Gp/output #825
Gp/output #825
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…streamline path handling and improve consistency
…pport conditional output based on input_info settings
Summary of ChangesHello @GACLove, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request focuses on enhancing the consistency and maintainability of image and video processing workflows within the system. It primarily refactors the VAE output conversion utility into a more unified and efficient function, and standardizes the return types of several image runner pipelines. Additionally, it refines the image saving logic to be more flexible and organized, contributing to a more robust and developer-friendly codebase. Highlights
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Code Review
This pull request refactors VAE output conversion functions and standardizes the return type of run_pipeline across several image-related runners. The vae_to_comfyui_image and vae_to_comfyui_image_inplace functions have been consolidated into wan_vae_to_comfy, which performs in-place normalization but returns a new tensor. The run_pipeline methods in longcat_image_runner.py, qwen_image_runner.py, and z_image_runner.py now consistently return a dictionary instead of a tuple, which is a breaking API change that should be noted. Additionally, minor f-string cleanups and improved image saving logic were implemented.
| Convert VAE decoder output to ComfyUI Image format (inplace operation) | ||
| Args: | ||
| vae_output: VAE decoder output tensor, typically in range [-1, 1] | ||
| Shape: [B, C, T, H, W] or [B, C, H, W] | ||
| WARNING: This tensor will be modified in-place! | ||
| Returns: | ||
| ComfyUI Image tensor in range [0, 1] | ||
| Shape: [B, H, W, C] for single frame or [B*T, H, W, C] for video | ||
| Note: The returned tensor is the same object as input (modified in-place) |
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The docstring for wan_vae_to_comfy states that it performs an "inplace operation" and that "The returned tensor is the same object as input (modified in-place)". While the normalization steps (add_, mul_, clamp_) are indeed in-place, the subsequent permute and flatten operations create new tensors (or views that are then copied to CPU). Therefore, the returned tensor is not the same object as the input vae_output. This contradiction can be misleading and potentially lead to unexpected behavior if callers rely on the returned object being the original input tensor. Please clarify the docstring to accurately reflect that the input tensor is modified in-place for normalization, but a new tensor is returned after permutation and flattening.
| Convert VAE decoder output to ComfyUI Image format (inplace operation) | |
| Args: | |
| vae_output: VAE decoder output tensor, typically in range [-1, 1] | |
| Shape: [B, C, T, H, W] or [B, C, H, W] | |
| WARNING: This tensor will be modified in-place! | |
| Returns: | |
| ComfyUI Image tensor in range [0, 1] | |
| Shape: [B, H, W, C] for single frame or [B*T, H, W, C] for video | |
| Note: The returned tensor is the same object as input (modified in-place) | |
| Convert VAE decoder output to ComfyUI Image format | |
| Args: | |
| vae_output: VAE decoder output tensor, typically in range [-1, 1] | |
| Shape: [B, C, T, H, W] or [B, C, H, W] | |
| WARNING: The input tensor `vae_output` will be modified in-place for normalization. | |
| Returns: | |
| A new ComfyUI Image tensor in range [0, 1] | |
| Shape: [B, H, W, C] for single frame or [B*T, H, W, C] for video |
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| def process_images_after_vae_decoder(self): | ||
| self.gen_video_final = vae_to_comfyui_image(self.gen_video_final) | ||
| self.gen_video_final = wan_vae_to_comfy(self.gen_video_final) |
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The change from vae_to_comfyui_image (which was not in-place) to wan_vae_to_comfy (which performs in-place normalization) represents a behavioral change for self.gen_video_final. While the assignment immediately overwrites the reference, it's important to be aware that self.gen_video_final is now modified in-place before being reassigned. This is generally acceptable for efficiency, but it's a subtle change from the previous non-in-place function.
| if input_info.return_result_tensor: | ||
| return {"images": images} | ||
| elif input_info.save_result_path is not None: | ||
| return {"images": None} |
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The return type of the run_pipeline method has changed from a tuple (images, None) to a dictionary {"images": images} or {"images": None}. This is a breaking API change that external callers might need to adapt to. Please ensure this change is documented and communicated appropriately.
| if input_info.return_result_tensor: | ||
| return {"images": images} | ||
| elif input_info.save_result_path is not None: | ||
| return {"images": None} |
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Similar to other image runners, the return type of the run_pipeline method has changed from a tuple (images, None) to a dictionary {"images": images} or {"images": None}. This is a breaking API change that external callers might need to adapt to. Please ensure this change is documented and communicated appropriately.
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