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/
A-Performance-Evaluation-of-CNN-for-Brain-Age-Prediction-Using-Structural-MRI-Data
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Authored by
Hyunji
2021-12-20 04:23:19 +0900
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Commit
f359b8bada55b7df16eab8f58f0f6cac66173a52
f359b8ba
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922a39b3
os
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2DCNN/lib/utils/os.py
2DCNN/lib/utils/os.py
0 → 100644
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f359b8b
""" general utility functions"""
import
argparse
import
importlib
import
json
import
logging
import
os
import
random
import
re
import
shutil
import
sys
import
typing
from
argparse
import
ArgumentParser
from
collections.abc
import
MutableMapping
import
numpy
import
torch
from
box
import
Box
logger
=
logging
.
getLogger
()
def
listorstr
(
inp
):
if
len
(
inp
)
==
1
:
return
try_cast
(
inp
[
0
])
for
i
,
val
in
enumerate
(
inp
):
inp
[
i
]
=
try_cast
(
val
)
return
inp
def
try_cast
(
text
):
""" try to cast to int or float if possible, else return the text itself"""
result
=
try_int
(
text
,
None
)
if
result
is
not
None
:
return
result
result
=
try_float
(
text
,
None
)
if
result
is
not
None
:
return
result
return
text
def
try_float
(
text
,
default
:
typing
.
Optional
[
int
]
=
0.0
):
result
=
default
try
:
result
=
float
(
text
)
except
Exception
as
_
:
pass
return
result
def
try_int
(
text
,
default
:
typing
.
Optional
[
int
]
=
0
):
result
=
default
try
:
result
=
int
(
text
)
except
Exception
as
_
:
pass
return
result
def
parse_args
(
parser
:
ArgumentParser
)
->
Box
:
# get defaults
defaults
=
{}
# taken from parser_known_args code
# add any action defaults that aren't present
for
action
in
parser
.
_actions
:
if
action
.
dest
is
not
argparse
.
SUPPRESS
:
if
action
.
default
is
not
argparse
.
SUPPRESS
:
defaults
[
action
.
dest
]
=
action
.
default
# add any parser defaults that aren't present
for
dest
in
parser
.
_defaults
:
defaults
[
dest
]
=
parser
.
_defaults
[
dest
]
# check if there is config & read config
args
=
parser
.
parse_args
()
if
vars
(
args
)
.
get
(
"config"
)
is
not
None
:
# load a .py config
configFile
=
args
.
config
spec
=
importlib
.
util
.
spec_from_file_location
(
"config"
,
configFile
)
module
=
importlib
.
util
.
module_from_spec
(
spec
)
spec
.
loader
.
exec_module
(
module
)
config
=
module
.
config
# merge config and override defaults
defaults
.
update
({
k
:
v
for
k
,
v
in
config
.
items
()})
# override defaults with command line params
# this will get rid of defaults and only read command line args
parser
.
_defaults
=
{}
parser
.
_actions
=
{}
args
=
parser
.
parse_args
()
defaults
.
update
({
k
:
v
for
k
,
v
in
vars
(
args
)
.
items
()})
return
boxify_dict
(
defaults
)
def
boxify_dict
(
config
):
"""
this takes a flat dictionary and break it into sub-dictionaries based on "." seperation
a = {"model.a": 1, "model.b" : 2, "alpha" : 3} will return Box({"model" : {"a" :1,
"b" : 2}, alpha:3})
a = {"model.a": 1, "model.b" : 2, "model" : 3} will throw error
"""
new_config
=
{}
# iterate over keys and split on "."
for
key
in
config
:
if
"."
in
key
:
temp_config
=
new_config
for
k
in
key
.
split
(
"."
)[:
-
1
]:
# create non-existent keys as dictionary recursively
if
temp_config
.
get
(
k
)
is
None
:
temp_config
[
k
]
=
{}
elif
not
isinstance
(
temp_config
.
get
(
k
),
dict
):
raise
TypeError
(
f
"Key '{k}' has values as well as child"
)
temp_config
=
temp_config
[
k
]
temp_config
[
key
.
split
(
"."
