From ba24ecccf410680dea0ec09d872502a530b613a4 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Thu, 30 Oct 2025 20:56:41 +0000
Subject: [PATCH 01/12] copy in metadata preservation

---
 .../transformation/extract_quant_scale_zeropt.py    |  8 ++++++++
 src/qonnx/transformation/gemm_to_matmul.py          | 13 ++++++++++++-
 2 files changed, 20 insertions(+), 1 deletion(-)

diff --git a/src/qonnx/transformation/extract_quant_scale_zeropt.py b/src/qonnx/transformation/extract_quant_scale_zeropt.py
index 58863f08..614df416 100644
--- a/src/qonnx/transformation/extract_quant_scale_zeropt.py
+++ b/src/qonnx/transformation/extract_quant_scale_zeropt.py
@@ -69,6 +69,8 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(inp_scaled)
                     inp_scale_node = helper.make_node("Div", [running_input, scale_nm], [inp_scaled_nm])
+                    if hasattr(node, "metadata_props"):
+                        inp_scale_node.metadata_props.extend(node.metadata_props)
                     graph.node.append(inp_scale_node)
                     # create new Mul node
                     # remove scale from Quant node
@@ -87,6 +89,8 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(inp_zeropt)
                     inp_zeropt_node = helper.make_node("Add", [running_input, zeropt_nm], [inp_zeropt_nm])
+                    if hasattr(node, "metadata_props"):
+                        inp_zeropt_node.metadata_props.extend(node.metadata_props)
                     graph.node.append(inp_zeropt_node)
                     # remove zeropt from Quant node
                     new_zeropt_nm = model.make_new_valueinfo_name()
@@ -108,6 +112,8 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(out_zeropt)
                     out_zeropt_node = helper.make_node("Sub", [out_zeropt_nm, zeropt_nm], [final_output])
+                    if hasattr(node, "metadata_props"):
+                        out_zeropt_node.metadata_props.extend(node.metadata_props)
                     last_node.output[0] = out_zeropt_nm
                     graph.node.append(out_zeropt_node)
                     # important: when tracking a pointer to newly added nodes,
@@ -127,6 +133,8 @@ def apply(self, model: ModelWrapper):
                     last_node.output[0] = out_scale_nm
                     graph.value_info.append(out_scale)
                     out_scale_node = helper.make_node("Mul", [out_scale_nm, scale_nm], [final_output])
+                    if hasattr(node, "metadata_props"):
+                        out_scale_node.metadata_props.extend(node.metadata_props)
                     graph.node.append(out_scale_node)
 
                 if extract_scale or extract_zeropt:
diff --git a/src/qonnx/transformation/gemm_to_matmul.py b/src/qonnx/transformation/gemm_to_matmul.py
index 5396a7d6..1298f3d6 100644
--- a/src/qonnx/transformation/gemm_to_matmul.py
+++ b/src/qonnx/transformation/gemm_to_matmul.py
@@ -76,6 +76,8 @@ def apply(self, model):
                     )
                     graph.value_info.append(inp_trans_out)
                     inp_trans_node = helper.make_node("Transpose", [n.input[0]], [inp_trans_out.name])
+                    if hasattr(n, "metadata_props"):
+                        inp_trans_node.metadata_props.extend(n.metadata_props)
                     graph.node.insert(running_node_index, inp_trans_node)
                     running_node_index += 1
                     dt = model.get_tensor_datatype(n.input[0])
@@ -98,6 +100,8 @@ def apply(self, model):
                     )
                     graph.value_info.append(inp_trans_out)
                     inp_trans_node = helper.make_node("Transpose", [n.input[1]], [inp_trans_out.name])
+                    if hasattr(n, "metadata_props"):
+                        inp_trans_node.metadata_props.extend(n.metadata_props)
                     graph.node.insert(running_node_index, inp_trans_node)
                     running_node_index += 1
                     # Copy over the datatype
@@ -109,6 +113,8 @@ def apply(self, model):
 
                 # Insert MatMul: A * B
                 matMul_node = helper.make_node("MatMul", [n.input[0], n.input[1]], [n.output[0]])
+                if hasattr(n, "metadata_props"):
+                    matMul_node.metadata_props.extend(n.metadata_props)
                 graph.node.insert(running_node_index, matMul_node)
                 matMul_node = graph.node[running_node_index]
                 running_node_index += 1
@@ -144,6 +150,8 @@ def apply(self, model):
                     [act_mul_tensor.name, mul_tensor.name],
                     [n.output[0]],
                 )
+                if hasattr(n, "metadata_props"):
+                    mul_node.metadata_props.extend(n.metadata_props)
                 graph.node.insert(running_node_index, mul_node)
                 mul_node_main_branch = graph.node[running_node_index]
                 running_node_index += 1
@@ -175,6 +183,8 @@ def apply(self, model):
                     [n.input[2], mul_tensor.name],
                     [act_mul_tensor.name],
                 )
+                if hasattr(n, "metadata_props"):
+                    mul_node.metadata_props.extend(n.metadata_props)
                 graph.node.insert(running_node_index, mul_node)
                 running_node_index += 1
                 dt = model.get_tensor_datatype(n.input[2])
@@ -196,7 +206,8 @@ def apply(self, model):
                     [act_add_tensor.name, n.input[2]],
                     [n.output[0]],
                 )
-
+                if hasattr(n, "metadata_props"):
+                    add_node.metadata_props.extend(n.metadata_props)
                 graph.node.insert(running_node_index, add_node)
                 running_node_index += 1
 

