comicocr / modules /base.py
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init
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import gc
import os
import time
from typing import Dict, List, Callable, Union
from copy import deepcopy
from collections import OrderedDict
import re
import importlib
from utils.logger import logger as LOGGER
from utils import shared
GPUINTENSIVE_SET = {'cuda', 'mps', 'xpu', 'privateuseone'}
def register_hooks(hooks_registered: OrderedDict, callbacks: Union[List, Callable, Dict]):
if callbacks is None:
return
if isinstance(callbacks, (Dict, OrderedDict)):
for k, v in callbacks.items():
hooks_registered[k] = v
else:
nhooks = len(hooks_registered)
if isinstance(callbacks, Callable):
callbacks = [callbacks]
for callback in callbacks:
hk = 'hook_' + str(nhooks).zfill(2)
while True:
if hk not in hooks_registered:
break
hk = hk + '_' + str(time.time_ns())
hooks_registered[hk] = callback
nhooks += 1
def patch_module_params(cfg_param, module_params, module_name: str = ''):
# cfg_param = config_params[module_key]
cfg_key_set = set(cfg_param.keys())
module_key_set = set(module_params.keys())
for ck in cfg_key_set:
if ck not in module_key_set:
LOGGER.warning(f'Found invalid {module_name} config: {ck}')
cfg_param.pop(ck)
for mk in module_key_set:
if mk not in cfg_key_set:
if not mk.startswith('__') and mk != 'description':
LOGGER.info(f'Found new {module_name} config: {mk}')
cfg_param[mk] = module_params[mk]
else:
mparam = module_params[mk]
cparam = cfg_param[mk]
if isinstance(mparam, dict):
tgt_type = mparam.get('data_type', type(mparam['value']))
if isinstance(cparam, dict):
if 'value' in cparam:
v = cparam['value']
elif isinstance(mparam['value'], dict):
for k in mparam['value']:
if k in cparam:
mparam['value'][k] = cparam[k]
v = mparam['value']
else:
v = mparam['value']
else:
v = cparam
valid = True
if tgt_type != type(v):
try:
v = tgt_type(v)
except:
valid = False
LOGGER.warning(f'Invalid param value {v} for defined dtype: {tgt_type}, it will be set to default value: {mparam}')
if valid:
mparam['value'] = v
cfg_param[mk] = mparam
else:
if type(cparam) != type(mparam):
if not isinstance(mparam, dict) and isinstance(cparam, dict):
cparam = cparam['value']
try:
cfg_param[mk] = type(mparam)(cparam)
except ValueError:
LOGGER.warning(f'Invalid param value {cparam} for defined dtype: {type(mparam)}, it will be set to default value: {mparam}')
cfg_param[mk] = mparam
cfg_key_list = list(cfg_param.keys())
module_key_list = list(module_params.keys())
if cfg_key_list != module_key_list:
new_params = {key: cfg_param[key] for key in module_key_list}
cfg_param.clear()
cfg_param.update(new_params)
module_key_set = set(module_params.keys())
cfg_param['__param_patched'] = True
return cfg_param
def merge_config_module_params(config_params: Dict, module_keys: List, get_module: Callable) -> Dict:
for module_key in module_keys:
module_params = get_module(module_key).params
if module_key not in config_params or config_params[module_key] is None:
config_params[module_key] = module_params
else:
patch_module_params(config_params[module_key], module_params, module_key)
return config_params
def standardize_module_params(params):
if params is None:
return
for k, v in params.items():
if not isinstance(v, dict):
v = {'value': v}
if 'data_type' not in v:
v['data_type'] = type(v['value'])
params[k] = v
class BaseModule:
params: Dict = None
logger = LOGGER
_preprocess_hooks: OrderedDict = None
_postprocess_hooks: OrderedDict = None
download_file_list: List = None
download_file_on_load = False
_load_model_keys: set = None
def __init__(self, **params) -> None:
standardize_module_params(self.params)
if self.params is not None and '__param_patched' not in params:
params = patch_module_params(params, self.params, self)
if params:
if self.params is None:
self.params = params
else:
self.params.update(params)
@classmethod
def register_postprocess_hooks(cls, callbacks: Union[List, Callable]):
"""
these hooks would be shared among all objects inherited from the same super class
"""
assert cls._postprocess_hooks is not None
register_hooks(cls._postprocess_hooks, callbacks)
@classmethod
def register_preprocess_hooks(cls, callbacks: Union[List, Callable, Dict]):
"""
these hooks would be shared among all objects inherited from the same super class
"""
assert cls._preprocess_hooks is not None
register_hooks(cls._preprocess_hooks, callbacks)
def get_param_value(self, param_key: str):
assert self.params is not None and param_key in self.params
p = self.params[param_key]
if isinstance(p, dict):
return p['value']
return p
def set_param_value(self, param_key: str, param_value, convert_dtype=True):
assert self.params is not None and param_key in self.params
p = self.params[param_key]
if isinstance(p, dict):
if convert_dtype:
try:
val_type = p.get('data_type', type(p['value']))
param_value = val_type(param_value)
except ValueError:
dtype = type(p['value'])
self.logger.warning(f'Invalid param value {param_value} for defined dtype: {dtype}')
