Remove unused helper node
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@@ -190,38 +190,6 @@ class _IntOperations(io.ComfyNode):
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result = cls.OPS[operation](a, b)
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return io.NodeOutput(int(result), bool(result))
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class _ImageBatchStateUnpack(io.ComfyNode):
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"""Internal helper: unpacks the loop_state dict produced by ImageBatchLoopOpen."""
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@classmethod
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="_ImageBatchStateUnpack",
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display_name="Image Batch State Unpack",
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category="looping/loops",
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#is_dev_only=True,
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inputs=[io.AnyType.Input("loop_state")],
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outputs=[
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io.Image.Output("images"),
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io.Int.Output("next_offset"),
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io.Boolean.Output("has_more"),
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io.Accumulation.Output("accumulation"),
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io.Int.Output("batch_size"),
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],
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)
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@classmethod
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def execute(cls, loop_state) -> io.NodeOutput:
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print(f"[_ImageBatchStateUnpack] next_offset={loop_state['next_offset']}, has_more={loop_state['has_more']}, accum_len={len(loop_state['accum']['accum']) if isinstance(loop_state['accum'], dict) else None}, images={loop_state['images'].shape}")
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return io.NodeOutput(
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loop_state["images"],
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loop_state["next_offset"],
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loop_state["has_more"],
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loop_state["accum"],
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loop_state["batch_size"],
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)
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class _AccumulationToImageBatch(io.ComfyNode):
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"""Internal helper: concatenates an ACCUMULATION of IMAGE/MASK tensors or LATENT dicts into a single batch."""
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@classmethod
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@@ -444,7 +412,6 @@ class LoopExtension(ComfyExtension):
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_AccumulateNode,
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_IntOperations,
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_AccumulationToImageBatch,
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_ImageBatchStateUnpack,
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_ImageAccumStateUnpack,
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_ImageAccumStatePack,
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]
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