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https://github.com/comfyanonymous/ComfyUI.git
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Remove breaking code, logging etc.
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@ -432,15 +432,6 @@ class CogVideoXTransformer3DModel(nn.Module):
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).execute(x, timestep, context, ofs, transformer_options, **kwargs)
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def _forward(self, x, timestep, context, ofs=None, transformer_options={}, **kwargs):
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import logging
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logger = logging.getLogger(__name__)
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if x.shape[1] > 16:
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lq_part = x[:, :16]
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ref_part = x[:, 16:]
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logger.warning(f"[CogVideoX] x: {x.shape}, t: {timestep.item():.0f}, ofs: {ofs}, LQ: mean={lq_part.float().mean():.4f} std={lq_part.float().std():.4f}, REF: mean={ref_part.float().mean():.4f} std={ref_part.float().std():.4f} nonzero={ref_part.count_nonzero().item()}")
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else:
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logger.warning(f"[CogVideoX] x: {x.shape}, t: {timestep.item():.0f}, ofs: {ofs}")
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# ComfyUI passes [B, C, T, H, W]
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batch_size, channels, t, h, w = x.shape
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@ -512,7 +503,6 @@ class CogVideoXTransformer3DModel(nn.Module):
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# Back to ComfyUI format [B, C, T, H, W] and crop padding
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output = output.permute(0, 2, 1, 3, 4)[:, :, :t, :h, :w]
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logger.warning(f"[CogVideoX] output: {output.shape}, mean={output.float().mean():.4f}, std={output.float().std():.4f}, min={output.float().min():.4f}, max={output.float().max():.4f}")
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return output
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def _get_rotary_emb(self, h, w, t, device):
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