Merge github.com:invoke-ai/InvokeAI into lstein/bugfix/model-install-thread-stop

invokeai/app/services/download/download_default.py

@@ -87,6 +87,8 @@ class DownloadQueueService(DownloadQueueServiceBase):
                 self._queue.queue.clear()
             self.join()  # wait for all active jobs to finish
             self._stop_event.set()
+            for thread in self._worker_pool:
+                thread.join()
             self._worker_pool.clear()
 
     def submit_download_job(

invokeai/app/services/model_install/model_install_default.py

@@ -34,6 +34,7 @@ from invokeai.backend.model_manager.config import (
 from invokeai.backend.model_manager.metadata import (
     AnyModelRepoMetadata,
     HuggingFaceMetadataFetch,
+    ModelMetadataFetchBase,
     ModelMetadataWithFiles,
     RemoteModelFile,
 )
@@ -92,6 +93,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self._download_cache: Dict[AnyHttpUrl, ModelInstallJob] = {}
         self._running = False
         self._session = session
+        self._install_thread: Optional[threading.Thread] = None
         self._next_job_id = 0
 
     @property
@@ -126,6 +128,8 @@ class ModelInstallService(ModelInstallServiceBase):
             self._stop_event.set()
             self._clear_pending_jobs()
             self._download_cache.clear()
+            assert self._install_thread is not None
+            self._install_thread.join()
             self._running = False
 
     def _clear_pending_jobs(self) -> None:
@@ -275,6 +279,7 @@ class ModelInstallService(ModelInstallServiceBase):
             if timeout > 0 and time.time() - start > timeout:
                 raise TimeoutError("Timeout exceeded")
         self._install_queue.join()
+
         return self._install_jobs
 
     def cancel_job(self, job: ModelInstallJob) -> None:
@@ -415,15 +420,16 @@ class ModelInstallService(ModelInstallServiceBase):
     # Internal functions that manage the installer threads
     # --------------------------------------------------------------------------------------------
     def _start_installer_thread(self) -> None:
-        threading.Thread(target=self._install_next_item, daemon=True).start()
+        self._install_thread = threading.Thread(target=self._install_next_item, daemon=True)
+        self._install_thread.start()
         self._running = True
 
     def _install_next_item(self) -> None:
-        done = False
+        self._logger.info(f"Installer thread {threading.get_ident()} starting")
-        while not done:
+        while True:
             if self._stop_event.is_set():
-                done = True
+                break
-                continue
+            self._logger.info(f"Installer thread {threading.get_ident()} running")
             try:
                 job = self._install_queue.get(timeout=1)
             except Empty:
@@ -436,9 +442,25 @@ class ModelInstallService(ModelInstallServiceBase):
                 elif job.errored:
                     self._signal_job_errored(job)
 
-                elif (
+                elif job.waiting or job.downloads_done:
-                    job.waiting or job.downloads_done
+                    self._register_or_install(job)
-                ):  # local jobs will be in waiting state, remote jobs will be downloading state
+
+            except InvalidModelConfigException as excp:
+                self._set_error(job, excp)
+
+            except (OSError, DuplicateModelException) as excp:
+                self._set_error(job, excp)
+
+            finally:
+                # if this is an install of a remote file, then clean up the temporary directory
+                if job._install_tmpdir is not None:
+                    rmtree(job._install_tmpdir)
+                self._install_completed_event.set()
+                self._install_queue.task_done()
+        self._logger.info(f"Installer thread {threading.get_ident()} exiting")
+
+    def _register_or_install(self, job: ModelInstallJob) -> None:
+        # local jobs will be in waiting state, remote jobs will be downloading state
         job.total_bytes = self._stat_size(job.local_path)
         job.bytes = job.total_bytes
         self._signal_job_running(job)
@@ -455,7 +477,7 @@ class ModelInstallService(ModelInstallServiceBase):
         job.config_out = self.record_store.get_model(key)
         self._signal_job_completed(job)
 
