81 lines
2.0 KiB
Python
81 lines
2.0 KiB
Python
import logging
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import os
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from lama_cleaner.schema import Config
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os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
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import torch
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from lama_cleaner.model_manager import ModelManager
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def test_model_switch():
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model = ModelManager(
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name="runwayml/stable-diffusion-inpainting",
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sd_controlnet=True,
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sd_controlnet_method="lllyasviel/control_v11p_sd15_canny",
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device=torch.device("mps"),
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hf_access_token="",
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disable_nsfw=True,
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sd_cpu_textencoder=True,
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cpu_offload=False,
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enable_xformers=False,
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callback=None,
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)
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model.switch("lama")
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def test_controlnet_switch_onoff(caplog):
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name = "runwayml/stable-diffusion-inpainting"
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model = ModelManager(
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name=name,
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sd_controlnet=True,
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sd_controlnet_method="lllyasviel/control_v11p_sd15_canny",
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device=torch.device("mps"),
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hf_access_token="",
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disable_nsfw=True,
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sd_cpu_textencoder=True,
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cpu_offload=False,
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enable_xformers=False,
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callback=None,
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)
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model.switch_controlnet_method(
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Config(
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name=name,
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controlnet_enabled=False,
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)
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)
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assert "Disable controlnet" in caplog.text
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def test_controlnet_switch_method(caplog):
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name = "runwayml/stable-diffusion-inpainting"
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old_method = "lllyasviel/control_v11p_sd15_canny"
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new_method = "lllyasviel/control_v11p_sd15_openpose"
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model = ModelManager(
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name=name,
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sd_controlnet=True,
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sd_controlnet_method=old_method,
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device=torch.device("mps"),
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hf_access_token="",
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disable_nsfw=True,
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sd_cpu_textencoder=True,
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cpu_offload=False,
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enable_xformers=False,
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callback=None,
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)
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model.switch_controlnet_method(
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Config(
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name=name,
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controlnet_enabled=True,
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controlnet_method=new_method,
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)
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)
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assert f"Switch Controlnet method from {old_method} to {new_method}" in caplog.text
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