InvokeAI/invokeai/backend/util/logging.py

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# Copyright (c) 2023 Lincoln D. Stein and The InvokeAI Development Team
"""invokeai.util.logging
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Logging class for InvokeAI that produces console messages
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Usage:
from invokeai.backend.util.logging import InvokeAILogger
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logger = InvokeAILogger.getLogger(name='InvokeAI') // Initialization
(or)
logger = InvokeAILogger.getLogger(__name__) // To use the filename
logger.critical('this is critical') // Critical Message
logger.error('this is an error') // Error Message
logger.warning('this is a warning') // Warning Message
logger.info('this is info') // Info Message
logger.debug('this is debugging') // Debug Message
Console messages:
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[12-05-2023 20]::[InvokeAI]::CRITICAL --> This is an info message [In Bold Red]
[12-05-2023 20]::[InvokeAI]::ERROR --> This is an info message [In Red]
[12-05-2023 20]::[InvokeAI]::WARNING --> This is an info message [In Yellow]
[12-05-2023 20]::[InvokeAI]::INFO --> This is an info message [In Grey]
[12-05-2023 20]::[InvokeAI]::DEBUG --> This is an info message [In Grey]
Alternate Method (in this case the logger name will be set to InvokeAI):
import invokeai.backend.util.logging as IAILogger
IAILogger.debug('this is a debugging message')
"""
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import logging
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add logging support This commit adds invokeai.backend.util.logging, which provides support for formatted console and logfile messages that follow the status reporting conventions of earlier InvokeAI versions. Examples: ### A critical error (logging.CRITICAL) *** A non-fatal error (logging.ERROR) ** A warning (logging.WARNING) >> Informational message (logging.INFO) | Debugging message (logging.DEBUG) This style logs everything through a single logging object and is identical to using Python's `logging` module. The commonly-used module-level logging functions are implemented as simple pass-thrus to logging: import invokeai.backend.util.logging as ialog ialog.debug('this is a debugging message') ialog.info('this is a informational message') ialog.log(level=logging.CRITICAL, 'get out of dodge') ialog.disable(level=logging.INFO) ialog.basicConfig(filename='/var/log/invokeai.log') Internally, the invokeai logging module creates a new default logger named "invokeai" so that its logging does not interfere with other module's use of the vanilla logging module. So `logging.error("foo")` will go through the regular logging path and not add the additional message decorations. For more control, the logging module's object-oriented logging style is also supported. The API is identical to the vanilla logging usage. In fact, the only thing that has changed is that the getLogger() method adds a custom formatter to the log messages. import logging from invokeai.backend.util.logging import InvokeAILogger logger = InvokeAILogger.getLogger(__name__) fh = logging.FileHandler('/var/invokeai.log') logger.addHandler(fh) logger.critical('this will be logged to both the console and the log file')
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# module level functions
def debug(msg, *args, **kwargs):
InvokeAILogger.getLogger().debug(msg, *args, **kwargs)
add logging support This commit adds invokeai.backend.util.logging, which provides support for formatted console and logfile messages that follow the status reporting conventions of earlier InvokeAI versions. Examples: ### A critical error (logging.CRITICAL) *** A non-fatal error (logging.ERROR) ** A warning (logging.WARNING) >> Informational message (logging.INFO) | Debugging message (logging.DEBUG) This style logs everything through a single logging object and is identical to using Python's `logging` module. The commonly-used module-level logging functions are implemented as simple pass-thrus to logging: import invokeai.backend.util.logging as ialog ialog.debug('this is a debugging message') ialog.info('this is a informational message') ialog.log(level=logging.CRITICAL, 'get out of dodge') ialog.disable(level=logging.INFO) ialog.basicConfig(filename='/var/log/invokeai.log') Internally, the invokeai logging module creates a new default logger named "invokeai" so that its logging does not interfere with other module's use of the vanilla logging module. So `logging.error("foo")` will go through the regular logging path and not add the additional message decorations. For more control, the logging module's object-oriented logging style is also supported. The API is identical to the vanilla logging usage. In fact, the only thing that has changed is that the getLogger() method adds a custom formatter to the log messages. import logging from invokeai.backend.util.logging import InvokeAILogger logger = InvokeAILogger.getLogger(__name__) fh = logging.FileHandler('/var/invokeai.log') logger.addHandler(fh) logger.critical('this will be logged to both the console and the log file')
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def info(msg, *args, **kwargs):
InvokeAILogger.getLogger().info(msg, *args, **kwargs)
add logging support This commit adds invokeai.backend.util.logging, which provides support for formatted console and logfile messages that follow the status reporting conventions of earlier InvokeAI versions. Examples: ### A critical error (logging.CRITICAL) *** A non-fatal error (logging.ERROR) ** A warning (logging.WARNING) >> Informational message (logging.INFO) | Debugging message (logging.DEBUG) This style logs everything through a single logging object and is identical to using Python's `logging` module. The commonly-used module-level logging functions are implemented as simple pass-thrus to logging: import invokeai.backend.util.logging as ialog ialog.debug('this is a debugging message') ialog.info('this is a informational message') ialog.log(level=logging.CRITICAL, 'get out of dodge') ialog.disable(level=logging.INFO) ialog.basicConfig(filename='/var/log/invokeai.log') Internally, the invokeai logging module creates a new default logger named "invokeai" so that its logging does not interfere with other module's use of the vanilla logging module. So `logging.error("foo")` will go through the regular logging path and not add the additional message decorations. For more control, the logging module's object-oriented logging style is also supported. The API is identical to the vanilla logging usage. In fact, the only thing that has changed is that the getLogger() method adds a custom formatter to the log messages. import logging from invokeai.backend.util.logging import InvokeAILogger logger = InvokeAILogger.getLogger(__name__) fh = logging.FileHandler('/var/invokeai.log') logger.addHandler(fh) logger.critical('this will be logged to both the console and the log file')
