BrokenPipeError: [WinError 109] 管道已结束。
HelloWorldYYYYY opened this issue · 4 comments
HelloWorldYYYYY commented
HelloWorldYYYYY commented
This is the first item I run after learning deep learning. I don't want this project to fail
SeungjunNah commented
Hi @HelloWorldYYYYY,
I don't support the code to run on Windows and also don't recognize the Chinese error logs.
From what I could read, it seems like a multiprocessing-related error is happening.
There is another thread (Issue #18) you might want to refer to.
Best,
Seungjun
HelloWorldYYYYY commented
@SeungjunNah Thank you for your reminder!I have solved the demo problem tonight.
HelloWorldYYYYY commented
<utils.py>
import readline
import rlcompleter
readline.parse_and_bind("tab: complete")
import code
import pdb
import time
import argparse
import os
import imageio
import torch
import torch.multiprocessing as mp
import cv2
# debugging tools
def interact(local=None):
"""interactive console with autocomplete function. Useful for debugging.
interact(locals())
"""
if local is None:
local=dict(globals(), **locals())
readline.set_completer(rlcompleter.Completer(local).complete)
code.interact(local=local)
def set_trace(local=None):
"""debugging with pdb
"""
if local is None:
local=dict(globals(), **locals())
pdb.Pdb.complete = rlcompleter.Completer(local).complete
pdb.set_trace()
# timer
class Timer():
"""Brought from https://github.com/thstkdgus35/EDSR-PyTorch
"""
def __init__(self):
self.acc = 0
self.tic()
def tic(self):
self.t0 = time.time()
def toc(self):
return time.time() - self.t0
def hold(self):
self.acc += self.toc()
def release(self):
ret = self.acc
self.acc = 0
return ret
def reset(self):
self.acc = 0
# argument parser type casting functions
def str2bool(val):
"""enable default constant true arguments"""
# https://stackoverflow.com/questions/15008758/parsing-boolean-values-with-argparse
if isinstance(val, bool):
return val
elif val.lower() == 'true':
return True
elif val.lower() == 'false':
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected')
def int2str(val):
"""convert int to str for environment variable related arguments"""
if isinstance(val, int):
return str(val)
elif isinstance(val, str):
return val
else:
raise argparse.ArgumentTypeError('number value expected')
def BGR_to_RGB(cvimg):
pilimg = cvimg.copy()
pilimg[:, :, 0] = cvimg[:, :, 2]
pilimg[:, :, 2] = cvimg[:, :, 0]
return pilimg
# image saver using multiprocessing queue
'''
class MultiSaver():
def __init__(self, result_dir=None):
self.queue = None
self.process = None
self.result_dir = result_dir
def begin_background(self):
self.queue = mp.Queue()
def t(queue):
while True:
if queue.empty():
continue
img, name = queue.get()
if name:
try:
basename, ext = os.path.splitext(name)
if ext != '.png':
name = '{}.png'.format(basename)
imageio.imwrite(name, img)
except Exception as e:
print(e)
else:
return
worker = lambda: mp.Process(target=t, args=(self.queue,), daemon=False)
cpu_count = min(8, mp.cpu_count() - 1)
self.process = [worker() for _ in range(cpu_count)]
for p in self.process:
p.start()
def end_background(self):
if self.queue is None:
return
for _ in self.process:
self.queue.put((None, None))
def join_background(self):
if self.queue is None:
return
while not self.queue.empty():
time.sleep(0.5)
for p in self.process:
p.join()
self.queue = None
def save_image(self, output, save_names, result_dir=None):
result_dir = result_dir if self.result_dir is None else self.result_dir
if result_dir is None:
raise Exception('no result dir specified!')
if self.queue is None:
try:
self.begin_background()
except Exception as e:
print(e)
return
# assume NCHW format
if output.ndim == 2:
output = output.expand([1, 1] + list(output.shape))
elif output.ndim == 3:
output = output.expand([1] + list(output.shape))
for output_img, save_name in zip(output, save_names):
# assume image range [0, 255]
output_img = output_img.add_(0.5).clamp_(0, 255).permute(1, 2, 0).to('cpu', torch.uint8).numpy()
save_name = os.path.join(result_dir, save_name)
save_dir = os.path.dirname(save_name)
os.makedirs(save_dir, exist_ok=True)
self.queue.put((output_img, save_name))
return
'''
class MultiSaver():
@staticmethod
def t(queue):
while True:
if queue.empty():
continue
img, name = queue.get()
if name:
try:
basename, ext = os.path.splitext(name)
if ext != '.png':
name = '{}.png'.format(basename)
imageio.imwrite(name, img)
except Exception as e:
print(e)
else:
return
def __init__(self, result_dir=None):
self.queue = None
self.process = None
self.result_dir = result_dir
def begin_background(self):
self.queue = mp.Queue()
worker = lambda: mp.Process(target=MultiSaver.t, args=(self.queue,), daemon=False)
cpu_count = min(8, mp.cpu_count() - 1)
self.process = [worker() for _ in range(cpu_count)]
for p in self.process:
p.start()
def end_background(self):
if self.queue is None:
return
for _ in self.process:
self.queue.put((None, None))
def join_background(self):
if self.queue is None:
return
while not self.queue.empty():
time.sleep(0.5)
for p in self.process:
p.join()
self.queue = None
def save_image(self, output, save_names, result_dir=None):
result_dir = result_dir if self.result_dir is None else self.result_dir
if result_dir is None:
raise Exception('no result dir specified!')
if self.queue is None:
try:
self.begin_background()
except Exception as e:
print(e)
return
# assume NCHW format
if output.ndim == 2:
output = output.expand([1, 1] + list(output.shape))
elif output.ndim == 3:
output = output.expand([1] + list(output.shape))
for output_img, save_name in zip(output, save_names):
# assume image range [0, 255]
output_img = output_img.add_(0.5).clamp_(0, 255).permute(1, 2, 0).to('cpu', torch.uint8).numpy()
save_name = os.path.join(result_dir, save_name)
isWritten = cv2.imwrite(save_name, BGR_to_RGB(output_img))
if isWritten:
print('The image is successfully saved.')
save_dir = os.path.dirname(save_name)
os.makedirs(save_dir, exist_ok=True)
self.queue.put((output_img, save_name))
return
class Map(dict):
"""
https://stackoverflow.com/questions/2352181/how-to-use-a-dot-to-access-members-of-dictionary
Example:
m = Map({'first_name': 'Eduardo'}, last_name='Pool', age=24, sports=['Soccer'])
"""
def __init__(self, *args, **kwargs):
super(Map, self).__init__(*args, **kwargs)
for arg in args:
if isinstance(arg, dict):
for k, v in arg.items():
self[k] = v
if kwargs:
for k, v in kwargs.items():
self[k] = v
def __getattr__(self, attr):
return self.get(attr)
def __setattr__(self, key, value):
self.__setitem__(key, value)
def __setitem__(self, key, value):
super(Map, self).__setitem__(key, value)
self.__dict__.update({key: value})
def __delattr__(self, item):
self.__delitem__(item)
def __delitem__(self, key):
super(Map, self).__delitem__(key)
del self.__dict__[key]
def toDict(self):
return self.__dict__