)[
-
1
]]
=
config
[
key
]
else
:
if
new_config
.
get
(
key
)
is
None
:
new_config
[
key
]
=
config
[
key
]
else
:
raise
TypeError
(
f
"Key '{key}' has values as well as child"
)
return
Box
(
new_config
)
# https://stackoverflow.com/questions/6027558/flatten-nested-dictionaries-compressing-keys
def
flatten
(
d
,
parent_key
=
''
,
sep
=
'.'
):
items
=
[]
for
k
,
v
in
d
.
items
():
new_key
=
parent_key
+
sep
+
k
if
parent_key
else
k
if
isinstance
(
v
,
MutableMapping
):
items
.
extend
(
flatten
(
v
,
new_key
,
sep
=
sep
)
.
items
())
else
:
items
.
append
((
new_key
,
v
))
return
Box
(
dict
(
items
))
def
str2bool
(
v
:
typing
.
Union
[
bool
,
str
,
int
])
->
bool
:
if
isinstance
(
v
,
bool
):
return
v
if
v
.
lower
()
in
(
"yes"
,
"true"
,
"t"
,
"y"
,
"1"
,
1
):
return
True
if
v
.
lower
()
in
(
"no"
,
"false"
,
"f"
,
"n"
,
"0"
,
0
):
return
False
raise
TypeError
(
"Boolean value expected."
)
def
safe_isdir
(
dir_name
):
return
os
.
path
.
exists
(
dir_name
)
and
os
.
path
.
isdir
(
dir_name
)
def
safe_makedirs
(
dir_name
):
try
:
os
.
makedirs
(
dir_name
)
except
OSError
as
e
:
print
(
e
)
def
jsonize
(
x
:
object
)
->
typing
.
Union
[
str
,
dict
]:
try
:
temp
=
json
.
dumps
(
x
)
return
temp
except
Exception
as
e
:
return
{}
def
copy_code
(
folder_to_copy
,
out_folder
,
replace
=
False
):
logger
.
info
(
f
"copying {folder_to_copy} to {out_folder}"
)
if
os
.
path
.
exists
(
out_folder
):
if
not
os
.
path
.
isdir
(
out_folder
):
logger
.
error
(
f
"{out_folder} is not a directory"
)
sys
.
exit
()
else
:
logger
.
info
(
f
"Not deleting existing result folder: {out_folder}"
)
else
:
os
.
makedirs
(
out_folder
)
# replace / with _
folder_name
=
f
'{out_folder}/{re.sub("/", "_", folder_to_copy)}'
# create a new copy if something already exists
if
not
replace
:
i
=
1
temp
=
folder_name
while
os
.
path
.
exists
(
temp
):
temp
=
f
"{folder_name}_{i}"
i
+=
1
folder_name
=
temp
else
:
if
os
.
path
.
exists
(
folder_name
):
if
os
.
path
.
isdir
(
folder_name
):
shutil
.
rmtree
(
folder_name
)
else
:
raise
FileExistsError
(
"There is a file with same name as folder"
)
logger
.
info
(
f
"Copying {folder_to_copy} to {folder_name}"
)
shutil
.
copytree
(
folder_to_copy
,
folder_name
)
def
get_state_params
(
wandb_use
,
run_id
,
result_folder
,
statefile
):
"""This searches for model and run id in result folder
The logic is as follows
if we are not given run_id there are four cases:
- we want to restart the wandb run but too lazy to look up run-id or/and statefile
- we want a new wandb fresh run
- we are not using wandb at all and need to restart
- we are not using wandb and need a fresh run
Case 1/3:
- If we want to restart the run, we expect the result_folder name to end with
/run_<numeric>.
