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Remove unused constructor params from ModelCache.

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This commit is contained in:
Ryan Dick 2024-08-27 14:33:56 +00:00
parent e064377c05
commit 5284a870b0
1 changed files with 0 additions and 5 deletions
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5
invokeai/backend/model_manager/load/model_cache/model_cache_default.py
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@ -48,8 +48,6 @@ MB = 2**20
class ModelCache(ModelCacheBase[AnyModel]):
"""Implementation of ModelCacheBase."""
def __init__(
self,
max_cache_size: float,
@ -57,9 +55,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
execution_device: torch.device = torch.device("cuda"),
storage_device: torch.device = torch.device("cpu"),
precision: torch.dtype = torch.float16,
sequential_offload: bool = False,
lazy_offloading: bool = True,
sha_chunksize: int = 16777216,
log_memory_usage: bool = False,
logger: Optional[Logger] = None,
):
@ -71,7 +67,6 @@ class ModelCache(ModelCacheBase[AnyModel]):
:param storage_device: Torch device to save inactive model in [torch.device('cpu')]
:param precision: Precision for loaded models [torch.float16]
:param lazy_offloading: Keep model in VRAM until another model needs to be loaded
:param sequential_offload: Conserve VRAM by loading and unloading each stage of the pipeline sequentially
:param log_memory_usage: If True, a memory snapshot will be captured before and after every model cache
operation, and the result will be logged (at debug level). There is a time cost to capturing the memory
snapshots, so it is recommended to disable this feature unless you are actively inspecting the model cache's