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Running on Zero
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99adaa0 ca9a89c 99adaa0 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 | from __future__ import annotations
import importlib.util
import pickle
import sys
import tempfile
import threading
import types
import unittest
from pathlib import Path
from unittest import mock
from core.task_scheduler import TaskCancelledError
ROOT = Path(__file__).resolve().parents[1]
class _LockedProgress:
def __init__(self, *args, **kwargs):
self.lock = threading.Lock()
self.updates = []
def __call__(self, value, desc=None):
self.updates.append((value, desc))
class _Assembler:
def __init__(self, after_assembly=None):
self.after_assembly = after_assembly
def assemble(self, values):
self.ui_values = values
if self.after_assembly:
self.after_assembly()
return {"1": {"class_type": "TestNode", "inputs": {"seed": values["seed"]}}}
def _module(name, **attributes):
module = types.ModuleType(name)
module.__dict__.update(attributes)
return module
class GpuBoundaryTests(unittest.TestCase):
"""执行真实 pipeline 调用链，只替换下载、推理依赖和 GPU 传输。"""
def setUp(self):
output_dir = self.enterContext(tempfile.TemporaryDirectory())
self.payloads = []
self.assemblers = []
self.after_assembly = None
self.download = mock.Mock()
self.release_models = mock.Mock()
self.execute_workflow = mock.Mock(
return_value=types.SimpleNamespace(shape=(0,))
)
def gpu_decorator(**_options):
def decorate(function):
def run(*args, **kwargs):
# 真正序列化入参，不能像 UI 烟测那样直接跳过生成调用。
args, kwargs = pickle.loads(pickle.dumps((args, kwargs)))
self.payloads.append(kwargs)
return function(*args, **kwargs)
return run
return decorate
def create_assembler(*_args, **_kwargs):
assembler = _Assembler(self.after_assembly)
self.assemblers.append(assembler)
return assembler
prepared_keys = (
"temp_files_to_clean", "active_loras_for_gpu", "active_loras_for_meta",
"active_controlnets", "active_anima_controlnets", "active_diffsynth_controlnets",
"active_ipadapters", "active_flux1_ipadapters", "active_sd3_ipadapters",
"active_styles", "active_reference_latents", "active_hidream_o1_reference",
"active_conditioning",
)
base_name = "core.pipelines.base_pipeline"
pipeline_name = "core.pipelines.sd_image_pipeline"
stubs = {
"gradio": _module("gradio", Error=RuntimeError, Progress=_LockedProgress),
"spaces": _module("spaces", GPU=gpu_decorator),
"torch": _module("torch"),
"imageio": _module("imageio"),
"numpy": _module("numpy"),
"core.model_manager": _module(
"core.model_manager",
model_manager=types.SimpleNamespace(ensure_models_downloaded=self.download),
release_loaded_models=self.release_models,
),
"core.workflow_assembler": _module(
"core.workflow_assembler", WorkflowAssembler=create_assembler
),
"imagegen_utils.app_utils": _module(
"imagegen_utils.app_utils", sanitize_prompt=lambda value: value
),
"core.pipelines.pipeline_input_processor": _module(
"core.pipelines.pipeline_input_processor",
process_pipeline_inputs=lambda *_: {key: [] for key in prepared_keys},
),
"core.pipelines.workflow_executor": _module(
"core.pipelines.workflow_executor",
WorkflowExecutor=types.SimpleNamespace(execute_workflow=self.execute_workflow),
),
}
specs = []
for name in (base_name, pipeline_name):
spec = importlib.util.spec_from_file_location(
name, ROOT / "core" / "pipelines" / f"{name.rsplit('.', 1)[1]}.py"
)
stubs[name] = importlib.util.module_from_spec(spec)
specs.append(spec)
self.enterContext(mock.patch.dict(sys.modules, stubs))
for spec in specs:
spec.loader.exec_module(stubs[spec.name])
self.module = stubs[pipeline_name]
self.module.OUTPUT_DIR = output_dir
self.pipeline = self.module.SdImagePipeline()
def inputs(self, **overrides):
values = {
"task_type": "txt2img",
"model_display_name": "circlestone-labs/Anima-Turbo-v1.0",
"positive_prompt": "测试图片",
"negative_prompt": "",
"seed": 42,
"batch_size": 1,
"num_inference_steps": 4,
"guidance_scale": 1.0,
"sampler": "euler",
"scheduler": "simple",
"width": 64,
"height": 64,
"denoise": 1.0,
}
values.update(overrides)
return values
def test_repeated_ui_calls_serialize_and_preserve_model_release(self):
for release in (True, False):
with self.subTest(release=release):
cancellation = threading.Event()
values = self.inputs(
_cancel_event=cancellation, _release_models_after_run=release
)
progress = _LockedProgress()
self.assertEqual(self.pipeline.run(values, progress), [])
payload = self.payloads[-1]
self.assertEqual(set(payload), {"ui_inputs", "loras_string", "workflow"})
self.assertNotIn("_cancel_event", payload["ui_inputs"])
self.assertEqual(payload["ui_inputs"]["_release_models_after_run"], release)
self.assertIs(values["_cancel_event"], cancellation)
self.assertIs(self.assemblers[-1].ui_values["_cancel_event"], cancellation)
self.assertTrue(progress.updates)
self.assertEqual(len(self.payloads), 2)
self.release_models.assert_called_once_with()
def test_request_without_cancel_event_serializes(self):
self.pipeline.run(self.inputs(), _LockedProgress())
self.assertNotIn("_cancel_event", self.payloads[0]["ui_inputs"])
self.release_models.assert_not_called()
def test_unsupported_stale_reference_does_not_block_img2img(self):
from PIL import Image
self.pipeline.run(self.inputs(task_type="img2img", img2img_image=Image.new("RGB", (64, 64)), qwen_image_edit_data=[Image.new("RGB", (32, 32))], positive_prompt="保留图1"), _LockedProgress())
self.download.assert_called_once()
self.assertEqual(self.payloads[0]["ui_inputs"]["qwen_image_edit_data"], [])
self.assertEqual(self.payloads[0]["ui_inputs"]["positive_prompt"], "保留image 1")
def test_invalid_numbered_reference_rejected_before_download_and_gpu(self):
with self.assertRaisesRegex(RuntimeError, "本次只有 0"):
self.pipeline.run(self.inputs(positive_prompt="img2"), _LockedProgress())
self.download.assert_not_called()
self.assertEqual(self.payloads, [])
def test_cancellation_after_download_stays_on_cpu(self):
cancellation = threading.Event()
self.download.side_effect = lambda *args, **kwargs: cancellation.set()
with self.assertRaises(TaskCancelledError):
self.pipeline.run(self.inputs(_cancel_event=cancellation), _LockedProgress())
self.assertEqual(self.payloads, [])
self.execute_workflow.assert_not_called()
def test_cancellation_after_assembly_stays_on_cpu(self):
cancellation = threading.Event()
self.after_assembly = cancellation.set
with self.assertRaises(TaskCancelledError):
self.pipeline.run(self.inputs(_cancel_event=cancellation), _LockedProgress())
self.assertEqual(self.payloads, [])
self.execute_workflow.assert_not_called()
def test_gpu_failure_still_releases_model_state(self):
self.execute_workflow.side_effect = RuntimeError("sampling failed")
with self.assertRaisesRegex(RuntimeError, "sampling failed"):
self.pipeline.run(
self.inputs(_cancel_event=threading.Event()), _LockedProgress()
)
self.release_models.assert_called_once_with()
if __name__ == "__main__":
unittest.main()
|