- In this case, if we are using wandb then we need to go inside wandb folder, list all
directory and pick up run id and (or) statefile
- If we are not using wandb we just look for model inside the run_<numeric> folder and
return statefile, run id as none
case 2/4:
if not 1/3, it is case 2/4
This is expected to be a fail safe script. i.e any of run_id or statefile may not be specified
and relies on whims of the user _-_
"""
# if not resume get run number and create result_folder/run_{run_num}
# if someone is resuming we expect them to give the exact folder name upto run num.
# this part of code searches for run_id i.e will work only if we are using wandb
if
run_id
is
None
:
# if result folder if of type folder/run_<num>, then search for current checkpoint and
# run-id else we will just create a new run with run_<num+1>
regex
=
r"^.*/?run_[0-9]+/?$"
if
re
.
match
(
regex
,
result_folder
):
# search for checkpoint and run-id if using wandb
if
wandb_use
:
# search in wandb folder if it exists else we want a new run
if
os
.
path
.
exists
(
f
"{result_folder}/wandb/"
):
# case 1
for
folder
in
sorted
(
os
.
listdir
(
f
"{result_folder}/wandb/"
),
reverse
=
True
):
# assume run_<##> will have only single run,
# also no other crap in this folder
if
os
.
path
.
exists
(
f
"{result_folder}/wandb/{folder}/current_model.pt"
):
run_id
=
folder
.
split
(
"-"
)[
-
1
]
logger
.
info
(
f
"using run id {run_id}"
)
# we are done break out of for loop
break
else
:
# case 3
# if not using wandb search within run_<num> directory
logger
.
info
(
f
"not using wandb"
)
if
os
.
path
.
exists
(
f
"{result_folder}/current_model.pt"
):
statefile
=
f
"{result_folder}/current_model.pt"
logger
.
info
(
f
"using statefile {statefile}"
)
else
:
# just start a new run
pass
else
:
# trailing is not run_<num>; that means user wants a new fresh run
# so we give a fresh run and create a new folder
# case 2/4
last_run_num
=
max
(
[
0
]
+
[
try_int
(
i
[
-
4
:])
for
i
in
os
.
listdir
(
result_folder
)])
+
1
result_folder
=
f
"{result_folder}/run_{last_run_num:04d}"
logger
.
info
(
f
"Creating new run with {result_folder}"
)
safe_makedirs
(
result_folder
)
# search for last checkpoint in case --statefile is none and we are resuming
if
run_id
is
not
None
and
statefile
is
None
:
folders
=
sorted
(
os
.
listdir
(
f
"{result_folder}/wandb"
),
reverse
=
True
)
for
folder
in
folders
:
if
run_id
in
folder
:
# check for current_model.pt
if
os
.
path
.
exists
(
f
"{result_folder}/wandb/{folder}/current_model.pt"
):
statefile
=
f
"{result_folder}/wandb/{folder}/current_model.pt"
logger
.
info
(
f
"Using state file {statefile} and run id {run_id}"
)
break
if
statefile
is
None
:
raise
Exception
(
"Did not find statefile, exiting!!"
)
return
statefile
,
run_id
,
result_folder
if
__name__
==
"__main__"
:
# test boxify_dict
a
=
{
"model.a"
:
1
,
"m odel.b"
:
2
,
"alpha"
:
3
}
print
(
boxify_dict
(
a
))
try
:
a
=
{
"model.a"
:
1
,
"model.b"
:
2
,
"model"
:
3
}
print
(
boxify_dict
(
a
))
except
Exception
as
e
:
print
(
e
)
try
:
a
=
{
"model"
:
4
,
"model.a"
:
1
,
"model.b"
:
2
,
"model"
:
3
}
print
(
boxify_dict
(
a
))
except
Exception
as
e
:
print
(
e
)
try
:
a
=
{
"model.a"
:
1
,
"model"
:
4
,
"model.b"
:
2
,
"model"
:
3
}
print
(
boxify_dict
(
a
))
except
Exception
as
e
:
print
(
e
)
try
:
a
=
{
"model"
:
{
"attr1"
:
1
,
"attr2"
:
{
"attr_attr_3"
:
3
}},
"train"
:
10
}
print
(
flatten
(
a
))
except
Exception
as
e
:
print
(
e
)
def
set_seed
(
seed
):
if
isinstance
(
seed
,
list
):
torch_seed
,
numpy_seed
,
random_seed
=
seed
else
:
torch_seed
,
numpy_seed
,
random_seed
=
seed
,
seed
,
seed
torch
.
manual_seed
(
torch_seed
)
numpy
.
random
.
seed
(
numpy_seed
)
random
.
seed
(
random_seed
)
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