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Upgraded to TF version 1.13.2

Browse source 
Removed the wait at first launch for most graphics cards.

Increased speed of training by 10-20%, but you have to retrain all models from scratch.

SAEHD:

added option 'use float16'
	Experimental option. Reduces the model size by half.
	Increases the speed of training.
	Decreases the accuracy of the model.
	The model may collapse or not train.
	Model may not learn the mask in large resolutions.

true_face_training option is replaced by
"True face power". 0.0000 .. 1.0
Experimental option. Discriminates the result face to be more like the src face. Higher value - stronger discrimination.
Comparison - https://i.imgur.com/czScS9q.png
This commit is contained in:
Colombo 2020-01-25 21:58:19 +04:00
commit 76ca79216e
49 changed files with 1320 additions and 1297 deletions
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48
core/leras/device.py
View file

@ -1,7 +1,7 @@
import sys
import ctypes
import os
class Device(object):
def __init__(self, index, name, total_mem, free_mem, cc=0):
self.index = index
@ -11,25 +11,25 @@ class Device(object):
self.total_mem_gb = total_mem / 1024**3
self.free_mem = free_mem
self.free_mem_gb = free_mem / 1024**3
def __str__(self):
return f"[{self.index}]:[{self.name}][{self.free_mem_gb:.3}/{self.total_mem_gb :.3}]"
class Devices(object):
all_devices = None
def __init__(self, devices):
self.devices = devices
def __len__(self):
return len(self.devices)
def __getitem__(self, key):
result = self.devices[key]
if isinstance(key, slice):
return Devices(result)
return result
def __iter__(self):
for device in self.devices:
yield device
@ -59,14 +59,14 @@ class Devices(object):
if device.index == idx:
return device
return None
def get_devices_from_index_list(self, idx_list):
result = []
for device in self.devices:
if device.index in idx_list:
result += [device]
return Devices(result)
def get_equal_devices(self, device):
device_name = device.name
result = []
@ -74,7 +74,7 @@ class Devices(object):
if device.name == device_name:
result.append (device)
return Devices(result)
def get_devices_at_least_mem(self, totalmemsize_gb):
result = []
for device in self.devices:
@ -84,7 +84,7 @@ class Devices(object):
@staticmethod
def initialize_main_env():
min_cc = int(os.environ.get("TF_MIN_REQ_CAP", 35))
min_cc = int(os.environ.get("TF_MIN_REQ_CAP", 35))
libnames = ('libcuda.so', 'libcuda.dylib', 'nvcuda.dll')
for libname in libnames:
try:
@ -122,40 +122,40 @@ class Devices(object):
if cuda.cuMemGetInfo_v2(ctypes.byref(freeMem), ctypes.byref(totalMem)) == 0:
cc = cc_major.value * 10 + cc_minor.value
if cc >= min_cc:
devices.append ( {'name' : name.split(b'\0', 1)[0].decode(),
devices.append ( {'name' : name.split(b'\0', 1)[0].decode(),
'total_mem' : totalMem.value,
'free_mem' : freeMem.value,
'cc' : cc
})
cuda.cuCtxDetach(context)
os.environ['NN_DEVICES_INITIALIZED'] = '1'
os.environ['NN_DEVICES_COUNT'] = str(len(devices))
for i, device in enumerate(devices):
os.environ['NN_DEVICES_COUNT'] = str(len(devices))
for i, device in enumerate(devices):
os.environ[f'NN_DEVICE_{i}_NAME'] = device['name']
os.environ[f'NN_DEVICE_{i}_TOTAL_MEM'] = str(device['total_mem'])
os.environ[f'NN_DEVICE_{i}_FREE_MEM'] = str(device['free_mem'])
os.environ[f'NN_DEVICE_{i}_CC'] = str(device['cc'])
@staticmethod
def getDevices():
if Devices.all_devices is None:
def getDevices():
if Devices.all_devices is None:
if int(os.environ.get("NN_DEVICES_INITIALIZED", 0)) != 1:
raise Exception("nn devices are not initialized. Run initialize_main_env() in main process.")
raise Exception("nn devices are not initialized. Run initialize_main_env() in main process.")
devices = []
for i in range ( int(os.environ['NN_DEVICES_COUNT']) ):
for i in range ( int(os.environ['NN_DEVICES_COUNT']) ):
devices.append ( Device(index=i,
name=os.environ[f'NN_DEVICE_{i}_NAME'],
name=os.environ[f'NN_DEVICE_{i}_NAME'],
total_mem=int(os.environ[f'NN_DEVICE_{i}_TOTAL_MEM']),
free_mem=int(os.environ[f'NN_DEVICE_{i}_FREE_MEM']),
cc=int(os.environ[f'NN_DEVICE_{i}_CC']) ))
Devices.all_devices = Devices(devices)
return Devices.all_devices
"""
if Devices.all_devices is None:
min_cc = int(os.environ.get("TF_MIN_REQ_CAP", 35))
if Devices.all_devices is None:
min_cc = int(os.environ.get("TF_MIN_REQ_CAP", 35))
libnames = ('libcuda.so', 'libcuda.dylib', 'nvcuda.dll')
for libname in libnames:
@ -195,7 +195,7 @@ if Devices.all_devices is None:
cc = cc_major.value * 10 + cc_minor.value
if cc >= min_cc:
devices.append ( Device(index=i,
name=name.split(b'\0', 1)[0].decode(),
name=name.split(b'\0', 1)[0].decode(),
total_mem=totalMem.value,
free_mem=freeMem.value,
cc=cc) )