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https://github.com/invoke-ai/InvokeAI
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Auto-format model_cache.py.
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@ -205,7 +205,8 @@ class ModelCache(object):
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cache_entry = self._cached_models.get(key, None)
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if cache_entry is None:
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self.logger.info(
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f"Loading model {model_path}, type {base_model.value}:{model_type.value}{':'+submodel.value if submodel else ''}"
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f"Loading model {model_path}, type"
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f" {base_model.value}:{model_type.value}{':'+submodel.value if submodel else ''}"
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)
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if self.stats:
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self.stats.misses += 1
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@ -339,7 +340,8 @@ class ModelCache(object):
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locked_models += 1
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self.logger.debug(
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f"Current VRAM/RAM usage: {vram}/{ram}; cached_models/loaded_models/locked_models/ = {cached_models}/{loaded_models}/{locked_models}"
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f"Current VRAM/RAM usage: {vram}/{ram}; cached_models/loaded_models/locked_models/ ="
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f" {cached_models}/{loaded_models}/{locked_models}"
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)
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def _cache_size(self) -> int:
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@ -354,7 +356,8 @@ class ModelCache(object):
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if current_size + bytes_needed > maximum_size:
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self.logger.debug(
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f"Max cache size exceeded: {(current_size/GIG):.2f}/{self.max_cache_size:.2f} GB, need an additional {(bytes_needed/GIG):.2f} GB"
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f"Max cache size exceeded: {(current_size/GIG):.2f}/{self.max_cache_size:.2f} GB, need an additional"
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f" {(bytes_needed/GIG):.2f} GB"
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)
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self.logger.debug(f"Before unloading: cached_models={len(self._cached_models)}")
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@ -387,7 +390,8 @@ class ModelCache(object):
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device = cache_entry.model.device if hasattr(cache_entry.model, "device") else None
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self.logger.debug(
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f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded}, refs: {refs}"
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f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded},"
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f" refs: {refs}"
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)
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# 2 refs:
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