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Remove default model cache sizes from model_cache_default.py. These defaults were misleading, because the config defaults take precedence over them.

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This commit is contained in:
Ryan Dick 2024-08-27 14:31:28 +00:00
parent 3e569c8312
commit e064377c05
1 changed files with 4 additions and 11 deletions
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15
invokeai/backend/model_manager/load/model_cache/model_cache_default.py
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@ -40,15 +40,8 @@ from invokeai.backend.model_manager.load.model_util import calc_model_size_by_da
from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.devices import TorchDevice
from invokeai.backend.util.logging import InvokeAILogger from invokeai.backend.util.logging import InvokeAILogger
# Maximum size of the cache, in gigs # Size of a GB in bytes.
# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously GIG = 2**30
DEFAULT_MAX_CACHE_SIZE = 6.0
# amount of GPU memory to hold in reserve for use by generations (GB)
DEFAULT_MAX_VRAM_CACHE_SIZE = 2.75
# actual size of a gig
GIG = 1073741824
# Size of a MB in bytes. # Size of a MB in bytes.
MB = 2**20 MB = 2**20
@ -59,8 +52,8 @@ class ModelCache(ModelCacheBase[AnyModel]):
def __init__( def __init__(
self, self,
max_cache_size: float = DEFAULT_MAX_CACHE_SIZE, max_cache_size: float,
max_vram_cache_size: float = DEFAULT_MAX_VRAM_CACHE_SIZE, max_vram_cache_size: float,
execution_device: torch.device = torch.device("cuda"), execution_device: torch.device = torch.device("cuda"),
storage_device: torch.device = torch.device("cpu"), storage_device: torch.device = torch.device("cpu"),
precision: torch.dtype = torch.float16, precision: torch.dtype = torch.float16,