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def warning(msg, *args, **kwargs):
InvokeAILogger.getLogger().warning(msg, *args, **kwargs)
add logging support This commit adds invokeai.backend.util.logging, which provides support for formatted console and logfile messages that follow the status reporting conventions of earlier InvokeAI versions. Examples: ### A critical error (logging.CRITICAL) *** A non-fatal error (logging.ERROR) ** A warning (logging.WARNING) >> Informational message (logging.INFO) | Debugging message (logging.DEBUG) This style logs everything through a single logging object and is identical to using Python's `logging` module. The commonly-used module-level logging functions are implemented as simple pass-thrus to logging: import invokeai.backend.util.logging as ialog ialog.debug('this is a debugging message') ialog.info('this is a informational message') ialog.log(level=logging.CRITICAL, 'get out of dodge') ialog.disable(level=logging.INFO) ialog.basicConfig(filename='/var/log/invokeai.log') Internally, the invokeai logging module creates a new default logger named "invokeai" so that its logging does not interfere with other module's use of the vanilla logging module. So `logging.error("foo")` will go through the regular logging path and not add the additional message decorations. For more control, the logging module's object-oriented logging style is also supported. The API is identical to the vanilla logging usage. In fact, the only thing that has changed is that the getLogger() method adds a custom formatter to the log messages. import logging from invokeai.backend.util.logging import InvokeAILogger logger = InvokeAILogger.getLogger(__name__) fh = logging.FileHandler('/var/invokeai.log') logger.addHandler(fh) logger.critical('this will be logged to both the console and the log file')
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def error(msg, *args, **kwargs):
InvokeAILogger.getLogger().error(msg, *args, **kwargs)
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add logging support This commit adds invokeai.backend.util.logging, which provides support for formatted console and logfile messages that follow the status reporting conventions of earlier InvokeAI versions. Examples: ### A critical error (logging.CRITICAL) *** A non-fatal error (logging.ERROR) ** A warning (logging.WARNING) >> Informational message (logging.INFO) | Debugging message (logging.DEBUG) This style logs everything through a single logging object and is identical to using Python's `logging` module. The commonly-used module-level logging functions are implemented as simple pass-thrus to logging: import invokeai.backend.util.logging as ialog ialog.debug('this is a debugging message') ialog.info('this is a informational message') ialog.log(level=logging.CRITICAL, 'get out of dodge') ialog.disable(level=logging.INFO) ialog.basicConfig(filename='/var/log/invokeai.log') Internally, the invokeai logging module creates a new default logger named "invokeai" so that its logging does not interfere with other module's use of the vanilla logging module. So `logging.error("foo")` will go through the regular logging path and not add the additional message decorations. For more control, the logging module's object-oriented logging style is also supported. The API is identical to the vanilla logging usage. In fact, the only thing that has changed is that the getLogger() method adds a custom formatter to the log messages. import logging from invokeai.backend.util.logging import InvokeAILogger logger = InvokeAILogger.getLogger(__name__) fh = logging.FileHandler('/var/invokeai.log') logger.addHandler(fh) logger.critical('this will be logged to both the console and the log file')
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def critical(msg, *args, **kwargs):
InvokeAILogger.getLogger().critical(msg, *args, **kwargs)
def log(level, msg, *args, **kwargs):
InvokeAILogger.getLogger().log(level, msg, *args, **kwargs)
def disable(level=logging.CRITICAL):
InvokeAILogger.getLogger().disable(level)
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def basicConfig(**kwargs):
InvokeAILogger.getLogger().basicConfig(**kwargs)
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def getLogger(name: str = None) -> logging.Logger:
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return InvokeAILogger.getLogger(name)
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class InvokeAILogFormatter(logging.Formatter):
'''
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Custom Formatting for the InvokeAI Logger
'''
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# Color Codes
grey = "\x1b[38;20m"
yellow = "\x1b[33;20m"
red = "\x1b[31;20m"
bold_red = "\x1b[31;1m"
reset = "\x1b[0m"
# Log Format
format = "[%(asctime)s]::[%(name)s]::%(levelname)s --> %(message)s"
## More Formatting Options: %(pathname)s, %(filename)s, %(module)s, %(lineno)d
# Format Map
FORMATS = {
logging.DEBUG: grey + format + reset,
logging.INFO: grey + format + reset,
logging.WARNING: yellow + format + reset,
logging.ERROR: red + format + reset,
logging.CRITICAL: bold_red + format + reset
}
def format(self, record):
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log_fmt = self.FORMATS.get(record.levelno)
formatter = logging.Formatter(log_fmt, datefmt="%d-%m-%Y %H:%M:%S")
return formatter.format(record)
class InvokeAILogger(object):
loggers = dict()
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@classmethod
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def getLogger(self, name: str = 'InvokeAI') -> logging.Logger:
if name not in self.loggers:
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
fmt = InvokeAILogFormatter()
ch.setFormatter(fmt)
logger.addHandler(ch)
self.loggers[name] = logger
return self.loggers[name]