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https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
fix merge conflicts with main
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@ -31,15 +31,12 @@ import torch
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from invokeai.backend.model_manager import AnyModel, SubModelType
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from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
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from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
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from invokeai.backend.util.devices import choose_torch_device
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from invokeai.backend.util.devices import TorchDevice
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from invokeai.backend.util.logging import InvokeAILogger
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from .model_cache_base import CacheRecord, CacheStats, ModelCacheBase, ModelLockerBase
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from .model_locker import ModelLocker
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if choose_torch_device() == torch.device("mps"):
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from torch import mps
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# Maximum size of the cache, in gigs
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# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
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DEFAULT_MAX_CACHE_SIZE = 6.0
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@ -245,9 +242,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
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f"Removing {cache_entry.key} from VRAM to free {(cache_entry.size/GIG):.2f}GB; vram free = {(torch.cuda.memory_allocated()/GIG):.2f}GB"
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)
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torch.cuda.empty_cache()
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if choose_torch_device() == torch.device("mps"):
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mps.empty_cache()
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TorchDevice.empty_cache()
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def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
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"""Move model into the indicated device.
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@ -417,10 +412,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
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self.stats.cleared = models_cleared
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gc.collect()
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torch.cuda.empty_cache()
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if choose_torch_device() == torch.device("mps"):
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mps.empty_cache()
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TorchDevice.empty_cache()
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self.logger.debug(f"After making room: cached_models={len(self._cached_models)}")
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def _delete_cache_entry(self, cache_entry: CacheRecord[AnyModel]) -> None:
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