From da632b9f9b94817a6e9dba51f2ac665818a55f84 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Thu, 30 Oct 2025 21:59:38 +0000
Subject: [PATCH 02/12] expand metadata copy coverage to other transforms

---
 src/qonnx/transformation/change_datalayout.py     | 6 ++++++
 src/qonnx/transformation/channels_last.py         | 6 ++++++
 src/qonnx/transformation/extract_conv_bias.py     | 2 ++
 src/qonnx/transformation/lower_convs_to_matmul.py | 4 ++++
 src/qonnx/transformation/qcdq_to_qonnx.py         | 4 ++++
 src/qonnx/transformation/rebalance_conv.py        | 2 ++
 src/qonnx/transformation/resize_conv_to_deconv.py | 3 +++
 src/qonnx/transformation/subpixel_to_deconv.py    | 3 +++
 8 files changed, 30 insertions(+)

diff --git a/src/qonnx/transformation/change_datalayout.py b/src/qonnx/transformation/change_datalayout.py
index 7b73e4bf..07fbe400 100644
--- a/src/qonnx/transformation/change_datalayout.py
+++ b/src/qonnx/transformation/change_datalayout.py
@@ -78,6 +78,8 @@ def apply(self, model):
                 graph.value_info.append(quantavg_out)
                 quantavg_out = quantavg_out.name
                 inp_trans_node = helper.make_node("Transpose", [node_input], [inp_trans_out], perm=[0, 2, 3, 1])
+                if hasattr(n, "metadata_props"):
+                    inp_trans_node.metadata_props.extend(n.metadata_props)
                 quantavg_node = helper.make_node(
                     "QuantAvgPool2d",
                     [inp_trans_out],
@@ -90,8 +92,12 @@ def apply(self, model):
                     signed=signed,
                     data_layout="NHWC",
                 )
+                if hasattr(n, "metadata_props"):
+                    quantavg_node.metadata_props.extend(n.metadata_props)
                 # NHWC -> NCHW
                 out_trans_node = helper.make_node("Transpose", [quantavg_out], [node_output], perm=[0, 3, 1, 2])
+                if hasattr(n, "metadata_props"):
+                    out_trans_node.metadata_props.extend(n.metadata_props)
                 # insert nodes
                 graph.node.insert(node_ind, inp_trans_node)
                 graph.node.insert(node_ind + 1, quantavg_node)
diff --git a/src/qonnx/transformation/channels_last.py b/src/qonnx/transformation/channels_last.py
index 175af058..8c934190 100644
--- a/src/qonnx/transformation/channels_last.py
+++ b/src/qonnx/transformation/channels_last.py
@@ -96,6 +96,8 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             new_t_inp = model.make_new_valueinfo_name()
             inv_perm = np.argsort(perm)
             new_transpose_node = helper.make_node("Transpose", [eltwise_inp], [new_t_inp], perm=inv_perm)
+            if hasattr(transpose_node, "metadata_props"):
+                new_transpose_node.metadata_props.extend(transpose_node.metadata_props)
             t_shape = np.transpose(np.empty(inp_shape), axes=inv_perm).shape
             model.set_tensor_shape(new_t_inp, t_shape)
             eltwise_node.input[ind] = new_t_inp
@@ -107,6 +109,8 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             model.set_initializer(unsqueeze_param_name, np.asarray(list(range(ndim_inp - ndim)), dtype=np.int64))
             unsqueeze_out_name = model.make_new_valueinfo_name()
             new_unsqueeze_node = helper.make_node("Unsqueeze", [eltwise_inp, unsqueeze_param_name], [unsqueeze_out_name])
+            if hasattr(eltwise_inp, "metadata_props"):
+                new_unsqueeze_node.metadata_props.extend(eltwise_inp.metadata_props)
             unsqueeze_out_shape = np.expand_dims(np.empty(inp_shape), axis=tuple(range(ndim_inp - ndim))).shape
             model.set_tensor_shape(unsqueeze_out_name, unsqueeze_out_shape)
             model.graph.node.append(new_unsqueeze_node)
@@ -114,6 +118,8 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             new_t_inp = model.make_new_valueinfo_name()
             inv_perm = np.argsort(perm)
             new_transpose_node = helper.make_node("Transpose", [unsqueeze_out_name], [new_t_inp], perm=inv_perm)
+            if hasattr(transpose_node, "metadata_props"):
+                new_transpose_node.metadata_props.extend(transpose_node.metadata_props)
             t_shape = np.transpose(np.empty(unsqueeze_out_shape), axes=inv_perm).shape
             model.set_tensor_shape(new_t_inp, t_shape)
             eltwise_node.input[ind] = new_t_inp
diff --git a/src/qonnx/transformation/extract_conv_bias.py b/src/qonnx/transformation/extract_conv_bias.py
index bf2cf8b4..1bf264e3 100644
--- a/src/qonnx/transformation/extract_conv_bias.py
+++ b/src/qonnx/transformation/extract_conv_bias.py
@@ -75,6 +75,8 @@ def apply(self, model):
                         [act_add_tensor.name, n.input[2]],
                         [n.output[0]],
                     )
+                    if hasattr(n, "metadata_props"):
+                        add_node.metadata_props.extend(n.metadata_props)
                     graph.node.insert(node_ind, add_node)
 
