added test_scan test_speed_batchrnn for Ilya

theano/scan_module/tests/test_scan.py

@@ -2569,6 +2569,67 @@ def test_speed_rnn():
         print 'theano (updates, cvm)', t3 - t2
         print shared_r.get_value()
 
+def test_speed_batchrnn():
+
+    #
+    # This function prints out the speed of recurrent neural network
+    # calculations implemented in various ways.  In DebugMode this will test the
+    # correctness of the optimizations applied, but generally
+    # correctness-testing is not the goal of this test.
+    #
+    # To be honest, it isn't really a unit test so much as a tool for testing
+    # approaches to scan.
+    #
+    # The computation being tested here is a repeated tanh of a matrix-vector
+    # multiplication - the heart of an ESN or RNN.
+    #
+    import theano.scalar.sharedvar
+    print """Warning: the updates version runs slower than python because by
+    default the blas optimizations don't replace dot with dot22.  Why is that?"""
+
+    L = 100
+    B = 50
+    N = 400
+
+    numpy.random.seed(2523452)
+
+    r = numpy.arange(B*L*N).astype(theano.config.floatX).reshape(L,B,N)
+
+    w = numpy.random.randn(N,N).astype(theano.config.floatX)
+
+    t0 = time.time()
+    for i in xrange(1,L):
+        r[i] = numpy.tanh(numpy.dot(r[i-1], w))
+    t1 = time.time()
+    print 'python', t1 - t0
+
+    if 1:
+        r = numpy.arange(B*L*N).astype(theano.config.floatX).reshape(L,B,N)
+        s_w = theano.shared(w)
+        shared_r = theano.shared(r)
+        s_i = theano.scalar.sharedvar.shared(1)
+        s_rinc = tensor.inc_subtensor(
+                shared_r[s_i],
+                theano.tensor.tanh(
+                    theano.tensor.dot(
+                        shared_r[s_i-1],
+                        w)),
+                tolerate_inplace_aliasing=True)
+        f = theano.function([], [],
+                updates={
+                    s_i: s_i+1,
+                    shared_r: s_rinc,
+                    },
+                mode=theano.Mode(linker='cvm'))
+        theano.printing.debugprint(f )
+        f_fn = f.fn
+        print f_fn
+        t2 = time.time()
+        f_fn(n_calls=L-2)
+        f() #999 to update the profiling timers
+        t3 = time.time()
+        print 'theano (updates, cvm)', t3 - t2
+
 if __name__ == '__main__':
     #'''
     print ' Use nosetests to run these tests '