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model_base: support non-dynamic disable cases
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@ -908,7 +908,7 @@ class LTXAVModel(LTXVModel):
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"""Process transformer blocks for LTXAV."""
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patches_replace = transformer_options.get("patches_replace", {})
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blocks_replace = patches_replace.get("dit", {})
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prefetch_queue = comfy.model_prefetch.make_prefetch_queue(list(self.transformer_blocks), vx.device)
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prefetch_queue = comfy.model_prefetch.make_prefetch_queue(list(self.transformer_blocks), vx.device, transformer_options)
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# Process transformer blocks
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for i, block in enumerate(self.transformer_blocks):
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@ -210,6 +210,11 @@ class BaseModel(torch.nn.Module):
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if "latent_shapes" in extra_conds:
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xc = utils.unpack_latents(xc, extra_conds.pop("latent_shapes"))
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transformer_options = transformer_options.copy()
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transformer_options["prefetch_dynamic_vbars"] = (
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self.current_patcher is not None and self.current_patcher.is_dynamic()
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)
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model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds)
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if len(model_output) > 1 and not torch.is_tensor(model_output):
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model_output, _ = utils.pack_latents(model_output)
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@ -57,8 +57,9 @@ def prefetch_queue_pop(queue, device, module):
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comfy.model_management.sync_stream(device, offload_stream)
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queue[0] = (offload_stream, (prefetch, comfy_modules))
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def make_prefetch_queue(queue, device):
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if (comfy.model_management.NUM_STREAMS == 0
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def make_prefetch_queue(queue, device, transformer_options):
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if (not transformer_options.get("prefetch_dynamic_vbars", False)
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or comfy.model_management.NUM_STREAMS == 0
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or comfy.model_management.is_device_cpu(device)
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or not comfy.model_management.device_supports_non_blocking(device)):
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return None
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