                     # Repoint Conv output and remove bias tensor
diff --git a/src/qonnx/transformation/lower_convs_to_matmul.py b/src/qonnx/transformation/lower_convs_to_matmul.py
index 81f0b713..d864d8d2 100644
--- a/src/qonnx/transformation/lower_convs_to_matmul.py
+++ b/src/qonnx/transformation/lower_convs_to_matmul.py
@@ -178,8 +178,12 @@ def apply(self, model):
             matmul_input = im2col_out if need_im2col else inp_trans_out
             # do matmul
             matmul_node = helper.make_node("MatMul", [matmul_input, conv_weight_inp_name], [matmul_out])
+            if hasattr(node, "metadata_props"):
+                matmul_node.metadata_props.extend(node.metadata_props)
             # NHWC -> NCHW
             out_trans_node = helper.make_node("Transpose", [matmul_out], [cnv_output], perm=[0, 3, 1, 2])
+            if hasattr(node, "metadata_props"):
+                out_trans_node.metadata_props.extend(node.metadata_props)
 
             nodes_to_insert.extend([matmul_node, out_trans_node])
 
diff --git a/src/qonnx/transformation/qcdq_to_qonnx.py b/src/qonnx/transformation/qcdq_to_qonnx.py
index b7e35c0d..b122d840 100644
--- a/src/qonnx/transformation/qcdq_to_qonnx.py
+++ b/src/qonnx/transformation/qcdq_to_qonnx.py
@@ -203,6 +203,10 @@ def apply(self, model: ModelWrapper) -> Tuple[ModelWrapper, bool]:
                     rounding_mode="ROUND",  # round-to-even
                     signed=signed,
                 )
+                # Pass on metadata from DequantizeLinear node since it's the only node that
+                # must be present to be able to perform this transformation.
+                if hasattr(node, "metadata_props"):
+                    fused_node.metadata_props.extend(node.metadata_props)
                 model.graph.node.insert(dequant_node_index, fused_node)
             for node_to_remove in nodes_to_remove:
                 model.graph.node.remove(node_to_remove)
diff --git a/src/qonnx/transformation/rebalance_conv.py b/src/qonnx/transformation/rebalance_conv.py
index ecb2b5e4..098bff20 100644
--- a/src/qonnx/transformation/rebalance_conv.py
+++ b/src/qonnx/transformation/rebalance_conv.py
@@ -103,6 +103,8 @@ def apply(self, model):
                     inp_reshape_node = helper.make_node(
                         "Reshape", [node.input[0], inp_shapedata.name], [inp_reshape_out.name]
                     )
+                    if hasattr(node, "metadata_props"):
+                        inp_reshape_node.metadata_props.extend(node.metadata_props)
                     graph.node.insert(running_node_index, inp_reshape_node)
                     # rewire Im2Col input
                     node.input[0] = inp_reshape_out.name
diff --git a/src/qonnx/transformation/resize_conv_to_deconv.py b/src/qonnx/transformation/resize_conv_to_deconv.py
index 0dd40972..30bc6c3c 100644
--- a/src/qonnx/transformation/resize_conv_to_deconv.py
+++ b/src/qonnx/transformation/resize_conv_to_deconv.py
@@ -242,6 +242,9 @@ def apply(self, model):
                         group=group,
                         dilations=dilation,
                     )
+                    # Save metadata from the convolution node
+                    if hasattr(conv, "metadata_props"):
+                        deconv_node.metadata_props.extend(conv.metadata_props)
                     W_deconv_init = weight_name
                     if weight_prod is not None:
                         W_deconv_init = q_w_name
diff --git a/src/qonnx/transformation/subpixel_to_deconv.py b/src/qonnx/transformation/subpixel_to_deconv.py
index 3f330c99..241422c8 100644
--- a/src/qonnx/transformation/subpixel_to_deconv.py
+++ b/src/qonnx/transformation/subpixel_to_deconv.py
@@ -197,6 +197,9 @@ def apply(self, model):
                         group=group,
                         dilations=dilation,
                     )
+                    # Save metadata from the original convolution node
+                    if hasattr(n, "metadata_props"):
+                        deconv_node.metadata_props.extend(n.metadata_props)
                     W_deconv_init = weight_name
                     if weight_prod is not None:
                         W_deconv_init = q_w_name

