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https://github.com/ostris/ai-toolkit.git
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Feat: Wandb logging (#95)
* wandb logging * fix: start logging before train loop * chore: add wandb dir to gitignore * fix: wrap wandb functions * fix: forget to send last samples * chore: use valid type * chore: use None when not type-checking * chore: resolved complicated logic * fix: follow log_every --------- Co-authored-by: Plat <github@p1at.dev> Co-authored-by: Jaret Burkett <jaretburkett@gmail.com>
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@@ -13,7 +13,9 @@ SaveFormat = Literal['safetensors', 'diffusers']
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if TYPE_CHECKING:
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from toolkit.guidance import GuidanceType
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from toolkit.logging import EmptyLogger
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else:
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EmptyLogger = None
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class SaveConfig:
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def __init__(self, **kwargs):
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@@ -27,11 +29,13 @@ class SaveConfig:
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self.hf_repo_id: Optional[str] = kwargs.get("hf_repo_id", None)
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self.hf_private: Optional[str] = kwargs.get("hf_private", False)
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class LogingConfig:
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class LoggingConfig:
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def __init__(self, **kwargs):
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self.log_every: int = kwargs.get('log_every', 100)
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self.verbose: bool = kwargs.get('verbose', False)
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self.use_wandb: bool = kwargs.get('use_wandb', False)
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self.project_name: str = kwargs.get('project_name', 'ai-toolkit')
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self.run_name: str = kwargs.get('run_name', None)
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class SampleConfig:
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@@ -655,6 +659,7 @@ class GenerateImageConfig:
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extra_kwargs: dict = None, # extra data to save with prompt file
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refiner_start_at: float = 0.5, # start at this percentage of a step. 0.0 to 1.0 . 1.0 is the end
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extra_values: List[float] = None, # extra values to save with prompt file
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logger: Optional[EmptyLogger] = None,
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):
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self.width: int = width
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self.height: int = height
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@@ -712,6 +717,8 @@ class GenerateImageConfig:
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self.height = max(64, self.height - self.height % 8) # round to divisible by 8
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self.width = max(64, self.width - self.width % 8) # round to divisible by 8
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self.logger = logger
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def set_gen_time(self, gen_time: int = None):
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if gen_time is not None:
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self.gen_time = gen_time
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@@ -855,3 +862,9 @@ class GenerateImageConfig:
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):
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# this is called after prompt embeds are encoded. We can override them in the future here
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pass
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def log_image(self, image, count: int = 0, max_count=0):
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if self.logger is None:
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return
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self.logger.log_image(image, count, self.prompt)
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84
toolkit/logging.py
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84
toolkit/logging.py
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@@ -0,0 +1,84 @@
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from typing import OrderedDict, Optional
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from PIL import Image
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from toolkit.config_modules import LoggingConfig
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# Base logger class
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# This class does nothing, it's just a placeholder
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class EmptyLogger:
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def __init__(self, *args, **kwargs) -> None:
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pass
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# start logging the training
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def start(self):
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pass
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# collect the log to send
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def log(self, *args, **kwargs):
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pass
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# send the log
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def commit(self, step: Optional[int] = None):
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pass
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# log image
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def log_image(self, *args, **kwargs):
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pass
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# finish logging
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def finish(self):
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pass
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# Wandb logger class
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# This class logs the data to wandb
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class WandbLogger(EmptyLogger):
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def __init__(self, project: str, run_name: str | None, config: OrderedDict) -> None:
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self.project = project
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self.run_name = run_name
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self.config = config
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def start(self):
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try:
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import wandb
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except ImportError:
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raise ImportError("Failed to import wandb. Please install wandb by running `pip install wandb`")
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# send the whole config to wandb
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run = wandb.init(project=self.project, name=self.run_name, config=self.config)
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self.run = run
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self._log = wandb.log # log function
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self._image = wandb.Image # image object
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def log(self, *args, **kwargs):
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# when commit is False, wandb increments the step,
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# but we don't want that to happen, so we set commit=False
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self._log(*args, **kwargs, commit=False)
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def commit(self, step: Optional[int] = None):
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# after overall one step is done, we commit the log
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# by log empty object with commit=True
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self._log({}, step=step, commit=True)
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def log_image(
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self,
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image: Image,
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id, # sample index
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caption: str | None = None, # positive prompt
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*args,
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**kwargs,
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):
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# create a wandb image object and log it
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image = self._image(image, caption=caption, *args, **kwargs)
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self._log({f"sample_{id}": image}, commit=False)
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def finish(self):
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self.run.finish()
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# create logger based on the logging config
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def create_logger(logging_config: LoggingConfig, all_config: OrderedDict):
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if logging_config.use_wandb:
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project_name = logging_config.project_name
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run_name = logging_config.run_name
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return WandbLogger(project=project_name, run_name=run_name, config=all_config)
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else:
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return EmptyLogger()
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@@ -1318,6 +1318,7 @@ class StableDiffusion:
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).images[0]
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gen_config.save_image(img, i)
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gen_config.log_image(img, i)
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if self.adapter is not None and isinstance(self.adapter, ReferenceAdapter):
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self.adapter.clear_memory()
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