⚡️ Speed up method Unknown_Config.from_model_on_disk by 147%
#150
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📄 147% (1.47x) speedup for
Unknown_Config.from_model_on_diskininvokeai/backend/model_manager/configs/unknown.py⏱️ Runtime :
9.51 microseconds→3.85 microseconds(best of41runs)📝 Explanation and details
The optimization replaces Python's
deepcopy()with the much fasterdict.copy()method when cloningoverride_fields.Key Change: Line 19 changed from
cloned_override_fields = deepcopy(override_fields)tocloned_override_fields = override_fields.copy().Why This Works: The function only needs to remove three specific keys (
"base","type","format") from the cloned dictionary without modifying any nested values. A shallow copy is sufficient since the code doesn't mutate any nested objects withinoverride_fields- it only removes top-level keys.Performance Impact: The line profiler shows the
deepcopyoperation took 28.97ms (95.5% of total runtime), whiledict.copy()takes only 0.053ms (3.6% of total runtime) - a 540x improvement on that specific line. This translates to an overall 146% speedup (9.51μs → 3.85μs).Why
deepcopyis Slow:deepcopy()recursively traverses the entire object graph, creating new instances of all nested objects even when unnecessary.dict.copy()simply creates a new dictionary with references to the same values, which is exactly what's needed here.Correctness: The optimization maintains identical behavior since the original
override_fieldsparameter is never mutated after the copy, making the deep vs shallow copy distinction irrelevant for this use case.This optimization is particularly valuable for model configuration workflows where this method might be called frequently during model loading and discovery operations.
✅ Correctness verification report:
🌀 Generated Regression Tests and Runtime
from copy import deepcopy
--- Function to test (copied from prompt, with simulated dependencies) ---
from typing import Any, Literal
imports
import pytest
from invokeai.backend.model_manager.configs.unknown import Unknown_Config
from typing_extensions import Self
--- Simulate dependencies for the function ---
Simulate enums from taxonomy
class BaseModelType:
Unknown = "unknown"
class ModelType:
Unknown = "unknown"
class ModelFormat:
Unknown = "unknown"
Simulate ModelOnDisk class (minimal stub)
class ModelOnDisk:
def init(self, path, metadata=None):
self.path = path
self.metadata = metadata or {}
Simulate Config_Base (minimal stub)
class Config_Base:
pass
from invokeai.backend.model_manager.configs.unknown import Unknown_Config
--- Unit tests ---
1. Basic Test Cases
#------------------------------------------------
from copy import deepcopy
Simulate required enums and classes
from enum import Enum
from typing import Any, Dict
imports
import pytest
from invokeai.backend.model_manager.configs.unknown import Unknown_Config
Simulate the enums used in Unknown_Config
class BaseModelType(str, Enum):
Unknown = "unknown"
Other = "other"
class ModelType(str, Enum):
Unknown = "unknown"
Other = "other"
class ModelFormat(str, Enum):
Unknown = "unknown"
Other = "other"
Simulate ModelOnDisk class
class ModelOnDisk:
# Minimal implementation for testing
def init(self, path: str, metadata: Dict[str, Any] = None):
self.path = path
self.metadata = metadata or {}
Simulate Config_Base
class Config_Base:
def init(self, **kwargs):
for k, v in kwargs.items():
setattr(self, k, v)
from invokeai.backend.model_manager.configs.unknown import Unknown_Config
----------------------
UNIT TESTS START HERE
----------------------
1. Basic Test Cases
def test_override_fields_with_non_string_keys():
"""Test that non-string keys in override_fields raise a TypeError."""
mod = ModelOnDisk(path="/models/model7.pt")
override_fields = {1: "integer_key", "foo": "bar"}
with pytest.raises(TypeError):
# The constructor expects keyword arguments as strings, so this should fail
Unknown_Config.from_model_on_disk(mod, override_fields) # 9.51μs -> 3.85μs (147% faster)
To edit these changes
git checkout codeflash/optimize-Unknown_Config.from_model_on_disk-mhvtfb8pand push.