FaceAlignmentCropper

Issue / Note: PyTorch 2.6+ Security Blocks Weights Loading in FaceAlignmentCropper Problem Description: When running a workflow with the LivePortrait Load FaceAlignmentCropper node, it fails to initialize and turns red on the canvas (entering an UNKNOWN state or throwing an initialization error). The ComfyUI console outputs a critical PyTorch serialization error.

Error Log:

Plaintext torch.serialization.WeightsOnlyLoadFailed: Weights only load failed. Re-running torch.load with weights_only=False to show an exception that happened instead has failed. AttributeError: Can't get attribute 'reduce_graph_module' on <module 'face_alignment...'>

Root Cause: Starting with PyTorch 2.6+, the default model loading mechanism strictly enforces security restrictions (weights_only=True). This blocks the execution of any hidden or non-standard code embedded within model weight files. The checkpoint used by the FaceAlignment backend was saved using an outdated method and contains a reference to an internal structure called reduce_graph_module. The updated PyTorch environment flags this structure as unsafe and completely blocks its import.

Solution / Workaround: Switch to the LivePortrait Load InsightFaceCropper node. It utilizes modern models in the .onnx format, which run via a separate ONNX Runtime engine. This completely bypasses PyTorch's pickle-based security checks, prevents initialization errors, and provides significantly more precise facial tracking utilizing GPU acceleration (CUDA) RTX 4080.