gaspersic/triton
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Input-dependent models now activated for all the operations

Browse Source
This commit is contained in:
Philippe Tillet
2014-10-04 08:58:11 +02:00
parent 044419f9f0
commit fc8b450a7c
5 changed files with 89 additions and 90 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
autotune/python/model.py
View File

@@ -8,7 +8,7 @@ from pybrain.supervised.trainers import BackpropTrainer
from pybrain.structure import LinearLayer, TanhLayer, SigmoidLayer, SoftmaxLayer, FeedForwardNetwork, BiasUnit
from pybrain.tools.neuralnets import NNregression, Trainer
def train_model(X, Y, profiles):
def train_model(X, Y, profiles, metric):
#Preprocessing
Xmean = np.mean(X, axis=0)
Xstd = np.std(X, axis=0)
@@ -43,7 +43,7 @@ def train_model(X, Y, profiles):
np.set_printoptions(precision=2)
print("-----------------")
print("Average testing speedup : %f (Optimal : %f)"%(sp.stats.gmean(speedups), sp.stats.gmean(optspeedups)))
print("Average GFLOP/s : %f (Default %f, Optimal %f)"%(np.mean(np.multiply(GFlops,speedups)), np.mean(GFlops), np.mean(np.multiply(GFlops,optspeedups))))
print("Minimum speedup is %f wrt %i GFlops"%(np.min(speedups), GFlops[np.argmin(speedups)]))
print("Maximum speedup is %f wrt %i GFlops for %s"%(np.max(speedups), GFlops[np.argmax(speedups)], X[np.argmax(speedups)]*Xstd+Xmean))
print("Average %s: %f (Default %f, Optimal %f)"%(metric, np.mean(np.multiply(GFlops,speedups)), np.mean(GFlops), np.mean(np.multiply(GFlops,optspeedups))))
print("Minimum speedup is %f wrt %i %s"%(np.min(speedups), GFlops[np.argmin(speedups)], metric))
print("Maximum speedup is %f wrt %i %s"%(np.max(speedups), GFlops[np.argmax(speedups)], metric))
print("--------")