 
 w = rng.rand(nout, nhid)
 a = rng.randn(nhid) * 0.0
@@ -22,38 +22,38 @@ dot_time = 0.0
 t = time.time()
 for i in xrange(niter):
     tt = time.time()
-    d = N.dot(x, w)
+    d = np.dot(x, w)
     dot_time += time.time() - tt
 
-    hid = N.tanh(d + a)
+    hid = np.tanh(d + a)
 
     tt = time.time()
-    d = N.dot(hid, w.T)
+    d = np.dot(hid, w.T)
     dot_time += time.time() - tt
-    out = N.tanh(d + b)
+    out = np.tanh(d + b)
 
     g_out = out - x
-    err = 0.5 * N.sum(g_out**2)
+    err = 0.5 * np.sum(g_out**2)
 
     g_hidwt = g_out * (1.0 - out**2)
 
-    b -= lr * N.sum(g_hidwt, axis=0)
+    b -= lr * np.sum(g_hidwt, axis=0)
 
     tt = time.time()
-    g_hid = N.dot(g_hidwt, w)
+    g_hid = np.dot(g_hidwt, w)
     dot_time += time.time() - tt
 
     g_hidin = g_hid * (1.0 - hid**2)
 
     tt = time.time()
-    d = N.dot(g_hidwt.T, hid)
-    dd = N.dot(x.T, g_hidin)
+    d = np.dot(g_hidwt.T, hid)
+    dd = np.dot(x.T, g_hidin)
     dot_time += time.time() - tt
 
     gw = (d + dd)
     w -= lr * gw
 
-    a -= lr * N.sum(g_hidin, axis=0)
+    a -= lr * np.sum(g_hidin, axis=0)
 
 total_time = time.time() - t
 print('time: ',total_time, 'err: ', err)