huangfeice 0eafd9cf0b fix: Clean up JoyImage model dead code and redundant casts ... Some cleanup of the JoyImage transformer: - FP32LayerNorm/JoyImageModulate: drop constructor params that were never used (dtype/device on the param-free FP32LayerNorm, operations on JoyImageModulate). - modulate_table: init with torch.empty instead of torch.zeros since it is loaded from the state dict, and cast at use with comfy.ops.cast_to_input. - Replace the FeedForward nn.Dropout(0.0) no-op with nn.Identity, keeping the ModuleList slot so state-dict keys are unchanged. - Drop the always-true vec.shape guard (time_proj_dim is always hidden_size*6). - Remove the redundant per-reference .to(device,dtype) in JoyImage._apply_model; the extra_conds cast loop already moves ref_latents to the compute dtype/device. - Drop the redundant .to(xq.device) in the RoPE apply; the freqs are built on the latent device.		2026-07-06 17:43:24 +08:00
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model.py	fix: Clean up JoyImage model dead code and redundant casts	2026-07-06 17:43:24 +08:00