def get_backup_dir_list(monitoring_dir, ELAPSED_TIME):
backup_dir_list = []
now = int(time.time())
for f in fs.find('*', path=monitoring_dir):
last_accessed = fs.stat(f).st_atime
diff = now - last_accessed
if diff > ELAPSED_TIME:
if not fs.dirname(f) in backup_dir_list:
backup_dir_list.append(fs.dirname(f))
return list(set(backup_dir_list))
def test_dirname_from_dir():
_dir1 = "foo"
_dir = "%s/bar" % _dir1
_dirname = fs.dirname(_dir)
assert _dirname == _dir1
def export_neglected_file_list(monitoring_dir, ROOT_DIR, LOG_DIR, backup_file_list):
today_obj = datetime.datetime.today()
today_str = str(today_obj.year)+str(today_obj.month)+str(today_obj.day)
export_name = today_str + "_neglected_files.log"
export_path = fs.join([ROOT_DIR, LOG_DIR, export_name])
if not fs.exists(fs.join([ROOT_DIR, LOG_DIR])):
try:
fs.mkdir(fs.join([ROOT_DIR, LOG_DIR]))
except:
print ("Can't create LOG_DIR in Func:", export_neglected_file_list)
try:
fs.touch(export_path)
file = fs.open(export_path, 'w')
for f in backup_file_list:
try:
file.write('================================================')
file.write('\n')
file.write(fs.filename(f))
file.write('\n')
file.write(fs.dirname(f))
file.write('\n')
except:
print("Cant' write export file in func: export_neglected_file_list")
except:
print ("cant export in func: export_neglected_file_list")
def set(key, data):
#print 'storing %s => %s' % (key, data)
filePath = _constructPathFromKey(key)
parentPath = dirname(filePath)
if not os.path.exists(parentPath):
mkdirs(parentPath)
with open(filePath, 'w') as fh:
return pickle.dump(data, fh) #filePutContents(_constructPathFromKey(key), data)
def test_dirname_from_file():
_file = 'test.txt'
_dir = "foo/bar"
_path = "%s/%s" % (_dir, _file)
_dirname = fs.dirname(_path)
assert _dirname == _dir
print("Expected Shape: ", nb_filter, stack_size, nb_col, nb_row)
print("Found Shape: ", np.array(blobs[0].data).shape)
weights_p = blobs[0].data.astype(dtype=np.float32)
weights_b = blobs[1].data.astype(dtype=np.float32)
if len(weights_p.shape) > 2:
# Caffe uses the shape f, (d, y, x)
# ConvnetJS uses the shape f, (y, x, d)
weights_p = np.swapaxes(np.swapaxes(weights_p, 3, 1), 2, 1)
print("Converted to Shape: ", weights_p.shape)
weights = {
'filter': weights_p.reshape((nb_filter, stack_size*nb_col*nb_row)).tolist(),
'bias': weights_b.tolist()
}
filename = WEIGHTS_DIR + key + '.txt'
if not fs.exists(fs.dirname(filename)):
fs.mkdir(fs.dirname(filename))
fs.write(fs.add_suffix(filename, "_filter"), "")
for i, f_weights in enumerate(weights['filter']):
if i == len(weights['filter']) - 1:
fs.append(fs.add_suffix(filename, "_filter"), ",".join(map(str, f_weights)))
else:
fs.append(fs.add_suffix(filename, "_filter"), ",".join(map(str, f_weights)) + "\n")
fs.write(fs.add_suffix(filename, "_bias"), ",".join(map(str, weights['bias'])))
import hashlib, os, sys
from fs import mkdirs, dirname #, filePutContents, fileGetContents
try:
import cPickle as pickle
except:
import pickle
"""
@description A static singleton-esque file-based key/value cache.
@date 2012-04-19
"""
CACHE_BASE_PATH = '%s/.cache/wget' % dirname(sys.argv[0])
def set(key, data):
#print 'storing %s => %s' % (key, data)
filePath = _constructPathFromKey(key)
parentPath = dirname(filePath)
if not os.path.exists(parentPath):
mkdirs(parentPath)
with open(filePath, 'w') as fh:
return pickle.dump(data, fh) #filePutContents(_constructPathFromKey(key), data)
def get(key):
try:
with open(_constructPathFromKey(key), 'r') as fh:
return pickle.load(fh) #fileGetContents(_constructPathFromKey(key))
except IOError:
return None
print("====> Layer: ", key)
print("Expected Shape: ", nb_filter, stack_size, nb_col, nb_row)
print("Found Shape: ", np.array(blobs[0].data).shape)
weights_p = blobs[0].data.reshape(
(nb_filter, stack_size, nb_col, nb_row)).astype(dtype=np.float32)
weights_b = blobs[1].data.astype(dtype=np.float32)
if len(weights_p.shape) > 2:
# Caffe uses the shape f, (d, y, x)
# ConvnetJS uses the shape f, (y, x, d)
weights_p = np.swapaxes(np.swapaxes(weights_p, 3, 1), 2, 1)
print("Converted to Shape: ", weights_p.shape)
weights = {
'filter': weights_p.reshape((nb_filter, stack_size * nb_col * nb_row)),
'bias': weights_b
}
filename = WEIGHTS_DIR + key + '.bin'
prev_shape = (nb_filter, stack_size, nb_col, nb_row)
if not fs.exists(fs.dirname(filename)):
fs.mkdir(fs.dirname(filename))
with open(fs.add_suffix(filename, "_filter"), 'wb') as f:
f.write(weights['filter'].astype(np.float32).tostring())
with open(fs.add_suffix(filename, "_bias"), 'wb') as f:
f.write(weights['bias'].astype(np.float32).tostring())
