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feat: optimize performance lora filtering in metadata (#3048)

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* feat: add remove_performance_lora method

* feat: use class PerformanceLoRA instead of strings in config

* refactor: cleanup flags, use __member__ to check if enums contains key

* feat: only filter lora of selected performance instead of all performance LoRAs

* fix: disable intermediate results for all restricted performances

too fast for Gradio, which becomes a bottleneck

* refactor: rename parse_json to to_json, rename parse_string to to_string

* feat: use speed steps as default instead of hardcoded 30

* feat: add method to_steps to Performance

* refactor: remove method ordinal_suffix, not needed anymore

* feat: only filter lora of selected performance instead of all performance LoRAs

both metadata and history log

* feat: do not filter LoRAs in metadata parser but rather in metadata load action
This commit is contained in:
Manuel Schmid
2024-05-30 16:14:28 +02:00
committed by GitHub
parent 3ef663c5b7
commit 4e658bb63a
8 changed files with 144 additions and 53 deletions
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tests/test_utils.py
+57 -1
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@@ -1,5 +1,7 @@
import os
import unittest
import modules.flags
from modules import util
@@ -77,5 +79,59 @@ class TestUtils(unittest.TestCase):
for test in test_cases:
prompt, loras, loras_limit, skip_file_check = test["input"]
expected = test["output"]
actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit, skip_file_check=skip_file_check)
actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit,
skip_file_check=skip_file_check)
self.assertEqual(expected, actual)
def test_can_parse_tokens_and_strip_performance_lora(self):
lora_filenames = [
'hey-lora.safetensors',
modules.flags.PerformanceLoRA.EXTREME_SPEED.value,
modules.flags.PerformanceLoRA.LIGHTNING.value,
os.path.join('subfolder', modules.flags.PerformanceLoRA.HYPER_SD.value)
]
test_cases = [
{
"input": ("some prompt, <lora:hey-lora:0.4>", [], 5, True, modules.flags.Performance.QUALITY),
"output": (
[('hey-lora.safetensors', 0.4)],
'some prompt'
),
},
{
"input": ("some prompt, <lora:hey-lora:0.4>", [], 5, True, modules.flags.Performance.SPEED),
"output": (
[('hey-lora.safetensors', 0.4)],
'some prompt'
),
},
{
"input": ("some prompt, <lora:sdxl_lcm_lora:1>, <lora:hey-lora:0.4>", [], 5, True, modules.flags.Performance.EXTREME_SPEED),
"output": (
[('hey-lora.safetensors', 0.4)],
'some prompt'
),
},
{
"input": ("some prompt, <lora:sdxl_lightning_4step_lora:1>, <lora:hey-lora:0.4>", [], 5, True, modules.flags.Performance.LIGHTNING),
"output": (
[('hey-lora.safetensors', 0.4)],
'some prompt'
),
},
{
"input": ("some prompt, <lora:sdxl_hyper_sd_4step_lora:1>, <lora:hey-lora:0.4>", [], 5, True, modules.flags.Performance.HYPER_SD),
"output": (
[('hey-lora.safetensors', 0.4)],
'some prompt'
),
}
]
for test in test_cases:
prompt, loras, loras_limit, skip_file_check, performance = test["input"]
lora_filenames = modules.util.remove_performance_lora(lora_filenames, performance)
expected = test["output"]
actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit, lora_filenames=lora_filenames)
self.assertEqual(expected, actual)