def __enter__(self):
try:
mkl.domain_set_num_threads(self.n_threads, domain='fft')
except:
raise ValueError(
"Class argument {} result in invalid number of threads {}".
format(self.workers, self.n_threads))
def test_domain_set_num_threads_blas(self):
saved_blas_nt = mkl.domain_get_max_threads(domain='blas')
saved_fft_nt = mkl.domain_get_max_threads(domain='fft')
saved_vml_nt = mkl.domain_get_max_threads(domain='vml')
# set
blas_nt = int((3 + saved_blas_nt) / 4)
fft_nt = int((3 + 2 * saved_fft_nt) / 4)
vml_nt = int((3 + 3 * saved_vml_nt) / 4)
status = mkl.domain_set_num_threads(blas_nt, domain='blas')
assert (status == 'success')
status = mkl.domain_set_num_threads(fft_nt, domain='fft')
assert (status == 'success')
status = mkl.domain_set_num_threads(vml_nt, domain='vml')
assert (status == 'success')
# check
assert (mkl.domain_get_max_threads(domain='blas') == blas_nt)
assert (mkl.domain_get_max_threads(domain='fft') == fft_nt)
assert (mkl.domain_get_max_threads(domain='vml') == vml_nt)
# restore
status = mkl.domain_set_num_threads(saved_blas_nt, domain='blas')
assert (status == 'success')
status = mkl.domain_set_num_threads(saved_fft_nt, domain='fft')
assert (status == 'success')
status = mkl.domain_set_num_threads(saved_vml_nt, domain='vml')
assert (status == 'success')
if _mklinc:
_incs.extend(_mklinc)
_pyx.install(setup_args={'include_dirs': _incs}, language_level=2)
except Exception as e:
_w.warn("no mkl autocorrelation")
from . import ft # noqa
# cuda
_cuda = _nbcuda.is_available()
if _cuda:
try:
from . import cucor, cucorrad, cusimple
simple = cusimple
qcor = cucor
qcorrad = cucorrad
except Exception as e:
print(e)
_cuda = False
if not _cuda:
_w.warn("no cuda available")
simple = cpusimple
qcor = cpucor
qcorrad = cpucorrad
if _mkl is not None:
_mkl.domain_set_num_threads(_vml_threads,
'vml') # numexpr messes with vml thread number
def __exit__(self, *args):
# restore default
n_threads = _hardware_counts.get_max_threads_count()
mkl.domain_set_num_threads(n_threads, domain='fft')
"""
Face detection
Creating New Python 3.6 environment
conda create -n face python=3.6
"""
#import tomopy
import mkl
mkl.domain_set_num_threads(1, domain='fft') # Intel(R) MKL FFT functions to run sequentially
import cv2
import os
from time import sleep
import numpy as np
import argparse
from wide_resnet import WideResNet
from keras.utils.data_utils import get_file
import os, random
class FaceCV(object):
"""
Singleton class for face recongnition task
"""
CASE_PATH = ".\\pretrained_models\\haarcascade_frontalface_alt.xml"
WRN_WEIGHTS_PATH = ".\\pretrained_models\\weights.18-4.06.hdf5"
def __new__(cls, weight_file=None, depth=16, width=8, face_size=64):
if not hasattr(cls, 'instance'):
def test_domain_set_num_threads_all(self):
status = mkl.domain_set_num_threads(4, domain='all')
assert (status == 'success')
def test_domain_set_num_threads_pardiso(self):
status = mkl.domain_set_num_threads(4, domain='pardiso')
assert (status == 'success')
