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7990faa38c
* Split provider hooks into override/adjust with cached CoreML base Replace the single resolve_inference_providers processor hook with two: override_inference_providers (full replacement) and adjust_inference_providers (merge options onto the base providers built by create_inference_providers). This lets CoreML processors inherit ModelCacheDirectory + SpecializationStrategy from the base while layering ModelFormat/MLComputeUnits on top. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01HTQCZiYjJyUX11bDpbRSiB * fix caching for execution provider by having override and adjust ways * fix caching for execution provider by having override and adjust ways * fix lint * use proper pytest fixtures --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
57 lines
2.9 KiB
Python
57 lines
2.9 KiB
Python
from types import SimpleNamespace
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from unittest.mock import Mock, patch
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import pytest
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from onnxruntime import InferenceSession
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from facefusion import content_analyser, state_manager
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from facefusion.execution import resolve_cache_path
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from facefusion.inference_manager import INFERENCE_POOL_SET, get_inference_pool, resolve_static_inference_providers
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@pytest.fixture(scope = 'module', autouse = True)
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def before_all() -> None:
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state_manager.init_item('execution_device_ids', [ 0 ])
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state_manager.init_item('execution_providers', [ 'cpu' ])
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state_manager.init_item('download_providers', [ 'github' ])
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def test_get_inference_pool() -> None:
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model_names = [ 'nsfw_1', 'nsfw_2', 'nsfw_3' ]
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_, model_source_set = content_analyser.collect_model_downloads()
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with patch('facefusion.inference_manager.detect_app_context', return_value = 'cli'):
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get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
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assert isinstance(INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1'), InferenceSession)
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with patch('facefusion.inference_manager.detect_app_context', return_value = 'ui'):
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get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
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assert isinstance(INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1'), InferenceSession)
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assert INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1') == INFERENCE_POOL_SET.get('ui').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1')
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@pytest.fixture
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def override_module() -> SimpleNamespace:
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return SimpleNamespace(override_inference_providers = Mock(return_value = [ ('CoreMLExecutionProvider', { 'ModelFormat': 'MLProgram' }) ]))
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@pytest.fixture
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def adjust_module() -> SimpleNamespace:
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return SimpleNamespace(adjust_inference_providers = Mock(return_value = [ ('CoreMLExecutionProvider', { 'ModelFormat': 'MLProgram' }) ]))
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def test_resolve_static_inference_providers(override_module : SimpleNamespace, adjust_module : SimpleNamespace) -> None:
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state_manager.init_item('execution_providers', ['coreml'])
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resolve_static_inference_providers.cache_clear()
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with patch('facefusion.inference_manager.importlib', Mock(import_module = Mock(return_value = override_module))):
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assert resolve_static_inference_providers('override_module', 0) == [ ('CoreMLExecutionProvider', { 'ModelFormat': 'MLProgram' }) ]
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with patch('facefusion.inference_manager.importlib', Mock(import_module = Mock(return_value = adjust_module))):
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assert resolve_static_inference_providers('adjust_module', 0) == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path(), 'ModelFormat': 'MLProgram' }) ]
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assert resolve_static_inference_providers('test', 0) == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path() }) ]
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