提交 b0b78690 authored 作者: Frederic Bastien's avatar Frederic Bastien

white space fix.

上级 bc396826
...@@ -32,13 +32,13 @@ def execute(execute=True, verbose=True): ...@@ -32,13 +32,13 @@ def execute(execute=True, verbose=True):
print ' blas.ldflags=',theano.config.blas.ldflags print ' blas.ldflags=',theano.config.blas.ldflags
print ' compiledir=',theano.config.compiledir print ' compiledir=',theano.config.compiledir
print ' floatX=',theano.config.floatX print ' floatX=',theano.config.floatX
print print
print 'Numpy config:(used when the theano flags "blas.ldflags" is empty)' print 'Numpy config:(used when the theano flags "blas.ldflags" is empty)'
numpy.show_config(); numpy.show_config();
print 'Numpy dot module:',numpy.dot.__module__; print 'Numpy dot module:',numpy.dot.__module__;
print 'Numpy file location that was loaded:',numpy.__file__; print 'Numpy file location that was loaded:',numpy.__file__;
print 'Numpy version:',numpy.__version__ print 'Numpy version:',numpy.__version__
print print
if any( [x.op.__class__.__name__=='Gemm' for x in f.maker.env.toposort()]): if any( [x.op.__class__.__name__=='Gemm' for x in f.maker.env.toposort()]):
print 'Used the cpu' print 'Used the cpu'
elif any( [x.op.__class__.__name__=='GpuGemm' for x in f.maker.env.toposort()]): elif any( [x.op.__class__.__name__=='GpuGemm' for x in f.maker.env.toposort()]):
...@@ -66,7 +66,7 @@ def jobman_job(state, channel): ...@@ -66,7 +66,7 @@ def jobman_job(state, channel):
def test(): def test():
execute() execute()
if __name__ == "__main__": if __name__ == "__main__":
verbose = True verbose = True
...@@ -81,8 +81,8 @@ if __name__ == "__main__": ...@@ -81,8 +81,8 @@ if __name__ == "__main__":
if verbose: if verbose:
print """ print """
Some result that you can compare again. They where 10 executions of gemm in float64 with matrix of shape 2000x2000 on FC9. Some result that you can compare again. They where 10 executions of gemm in float64 with matrix of shape 2000x2000 on FC9.
Cpu tested: Xeon E5345, Xeon E5430, Xeon E5450, Core 2 E8500, Core i7 930(hyper-threads enabled) Cpu tested: Xeon E5345, Xeon E5430, Xeon E5450, Core 2 E8500, Core i7 930(hyper-threads enabled)
Lib tested: Lib tested:
...@@ -90,14 +90,14 @@ if __name__ == "__main__": ...@@ -90,14 +90,14 @@ if __name__ == "__main__":
* manually compiled numpy and ATLAS with 2 threads * manually compiled numpy and ATLAS with 2 threads
* goto with 1, 2, 4 and 8 threads. * goto with 1, 2, 4 and 8 threads.
Xeon Xeno Xeon Core2 i7 Xeon Xeno Xeon Core2 i7
lib/nb threads E5345 E5430 E5450 E8500 930 lib/nb threads E5345 E5430 E5450 E8500 930
numpy_FC9_atlas/1 39.2s 35.0s 30.7s 29.6s 21.5s numpy_FC9_atlas/1 39.2s 35.0s 30.7s 29.6s 21.5s
goto/1 18.7s 16.1s 14.2s 13.7s 16.1s goto/1 18.7s 16.1s 14.2s 13.7s 16.1s
numpy_MAN_atlas/2 12.0s 11.6s 10.2s 9.2s 9.0s numpy_MAN_atlas/2 12.0s 11.6s 10.2s 9.2s 9.0s
goto/2 9.5s 8.1s 7.1s 7.3s 8.1s goto/2 9.5s 8.1s 7.1s 7.3s 8.1s
goto/4 4.9s 4.4s 3.7s - 4.1s goto/4 4.9s 4.4s 3.7s - 4.1s
goto/8 2.7s 2.4s 2.0s - 4.1s goto/8 2.7s 2.4s 2.0s - 4.1s
Test time in float32 with cuda 3.0.14 Test time in float32 with cuda 3.0.14
(cuda version 3.2RC and up are supposed to have faster gemm on the GTX4?? card) (cuda version 3.2RC and up are supposed to have faster gemm on the GTX4?? card)
...@@ -109,9 +109,9 @@ if __name__ == "__main__": ...@@ -109,9 +109,9 @@ if __name__ == "__main__":
GTX285/3.0 0.40s GTX285/3.0 0.40s
GT220/3.2RC 5.15s GT220/3.2RC 5.15s
8500GT/3.0 10.68s 8500GT/3.0 10.68s
""" """
print print
print "We timed",iters,"executions of gemm with matrix of shapes",shapes print "We timed",iters,"executions of gemm with matrix of shapes",shapes
else: else:
print t print t
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