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util.py
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# Copyright 2014 Google Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
import cPickle
import os
from cStringIO import StringIO
from scipy.io import loadmat
import h5py
import numpy as np
class UnpickleError(Exception):
pass
GPU_LOCK_NO_SCRIPT = -2
GPU_LOCK_NO_LOCK = -1
def pickle(filename, data):
fo = filename
if type(filename) == str:
fo = open(filename, "w")
cPickle.dump(data, fo, protocol=cPickle.HIGHEST_PROTOCOL)
fo.close()
def unpickle(filename):
if not os.path.exists(filename):
raise UnpickleError("Path '%s' does not exist." % filename)
fo = open(filename, 'r')
z = StringIO()
file_size = os.fstat(fo.fileno()).st_size
# Read 1GB at a time to avoid overflow
while fo.tell() < file_size:
z.write(fo.read(1 << 30))
fo.close()
dict = cPickle.loads(z.getvalue())
z.close()
return dict
def is_intel_machine():
VENDOR_ID_REGEX = re.compile('^vendor_id\s+: (\S+)')
f = open('/proc/cpuinfo')
for line in f:
m = VENDOR_ID_REGEX.match(line)
if m:
f.close()
return m.group(1) == 'GenuineIntel'
f.close()
return False
# Returns the CPUs associated with a given GPU
def get_cpus_for_gpu(gpu):
# proc = subprocess.Popen(['nvidia-smi', '-q', '-i', str(gpu)], stdout=subprocess.PIPE)
# lines = proc.communicate()[0]
# lines = subprocess.check_output(['nvidia-smi', '-q', '-i', str(gpu)]).split(os.linesep)
with open('/proc/driver/nvidia/gpus/%d/information' % gpu) as f:
for line in f:
if line.startswith('Bus Location'):
bus_id = line.split(':', 1)[1].strip()
bus_id = bus_id[:7] + ':' + bus_id[8:]
ff = open('/sys/module/nvidia/drivers/pci:nvidia/%s/local_cpulist' % bus_id)
cpus_str = ff.readline()
ff.close()
cpus = [cpu for s in cpus_str.split(',') for cpu in
range(int(s.split('-')[0]), int(s.split('-')[1]) + 1)]
return cpus
return [-1]
def get_cpu():
if is_intel_machine():
return 'intel'
return 'amd'
# Copyright 2014 Google Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
import cPickle
import os
from cStringIO import StringIO
from scipy.io import loadmat
import h5py
import numpy as np
class UnpickleError(Exception):
pass
GPU_LOCK_NO_SCRIPT = -2
GPU_LOCK_NO_LOCK = -1
def pickle(filename, data):
fo = filename
if type(filename) == str:
fo = open(filename, "w")
cPickle.dump(data, fo, protocol=cPickle.HIGHEST_PROTOCOL)
fo.close()
def unpickle(filename):
if not os.path.exists(filename):
raise UnpickleError("Path '%s' does not exist." % filename)
fo = open(filename, 'r')
z = StringIO()
file_size = os.fstat(fo.fileno()).st_size
# Read 1GB at a time to avoid overflow
while fo.tell() < file_size:
z.write(fo.read(1 << 30))
fo.close()
dict = cPickle.loads(z.getvalue())
z.close()
return dict
def is_intel_machine():
VENDOR_ID_REGEX = re.compile('^vendor_id\s+: (\S+)')
f = open('/proc/cpuinfo')
for line in f:
m = VENDOR_ID_REGEX.match(line)
if m:
f.close()
return m.group(1) == 'GenuineIntel'
f.close()
return False
# Returns the CPUs associated with a given GPU
def get_cpus_for_gpu(gpu):
# proc = subprocess.Popen(['nvidia-smi', '-q', '-i', str(gpu)], stdout=subprocess.PIPE)
# lines = proc.communicate()[0]
# lines = subprocess.check_output(['nvidia-smi', '-q', '-i', str(gpu)]).split(os.linesep)
with open('/proc/driver/nvidia/gpus/%d/information' % gpu) as f:
for line in f:
if line.startswith('Bus Location'):
bus_id = line.split(':', 1)[1].strip()
bus_id = bus_id[:7] + ':' + bus_id[8:]
ff = open('/sys/module/nvidia/drivers/pci:nvidia/%s/local_cpulist' % bus_id)
cpus_str = ff.readline()
ff.close()
cpus = [cpu for s in cpus_str.split(',') for cpu in
range(int(s.split('-')[0]), int(s.split('-')[1]) + 1)]
return cpus
return [-1]
def get_cpu():
if is_intel_machine():
return 'intel'
return 'amd'
def is_windows_machine():
return os.name == 'nt'
def tryint(s):
try:
return int(s)
except:
return s
def alphanum_key(s):
return [tryint(c) for c in re.split('([0-9]+)', s)]
def my_load_mat(mat_path):
try:
return loadmat(mat_path)
except:
f = h5py.File(mat_path, 'r')
data = np.transpose(f['data'])
try:
labels = np.transpose(f['labels'])
return {'data': data, 'labels': labels}
except:
return {'data': data}
def load_list(list_path):
with open(list_path, 'r') as fs:
inputs = []
for line in fs:
inputs.append(line.strip())
return inputs
def is_windows_machine():
return os.name == 'nt'
def tryint(s):
try:
return int(s)
except:
return s
def alphanum_key(s):
return [tryint(c) for c in re.split('([0-9]+)', s)]
def alternate(list1, list2):
return [v for v in sum(zip_longest(list1, list2), ()) if v is not None]