ai: add missing activatin shape
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@@ -340,6 +340,7 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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"cond_index": float(idx_side),
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"is_positive": 1.0 if side == "positive" else 0.0,
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"is_negative": 1.0 if side == "negative" else 0.0,
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"activations_shape": tensor_shape(out["img"]) if isinstance(out, dict) and "img" in out else [],
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}
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out = extra_args["original_block"](args)
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@@ -484,7 +485,9 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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"cond_index": float(idx_side),
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"is_positive": 1.0 if side == "positive" else 0.0,
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"is_negative": 1.0 if side == "negative" else 0.0,
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"activations_shape": tensor_shape(t),
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}
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return run_expr(t, meta)
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def input_block_patch(h, transformer_options):
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@@ -508,6 +511,7 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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patches["output_block_patch"] = list(patches.get("output_block_patch", [])) + [output_block_patch]
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patches["middle_patch"] = list(patches.get("middle_patch", [])) + [middle_patch]
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patches["emb_patch"] = list(patches.get("emb_patch", [])) + [emb_patch]
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patches["middle_block_after_patch"] = list(patches.get("middle_block_after_patch", [])) + [middle_patch]
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topts["patches"] = patches
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patched_dict["transformer_options"] = topts
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@@ -533,6 +537,7 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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"total_blocks": -1.0,
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"has_qkv": 0.0,
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"layer_key": "model.begin",
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"activations_shape": tensor_shape(x),
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}
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xin = run_expr(x, pre_meta) if isinstance(x, torch.Tensor) else x
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else:
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@@ -552,6 +557,7 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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"total_blocks": -1.0,
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"has_qkv": 0.0,
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"layer_key": "model.end",
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"activations_shape": tensor_shape(out),
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}
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return run_expr(out, post_meta)
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return out
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@@ -673,4 +679,7 @@ class SelectiveGuiderMathNode(io.ComfyNode):
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for item in uniq:
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dbg(f"HOOK SUMMARY ITEM {item}")
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return result
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return result
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def tensor_shape(x):
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return list(x.shape) if isinstance(x, torch.Tensor) else []
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