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68f5b543d9
vector_norm(dim=1) dropped the channel axis, so dividing the (B,C,H,W) latent by the (B,H,W) norm broadcast the batch axis onto the channels. With batch_size != channels this raised a RuntimeError, and when they happened to be equal it silently mixed the per-sample normalization. Keep the channel dimension with keepdim=True so each latent is normalized independently. |
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| .. | ||
| __init__.py | ||
| image_stitch_test.py | ||
| nodes_latent_test.py | ||
| nodes_math_test.py | ||
| nodes_number_convert_test.py | ||
| test_seedvr2_conditioning.py | ||
| test_seedvr2_nodes.py | ||
| test_seedvr2_post_processing.py | ||
| test_seedvr2_temporal_chunk.py | ||