From ecba9ede19d1ae75004f1bca07dd8c2314696210 Mon Sep 17 00:00:00 2001
From: Denis Arrivault <denis.arrivault@lif.univ-mrs.fr>
Date: Thu, 1 Mar 2018 14:17:25 +0100
Subject: [PATCH] Svd tests for gpu
---
examples/performances_calculation.py | 9 ++--
examples/svd_tests.py | 73 ++++++++++++++++++++++++++++
2 files changed, 77 insertions(+), 5 deletions(-)
create mode 100644 examples/svd_tests.py
diff --git a/examples/performances_calculation.py b/examples/performances_calculation.py
index 0c2987e..771fe0b 100644
--- a/examples/performances_calculation.py
+++ b/examples/performances_calculation.py
@@ -5,14 +5,13 @@ Created on 20 févr. 2018
@author: arrivault
'''
-import sys
from timeit import default_timer as timer
from splearn import Spectral
from splearn.tests.datasets.get_dataset_path import get_dataset_path
from splearn.datasets.base import load_data_sample
-def launch(X, version='classic', partial=True, sparse=True, smooth_method='none'):
+def launch_fit(X, version='classic', partial=True, sparse=True, smooth_method='none'):
param = "****** {:s} - partial = {:b} - sparse = {:b}, {:s} *****".format(version, partial, sparse, smooth_method)
print(param)
@@ -33,7 +32,7 @@ def launch(X, version='classic', partial=True, sparse=True, smooth_method='none'
# else:
# print("The result is different", file=sys.stderr)
-def test():
+def test_fit():
adr = get_dataset_path("3.pautomac_light.train")
data = load_data_sample(adr=adr)
X = data.data
@@ -43,7 +42,7 @@ def test():
# for partial in param['partial']:
for sparse in param['sparse']:
for smooth_method in param['smooth_method']:
- launch(X, version=version, partial=True, sparse=sparse, smooth_method=smooth_method)
+ launch_fit(X, version=version, partial=True, sparse=sparse, smooth_method=smooth_method)
if __name__ == '__main__':
- test()
+ test_fit()
diff --git a/examples/svd_tests.py b/examples/svd_tests.py
new file mode 100644
index 0000000..6fca06d
--- /dev/null
+++ b/examples/svd_tests.py
@@ -0,0 +1,73 @@
+# -*- coding: utf-8 -*-
+
+'''
+Created on 20 févr. 2018
+
+@author: arrivault
+'''
+import sys
+from timeit import default_timer as timer
+import numpy as np
+
+def test_svd():
+ d = 100
+ A = np.asarray(np.random.randint(1, 10,(d, d)), dtype=np.float64)
+
+ # scipy
+ print("\n****************** Scipy")
+ from scipy import linalg as sc_linalg
+ start = timer()
+ u_sc, s_sc, v_sc = sc_linalg.svd(A)
+ duration = timer() - start
+ print("SVD scipy : " + str(duration))
+ print(s_sc)
+ print(type(s_sc))
+
+ # scikit-cuda
+ print("\n****************** scikit-cuda")
+ import pycuda.autoinit
+ import pycuda.gpuarray as gpuarray
+ #import ctypes
+ #ctypes.CDLL('libgomp.so.1', mode=ctypes.RTLD_GLOBAL)
+ from skcuda import linalg as sk_linalg
+ start = timer()
+ sk_linalg.init()
+ A_sk = gpuarray.to_gpu(A)
+ u_sk, s_sk, vh_sk = sk_linalg.svd(A_sk, jobu='S', jobvt='S', lib='cusolver')
+ u_sk, s_sk, v_sk = u_sk.get_async(), s_sk.get_async(), vh_sk.get_async()
+ duration = timer() - start
+ print("SVD skcuda : " + str(duration))
+ print(s_sk)
+ print(type(s_sk))
+
+ # tensorflow
+ print("\n****************** tensorflow")
+ import tensorflow as tf
+ from tensorflow import linalg as tf_linalg
+ start = timer()
+ with tf.Session(config=tf.ConfigProto(log_device_placement=True)) as sess:
+ s_tf, u_tf, v_tf = tf_linalg.svd(A)
+ s_tf, u_tf, v_tf = s_tf.eval(), u_tf.eval(), v_tf.eval()
+ duration = timer() - start
+ print("SVD tensorflow : " + str(duration))
+ print(s_tf)
+ print(type(s_tf))
+
+ # Theano
+ print("\n****************** theano")
+ import theano.tensor as T
+ from theano import function
+ import theano.tensor.nlinalg as th_linalg
+ x = T.dmatrix('x')
+ u, s, v = th_linalg.svd(x)
+ f = function([x], (u, s, v))
+ start = timer()
+ u_th, s_th, v_th = f(A)
+ duration = timer() - start
+ print("SVD theano : " + str(duration))
+ print(s_th)
+ print(type(s_th))
+
+
+if __name__ == '__main__':
+ test_svd()
--
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