-            except InvalidModelConfigException as excp:
+    def _set_error(self, job: ModelInstallJob, excp: Exception) -> None:
         if any(x.content_type is not None and "text/html" in x.content_type for x in job.download_parts):
             job.set_error(
                 InvalidModelConfigException(
@@ -466,17 +488,6 @@ class ModelInstallService(ModelInstallServiceBase):
             job.set_error(excp)
         self._signal_job_errored(job)
 
-            except (OSError, DuplicateModelException) as excp:
-                job.set_error(excp)
-                self._signal_job_errored(job)
-
-            finally:
-                # if this is an install of a remote file, then clean up the temporary directory
-                if job._install_tmpdir is not None:
-                    rmtree(job._install_tmpdir)
-                self._install_completed_event.set()
-                self._install_queue.task_done()
-
     # --------------------------------------------------------------------------------------------
     # Internal functions that manage the models directory
     # --------------------------------------------------------------------------------------------
@@ -905,7 +916,7 @@ class ModelInstallService(ModelInstallServiceBase):
             self._event_bus.emit_model_install_cancelled(str(job.source), id=job.id)
 
     @staticmethod
-    def get_fetcher_from_url(url: str):
+    def get_fetcher_from_url(url: str) -> ModelMetadataFetchBase:
         if re.match(r"^https?://huggingface.co/[^/]+/[^/]+$", url.lower()):
             return HuggingFaceMetadataFetch
         raise ValueError(f"Unsupported model source: '{url}'")

tests/app/services/download/test_download_queue.py

@@ -51,6 +51,7 @@ def session() -> Session:
     return sess
 
 
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_basic_queue_download(tmp_path: Path, session: Session) -> None:
     events = set()
 
@@ -80,6 +81,7 @@ def test_basic_queue_download(tmp_path: Path, session: Session) -> None:
     queue.stop()
 
 
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_errors(tmp_path: Path, session: Session) -> None:
     queue = DownloadQueueService(
         requests_session=session,
@@ -101,6 +103,7 @@ def test_errors(tmp_path: Path, session: Session) -> None:
     queue.stop()
 
 
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_event_bus(tmp_path: Path, session: Session) -> None:
     event_bus = TestEventService()
 
@@ -136,6 +139,7 @@ def test_event_bus(tmp_path: Path, session: Session) -> None:
     queue.stop()
 
 
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None:
     queue = DownloadQueueService(
         requests_session=session,

tests/app/services/model_install/test_model_install.py

@@ -5,6 +5,7 @@ Test the model installer
 import platform
 import uuid
 from pathlib import Path
+from typing import Any, Dict
 
 import pytest
 from pydantic import ValidationError
@@ -276,48 +277,48 @@ def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: In
 
