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Remove logic to update model cache size estimates dynamically.

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This commit is contained in:
Ryan Dick 2023-10-03 12:03:22 -04:00
parent b9fd2e9e76
commit 4580ba0d87
1 changed files with 0 additions and 19 deletions
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19
invokeai/backend/model_management/model_cache.py
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@ -305,25 +305,6 @@ class ModelCache(object):
f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
)
# Now, we will update our size estimate for `cache_entry` based on the change in VRAM usage. We only use the
# change in VRAM usage, not the change in RAM usage, because it is a more accurate measurement. The VRAM
# usage measurement only includes the memory used by PyTorch tensors, whereas the RAM usage measurement is
# of total process memory and is influenced by other factors.
# We want to err on the side of over-estimating the model's size, so we only update our estimate if the new
# information suggests that the model is larger than we previously thought.
if vram_change > cache_entry.size:
self.logger.info(
f"Updating the cache size estimate for model '{key}'. {(cache_entry.size/GIG):.2f}GB ->"
f" {(vram_change/GIG):.2f}GB."
)
cache_entry.size = vram_change
self.logger.info(
"Clearing models from cache, if necessary, after updating a model's size estimate."
)
self._make_cache_room(0)
class ModelLocker(object):
def __init__(self, cache, key, model, gpu_load, size_needed):
"""