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Running on Zero
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8a28a8d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | from __future__ import annotations
import threading
import unittest
from PIL import Image
from core.execution_plan import (
MODE_MODEL_PK,
MODE_MULTI_INDEPENDENT,
MODE_MULTI_MODEL_GRID,
MODE_MULTI_REFERENCE,
ExecutionPlanError,
PlannedGeneration,
build_execution_plan,
execute_generation_plan,
)
def base_inputs(**overrides):
values = {
"task_type": "txt2img",
"model_display_name": "Krea-2-Turbo",
"positive_prompt": "一只猫",
"negative_prompt": "",
"seed": -1,
"batch_size": 1,
"num_inference_steps": 13,
"guidance_scale": 2.5,
"sampler": "euler",
"scheduler": "simple",
"width": 1024,
"height": 1024,
}
values.update(overrides)
return values
class ExecutionPlanTests(unittest.TestCase):
def test_pk_resolves_one_seed_and_marks_only_the_model_boundary(self):
plan = build_execution_plan(
base_inputs(lora_data=["Civitai", "123", 1.0, None]),
mode=MODE_MODEL_PK,
extra_models=["Krea-2-Raw"],
use_model_defaults=True,
)
self.assertEqual(len(plan), 2)
self.assertEqual(plan[0].inputs["seed"], plan[1].inputs["seed"])
self.assertGreaterEqual(plan[0].inputs["seed"], 0)
self.assertEqual(plan[0].inputs["num_inference_steps"], 8)
self.assertEqual(plan[1].inputs["num_inference_steps"], 52)
self.assertTrue(plan[0].inputs["_release_models_after_run"])
self.assertNotIn("_release_models_after_run", plan[1].inputs)
self.assertEqual(plan[0].inputs["lora_data"], [])
self.assertEqual(plan[1].inputs["lora_data"], [])
def test_independent_images_keep_user_sampling_values(self):
images = [Image.new("RGB", (32, 32)), Image.new("RGB", (48, 32))]
plan = build_execution_plan(
base_inputs(task_type="img2img"),
mode=MODE_MULTI_INDEPENDENT,
images=images,
use_model_defaults=True,
)
self.assertEqual(len(plan), 2)
self.assertEqual([item.inputs["img2img_image"] for item in plan], images)
self.assertTrue(all(item.inputs["num_inference_steps"] == 13 for item in plan))
def test_image_model_grid_groups_inputs_by_model(self):
images = [Image.new("RGB", (32, 32)), Image.new("RGB", (48, 32))]
plan = build_execution_plan(
base_inputs(task_type="img2img"),
mode=MODE_MULTI_MODEL_GRID,
extra_models=["Krea-2-Raw"],
images=images,
)
self.assertEqual(
[item.inputs["model_display_name"] for item in plan],
["Krea-2-Turbo", "Krea-2-Turbo", "Krea-2-Raw", "Krea-2-Raw"],
)
self.assertNotIn("_release_models_after_run", plan[0].inputs)
self.assertTrue(plan[1].inputs["_release_models_after_run"])
def test_reference_fusion_uses_edit_checkpoint_chain(self):
images = [Image.new("RGB", (32, 32)), Image.new("RGB", (32, 32))]
edit_model = "lightx2v/Qwen-Image-Edit-2511-Lightning"
plan = build_execution_plan(
base_inputs(model_display_name=edit_model),
mode=MODE_MULTI_REFERENCE,
images=images,
)
self.assertEqual(plan[0].inputs["qwen_image_edit_data"], images)
with self.assertRaisesRegex(ExecutionPlanError, "编辑/多模态模型"):
build_execution_plan(
base_inputs(
model_display_name="lightx2v/Qwen-Image-2512-Lightning"
),
mode=MODE_MULTI_REFERENCE,
images=images,
)
def test_reference_fusion_is_not_img2img(self):
with self.assertRaisesRegex(ExecutionPlanError, "文生图"):
build_execution_plan(
base_inputs(task_type="img2img"),
mode=MODE_MULTI_REFERENCE,
images=[Image.new("RGB", (32, 32))],
)
def test_executor_keeps_partial_results_and_failure_context(self):
plan = [
PlannedGeneration({"id": 1}, "模型一"),
PlannedGeneration({"id": 2}, "模型二"),
]
def generate(inputs, _progress):
if inputs["id"] == 2:
raise RuntimeError("显存不足")
return ["one.png"]
gallery, summary = execute_generation_plan(plan, generate)
self.assertEqual(gallery, [("one.png", "模型一")])
self.assertIn("模型二：显存不足", summary)
def test_executor_stops_before_next_case_after_cancel(self):
cancellation = threading.Event()
cancellation.set()
with self.assertRaisesRegex(ExecutionPlanError, "已取消"):
execute_generation_plan(
[PlannedGeneration({}, "任务")],
lambda *_: ["unexpected.png"],
cancel_event=cancellation,
)
def test_cancel_after_success_keeps_partial_gallery(self):
cancellation = threading.Event()
called = []
def generate(inputs, _progress):
called.append(inputs["id"])
cancellation.set()
return ["kept.png"]
gallery, summary = execute_generation_plan(
[
PlannedGeneration({"id": 1}, "任务一"),
PlannedGeneration({"id": 2}, "任务二"),
],
generate,
cancel_event=cancellation,
)
self.assertEqual(called, [1])
self.assertEqual(gallery, [("kept.png", "任务一")])
self.assertIn("已保留成功结果", summary)
if __name__ == "__main__":
unittest.main()
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