DeepFaceLab/utils/mp_utils.py
2020-01-07 13:45:54 +04:00

302 lines
8.5 KiB
Python

import multiprocessing
import threading
import time
import numpy as np
class Index2DHost():
"""
Provides random shuffled 2D indexes for multiprocesses
"""
def __init__(self, indexes2D):
self.sq = multiprocessing.Queue()
self.cqs = []
self.clis = []
self.thread = threading.Thread(target=self.host_thread, args=(indexes2D,) )
self.thread.daemon = True
self.thread.start()
def host_thread(self, indexes2D):
indexes_counts_len = len(indexes2D)
idxs = [*range(indexes_counts_len)]
idxs_2D = [None]*indexes_counts_len
shuffle_idxs = []
shuffle_idxs_2D = [None]*indexes_counts_len
for i in range(indexes_counts_len):
idxs_2D[i] = indexes2D[i]
shuffle_idxs_2D[i] = []
sq = self.sq
while True:
while not sq.empty():
obj = sq.get()
cq_id, cmd = obj[0], obj[1]
if cmd == 0: #get_1D
count = obj[2]
result = []
for i in range(count):
if len(shuffle_idxs) == 0:
shuffle_idxs = idxs.copy()
np.random.shuffle(shuffle_idxs)
result.append(shuffle_idxs.pop())
self.cqs[cq_id].put (result)
elif cmd == 1: #get_2D
targ_idxs,count = obj[2], obj[3]
result = []
for targ_idx in targ_idxs:
sub_idxs = []
for i in range(count):
ar = shuffle_idxs_2D[targ_idx]
if len(ar) == 0:
ar = shuffle_idxs_2D[targ_idx] = idxs_2D[targ_idx].copy()
np.random.shuffle(ar)
sub_idxs.append(ar.pop())
result.append (sub_idxs)
self.cqs[cq_id].put (result)
time.sleep(0.005)
def create_cli(self):
cq = multiprocessing.Queue()
self.cqs.append ( cq )
cq_id = len(self.cqs)-1
return Index2DHost.Cli(self.sq, cq, cq_id)
# disable pickling
def __getstate__(self):
return dict()
def __setstate__(self, d):
self.__dict__.update(d)
class Cli():
def __init__(self, sq, cq, cq_id):
self.sq = sq
self.cq = cq
self.cq_id = cq_id
def get_1D(self, count):
self.sq.put ( (self.cq_id,0, count) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
def get_2D(self, idxs, count):
self.sq.put ( (self.cq_id,1,idxs,count) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
class IndexHost():
"""
Provides random shuffled indexes for multiprocesses
"""
def __init__(self, indexes_count):
self.sq = multiprocessing.Queue()
self.cqs = []
self.clis = []
self.thread = threading.Thread(target=self.host_thread, args=(indexes_count,) )
self.thread.daemon = True
self.thread.start()
def host_thread(self, indexes_count):
idxs = [*range(indexes_count)]
shuffle_idxs = []
sq = self.sq
while True:
while not sq.empty():
obj = sq.get()
cq_id, count = obj[0], obj[1]
result = []
for i in range(count):
if len(shuffle_idxs) == 0:
shuffle_idxs = idxs.copy()
np.random.shuffle(shuffle_idxs)
result.append(shuffle_idxs.pop())
self.cqs[cq_id].put (result)
time.sleep(0.001)
def create_cli(self):
cq = multiprocessing.Queue()
self.cqs.append ( cq )
cq_id = len(self.cqs)-1
return IndexHost.Cli(self.sq, cq, cq_id)
# disable pickling
def __getstate__(self):
return dict()
def __setstate__(self, d):
self.__dict__.update(d)
class Cli():
def __init__(self, sq, cq, cq_id):
self.sq = sq
self.cq = cq
self.cq_id = cq_id
def multi_get(self, count):
self.sq.put ( (self.cq_id,count) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
class ListHost():
def __init__(self, list_):
self.sq = multiprocessing.Queue()
self.cqs = []
self.clis = []
self.m_list = list_
self.thread = threading.Thread(target=self.host_thread)
self.thread.daemon = True
self.thread.start()
def host_thread(self):
sq = self.sq
while True:
while not sq.empty():
obj = sq.get()
cq_id, cmd = obj[0], obj[1]
if cmd == 0:
self.cqs[cq_id].put ( len(self.m_list) )
elif cmd == 1:
idx = obj[2]
item = self.m_list[idx ]
self.cqs[cq_id].put ( item )
elif cmd == 2:
result = []
for item in obj[2]:
result.append ( self.m_list[item] )
self.cqs[cq_id].put ( result )
elif cmd == 3:
self.m_list.insert(obj[2], obj[3])
elif cmd == 4:
self.m_list.append(obj[2])
elif cmd == 5:
self.m_list.extend(obj[2])
time.sleep(0.005)
def create_cli(self):
cq = multiprocessing.Queue()
self.cqs.append ( cq )
cq_id = len(self.cqs)-1
return ListHost.Cli(self.sq, cq, cq_id)
def get_list(self):
return self.list_
# disable pickling
def __getstate__(self):
return dict()
def __setstate__(self, d):
self.__dict__.update(d)
class Cli():
def __init__(self, sq, cq, cq_id):
self.sq = sq
self.cq = cq
self.cq_id = cq_id
def __len__(self):
self.sq.put ( (self.cq_id,0) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
def __getitem__(self, key):
self.sq.put ( (self.cq_id,1,key) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
def multi_get(self, keys):
self.sq.put ( (self.cq_id,2,keys) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
def insert(self, index, item):
self.sq.put ( (self.cq_id,3,index,item) )
def append(self, item):
self.sq.put ( (self.cq_id,4,item) )
def extend(self, items):
self.sq.put ( (self.cq_id,5,items) )
class DictHost():
def __init__(self, d, num_users):
self.sqs = [ multiprocessing.Queue() for _ in range(num_users) ]
self.cqs = [ multiprocessing.Queue() for _ in range(num_users) ]
self.thread = threading.Thread(target=self.host_thread, args=(d,) )
self.thread.daemon = True
self.thread.start()
self.clis = [ DictHostCli(sq,cq) for sq, cq in zip(self.sqs, self.cqs) ]
def host_thread(self, d):
while True:
for sq, cq in zip(self.sqs, self.cqs):
if not sq.empty():
obj = sq.get()
cmd = obj[0]
if cmd == 0:
cq.put (d[ obj[1] ])
elif cmd == 1:
cq.put ( list(d.keys()) )
time.sleep(0.005)
def get_cli(self, n_user):
return self.clis[n_user]
# disable pickling
def __getstate__(self):
return dict()
def __setstate__(self, d):
self.__dict__.update(d)
class DictHostCli():
def __init__(self, sq, cq):
self.sq = sq
self.cq = cq
def __getitem__(self, key):
self.sq.put ( (0,key) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)
def keys(self):
self.sq.put ( (1,) )
while True:
if not self.cq.empty():
return self.cq.get()
time.sleep(0.001)