 
 # TODO: Fix bug in model install causing jobs to get installed multiple times then uncomment this test
-# @pytest.mark.parametrize(
+@pytest.mark.parametrize(
-#     "model_params",
+    "model_params",
-#     [
+    [
-#         # SDXL, Lora
+        # SDXL, Lora
-#         {
+        {
-#             "repo_id": "InvokeAI-test/textual_inversion_tests::learned_embeds-steps-1000.safetensors",
+            "repo_id": "InvokeAI-test/textual_inversion_tests::learned_embeds-steps-1000.safetensors",
-#             "name": "test_lora",
+            "name": "test_lora",
-#             "type": "embedding",
+            "type": "embedding",
-#         },
+        },
-#         # SDXL, Lora - incorrect type
+        # SDXL, Lora - incorrect type
-#         {
+        {
-#             "repo_id": "InvokeAI-test/textual_inversion_tests::learned_embeds-steps-1000.safetensors",
+            "repo_id": "InvokeAI-test/textual_inversion_tests::learned_embeds-steps-1000.safetensors",
-#             "name": "test_lora",
+            "name": "test_lora",
-#             "type": "lora",
+            "type": "lora",
-#         },
+        },
-#     ],
+    ],
-# )
+)
-# @pytest.mark.timeout(timeout=40, method="thread")
+@pytest.mark.timeout(timeout=40, method="thread")
-# def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, model_params: Dict[str, str]):
+def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, model_params: Dict[str, str]):
-#     """Test whether or not type is respected on configs when passed to heuristic import."""
+    """Test whether or not type is respected on configs when passed to heuristic import."""
-#     assert "name" in model_params and "type" in model_params
+    assert "name" in model_params and "type" in model_params
-#     config1: Dict[str, Any] = {
+    config1: Dict[str, Any] = {
-#         "name": f"{model_params['name']}_1",
+        "name": f"{model_params['name']}_1",
-#         "type": model_params["type"],
+        "type": model_params["type"],
-#         "hash": "placeholder1",
+        "hash": "placeholder1",
-#     }
+    }
-#     config2: Dict[str, Any] = {
+    config2: Dict[str, Any] = {
-#         "name": f"{model_params['name']}_2",
+        "name": f"{model_params['name']}_2",
-#         "type": ModelType(model_params["type"]),
+        "type": ModelType(model_params["type"]),
-#         "hash": "placeholder2",
+        "hash": "placeholder2",
-#     }
+    }
-#     assert "repo_id" in model_params
+    assert "repo_id" in model_params
-#     install_job1 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config1)
+    install_job1 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config1)
-#     mm2_installer.wait_for_job(install_job1, timeout=20)
+    mm2_installer.wait_for_job(install_job1, timeout=20)
-#     if model_params["type"] != "embedding":
+    if model_params["type"] != "embedding":
-#         assert install_job1.errored
+        assert install_job1.errored
-#         assert install_job1.error_type == "InvalidModelConfigException"
+        assert install_job1.error_type == "InvalidModelConfigException"
-#         return
+        return
-#     assert install_job1.complete
+    assert install_job1.complete
-#     assert install_job1.config_out if model_params["type"] == "embedding" else not install_job1.config_out
+    assert install_job1.config_out if model_params["type"] == "embedding" else not install_job1.config_out
 
-#     install_job2 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config2)
+    install_job2 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config2)
-#     mm2_installer.wait_for_job(install_job2, timeout=20)
+    mm2_installer.wait_for_job(install_job2, timeout=20)
-#     assert install_job2.complete
+    assert install_job2.complete
-#     assert install_job2.config_out if model_params["type"] == "embedding" else not install_job2.config_out
+    assert install_job2.config_out if model_params["type"] == "embedding" else not install_job2.config_out

tests/backend/model_manager/model_manager_fixtures.py

@@ -2,13 +2,11 @@
 
 import os
 import shutil
-import time
 from pathlib import Path
 from typing import Any, Dict, List
 
 import pytest
 from pydantic import BaseModel
-from pytest import FixtureRequest
 from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
@@ -99,16 +97,12 @@ def mm2_app_config(mm2_root_dir: Path) -> InvokeAIAppConfig:
 
 
 @pytest.fixture
-def mm2_download_queue(mm2_session: Session, request: FixtureRequest) -> DownloadQueueServiceBase:
+def mm2_download_queue(mm2_session: Session) -> DownloadQueueServiceBase:
     download_queue = DownloadQueueService(requests_session=mm2_session)
     download_queue.start()
-
+    yield download_queue
-    def stop_queue() -> None:
     download_queue.stop()
 
-    request.addfinalizer(stop_queue)
-    return download_queue
-
 
 @pytest.fixture
 def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceBase) -> ModelLoadServiceBase:
@@ -130,7 +124,6 @@ def mm2_installer(
     mm2_app_config: InvokeAIAppConfig,
     mm2_download_queue: DownloadQueueServiceBase,
     mm2_session: Session,
-    request: FixtureRequest,
 ) -> ModelInstallServiceBase:
     logger = InvokeAILogger.get_logger()
     db = create_mock_sqlite_database(mm2_app_config, logger)
@@ -145,13 +138,8 @@ def mm2_installer(
         session=mm2_session,
     )
     installer.start()
-
+    yield installer
-    def stop_installer() -> None:
     installer.stop()
-        time.sleep(0.1)  # avoid error message from the logger when it is closed before thread prints final message
-
-    request.addfinalizer(stop_installer)
-    return installer
 
 
 @pytest.fixture