zsyoaoa/invsr 🔢🖼️❓ → 🖼️

Setting timesteps for inference: [200]
Downloading: "https://huggingface.co/OAOA/InvSR/resolve/main/noise_predictor_sd_turbo_v5.pth" to /src/weights/noise_predictor_sd_turbo_v5.pth
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You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_inversion_sr.StableDiffusionInvEnhancePipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
Activating gradient checkpoing for vae...
Loading started model from ./weights/noise_predictor_sd_turbo_v5.pth...
/src/sampler_invsr.py:101: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
state = torch.load(ckpt_path, map_location=f"cuda")
Loading Done
/root/.pyenv/versions/3.10.15/lib/python3.10/site-packages/diffusers/configuration_utils.py:140: FutureWarning: Accessing config attribute `vae_latent_channels` directly via 'VaeImageProcessor' object attribute is deprecated. Please access 'vae_latent_channels' over 'VaeImageProcessor's config object instead, e.g. 'scheduler.config.vae_latent_channels'.
deprecate("direct config name access", "1.0.0", deprecation_message, standard_warn=False)
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Processing done, enjoy the results in invsr_output