@@ -72,7 +72,7 @@ def speed():
7272 """
7373
7474 algo = ['logistic_sgd' , 'logistic_cg' , 'mlp' , 'convolutional_mlp' ,
75- 'dA' , 'SdA' , 'DBN' , 'rbm' , 'rnnrbm' , 'rnnslu' ]
75+ 'dA' , 'SdA' , 'DBN' , 'rbm' , 'rnnrbm' , 'rnnslu' , 'lstm' ]
7676 to_exec = [True ] * len (algo )
7777# to_exec = [False] * len(algo)
7878# to_exec[-1] = True
@@ -87,9 +87,9 @@ def speed():
8787 # 7.1-2 (python 2.7.2, mkl unknow). BLAS with only 1 thread.
8888
8989 expected_times_64 = numpy .asarray ([9.8 , 22.5 , 76.1 , 73.7 , 116.4 ,
90- 346.9 , 381.9 , 558.1 , 186.3 , 50.8 ])
90+ 346.9 , 381.9 , 558.1 , 186.3 , 50.8 , 113.6 ])
9191 expected_times_32 = numpy .asarray ([8.1 , 17.9 , 42.5 , 66.5 , 71 ,
92- 191.2 , 226.8 , 432.8 , 176.2 , 36.9 ])
92+ 191.2 , 226.8 , 432.8 , 176.2 , 36.9 , 78.0 ])
9393
9494 # Number with just 1 decimal are new value that are faster with
9595 # the Theano version 0.5rc2 Other number are older. They are not
@@ -110,7 +110,7 @@ def speed():
110110
111111 expected_times_gpu = numpy .asarray ([3.0 , 7.55523491 , 18.99226785 ,
112112 5.8 , 21.5 ,
113- 11.8 , 47.9 , 290.1 , 255.4 , 72.4 ])
113+ 11.8 , 47.9 , 290.1 , 255.4 , 72.4 , 17.0 ])
114114 expected_times_64 = [s for idx , s in enumerate (expected_times_64 )
115115 if to_exec [idx ]]
116116 expected_times_32 = [s for idx , s in enumerate (expected_times_32 )
@@ -167,6 +167,8 @@ def do_tests():
167167 # 60 is recommended
168168 'savemodel' : False }
169169 time_test (m , l , 9 , rnnslu .main , param = s )
170+ time_test (m , l , 10 , lstm .train_lstm , max_epochs = 1 , test_size = 1000 ,
171+ saveto = '' )
170172 return numpy .asarray (l )
171173
172174 #test in float64 in FAST_RUN mode on the cpu
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