p['value'] = param_value
else:
if convert_dtype:
try:
param_value = type(p)(param_value)
except ValueError:
self.logger.warning(f'Invalid param value {param_value} for defined dtype: {type(p)}, revert to original value {p}')
param_value = p
self.params[param_key] = param_value
def updateParam(self, param_key: str, param_content):
self.set_param_value(param_key, param_content)
@property
def low_vram_mode(self):
if 'low vram mode' in self.params:
return self.get_param_value('low vram mode')
return False
def is_cpu_intensive(self)->bool:
if self.params is not None and 'device' in self.params:
return self.params['device']['value'] == 'cpu'
return False
def is_gpu_intensive(self) -> bool:
if self.params is not None and 'device' in self.params:
return self.params['device']['value'] in GPUINTENSIVE_SET
return False
def is_computational_intensive(self) -> bool:
if self.params is not None and 'device' in self.params:
return True
return False
def unload_model(self, empty_cache=False):
model_deleted = False
if self._load_model_keys is not None:
for k in self._load_model_keys:
if hasattr(self, k):
model = getattr(self, k)
if model is not None:
if hasattr(model, 'unload_model'):
model.unload_model(empty_cache=False)
del model
setattr(self, k, None)
model_deleted = True
if empty_cache and model_deleted:
soft_empty_cache()
return model_deleted
def load_model(self):
# TODO: check and download files
self._load_model()
return
def _load_model(self):
return
def all_model_loaded(self):
if self._load_model_keys is None:
return True
for k in self._load_model_keys:
if not hasattr(self, k) or getattr(self, k) is None:
return False
return True
def __del__(self):
self.unload_model()
@property
def debug_mode(self):
return shared.DEBUG
def flush(self, param_key: str):
return None
os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1'
import torch
DEFAULT_DEVICE = 'cpu'
AVAILABLE_DEVICES = ['cpu']
if hasattr(torch, 'cuda') and torch.cuda.is_available():
DEFAULT_DEVICE = 'cuda'
AVAILABLE_DEVICES.append(DEFAULT_DEVICE)
if hasattr(torch, 'xpu') and torch.xpu.is_available():
DEFAULT_DEVICE = 'xpu' if torch.xpu.is_available() else 'cpu'
AVAILABLE_DEVICES.append(DEFAULT_DEVICE)
if hasattr(torch, 'backends') and hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
DEFAULT_DEVICE = 'mps'
AVAILABLE_DEVICES.append(DEFAULT_DEVICE)
try:
import torch_directml
if hasattr(torch, 'privateuseone') and torch_directml.device_count() > 0:
torch.dml = torch_directml
DEFAULT_DEVICE = f'privateuseone:{torch.dml.default_device()}'
AVAILABLE_DEVICES += [f"privateuseone:{d}" for d in range(torch.dml.device_count())]
except:
# directml is not supported
pass
BF16_SUPPORTED = DEFAULT_DEVICE == 'cuda' and torch.cuda.is_bf16_supported() or DEFAULT_DEVICE == 'xpu' and torch.xpu.is_bf16_supported()
def is_nvidia():
if DEFAULT_DEVICE == 'cuda':
if torch.version.cuda:
return True
return False
def is_intel():
if DEFAULT_DEVICE == 'xpu':
if torch.version.xpu:
return True
return False
def soft_empty_cache():
gc.collect()
if DEFAULT_DEVICE == 'cuda':
torch.cuda.empty_cache()
torch.cuda.ipc_collect()
elif DEFAULT_DEVICE == 'xpu':
torch.xpu.empty_cache()
# torch.xpu.ipc_collect()
elif DEFAULT_DEVICE == 'mps':
torch.mps.empty_cache()
def DEVICE_SELECTOR(not_supported:list[str]=[]): return deepcopy(
{
'type': 'selector',
'options': [opt for opt in AVAILABLE_DEVICES if all(device not in opt for device in not_supported)],
'value': DEFAULT_DEVICE if not any(DEFAULT_DEVICE in device for device in not_supported) else 'cpu'
}
)
TORCH_DTYPE_MAP = {
'fp32': torch.float32,
'fp16': torch.float16,
'bf16': torch.bfloat16,
}
MODULE_SCRIPTS = {
'translator': {'module_dir': 'modules/translators', 'module_pattern': r'trans_(.*?).py'},
'textdetector': {'module_dir': 'modules/textdetector', 'module_pattern': r'detector_(.*?).py'},
'inpainter': {'module_dir': 'modules/inpaint', 'module_pattern': r'inpaint_(.*?).py'},
'ocr': {'module_dir': 'modules/ocr', 'module_pattern': r'ocr_(.*?).py'},
}
def init_module_registries(target_modules=None):
def _load_module(module_dir: str, module_pattern: str):
modules = os.listdir(module_dir)
pattern = re.compile(module_pattern)
module_path = module_dir.replace('/', '.')
if not module_path.endswith('.'):
module_path += '.'
for module_name in modules:
if pattern.match(module_name) is not None:
try:
module = module_path + module_name.replace('.py', '')
importlib.import_module(module)
except Exception as e:
LOGGER.warning(f'Failed to import {module}: {e}')
if target_modules is None:
target_modules = MODULE_SCRIPTS
if isinstance(target_modules, str):
target_modules = [target_modules]
for k in target_modules:
_load_module(**MODULE_SCRIPTS[k])
def init_textdetector_registries():
init_module_registries('textdetector')
def init_inpainter_registries():
init_module_registries('inpainter')
def init_ocr_registries():
init_module_registries('ocr')
def init_translator_registries():
init_module_registries('translator')