From 0d9d3e56ad6cc899872f5730b8be0af10f7ead02 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Thu, 30 Oct 2025 22:06:39 +0000
Subject: [PATCH 03/12] add  copy metadata props function

---
 src/qonnx/transformation/change_datalayout.py | 11 +++----
 .../extract_quant_scale_zeropt.py             | 13 +++-----
 src/qonnx/transformation/gemm_to_matmul.py    | 20 ++++--------
 .../transformation/lower_convs_to_matmul.py   |  8 ++---
 src/qonnx/transformation/qcdq_to_qonnx.py     |  8 ++---
 .../transformation/resize_conv_to_deconv.py   |  6 ++--
 .../transformation/subpixel_to_deconv.py      |  6 ++--
 src/qonnx/util/basic.py                       | 32 +++++++++++++++++++
 8 files changed, 58 insertions(+), 46 deletions(-)

diff --git a/src/qonnx/transformation/change_datalayout.py b/src/qonnx/transformation/change_datalayout.py
index 07fbe400..62e6140b 100644
--- a/src/qonnx/transformation/change_datalayout.py
+++ b/src/qonnx/transformation/change_datalayout.py
@@ -30,7 +30,7 @@
 
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.infer_shapes import InferShapes
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import copy_metadata_props, get_by_name
 
 
 class ChangeDataLayoutQuantAvgPool2d(Transformation):
@@ -78,8 +78,7 @@ def apply(self, model):
                 graph.value_info.append(quantavg_out)
                 quantavg_out = quantavg_out.name
                 inp_trans_node = helper.make_node("Transpose", [node_input], [inp_trans_out], perm=[0, 2, 3, 1])
-                if hasattr(n, "metadata_props"):
-                    inp_trans_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, inp_trans_node)
                 quantavg_node = helper.make_node(
                     "QuantAvgPool2d",
                     [inp_trans_out],
@@ -92,12 +91,10 @@ def apply(self, model):
                     signed=signed,
                     data_layout="NHWC",
                 )
-                if hasattr(n, "metadata_props"):
-                    quantavg_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, quantavg_node)
                 # NHWC -> NCHW
                 out_trans_node = helper.make_node("Transpose", [quantavg_out], [node_output], perm=[0, 3, 1, 2])
-                if hasattr(n, "metadata_props"):
-                    out_trans_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, out_trans_node)
                 # insert nodes
                 graph.node.insert(node_ind, inp_trans_node)
                 graph.node.insert(node_ind + 1, quantavg_node)
diff --git a/src/qonnx/transformation/extract_quant_scale_zeropt.py b/src/qonnx/transformation/extract_quant_scale_zeropt.py
index 614df416..f76e5555 100644
--- a/src/qonnx/transformation/extract_quant_scale_zeropt.py
+++ b/src/qonnx/transformation/extract_quant_scale_zeropt.py
@@ -33,6 +33,7 @@
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.general import GiveUniqueParameterTensors, SortGraph
 from qonnx.transformation.remove import RemoveIdentityOps
+from qonnx.util.basic import copy_metadata_props
 
 
 class ExtractQuantScaleZeroPt(Transformation):
@@ -69,8 +70,7 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(inp_scaled)
                     inp_scale_node = helper.make_node("Div", [running_input, scale_nm], [inp_scaled_nm])
-                    if hasattr(node, "metadata_props"):
-                        inp_scale_node.metadata_props.extend(node.metadata_props)
+                    copy_metadata_props(node, inp_scale_node)
                     graph.node.append(inp_scale_node)
                     # create new Mul node
                     # remove scale from Quant node
@@ -89,8 +89,7 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(inp_zeropt)
                     inp_zeropt_node = helper.make_node("Add", [running_input, zeropt_nm], [inp_zeropt_nm])
-                    if hasattr(node, "metadata_props"):
-                        inp_zeropt_node.metadata_props.extend(node.metadata_props)
+                    copy_metadata_props(node, inp_zeropt_node)
                     graph.node.append(inp_zeropt_node)
                     # remove zeropt from Quant node
                     new_zeropt_nm = model.make_new_valueinfo_name()
@@ -112,8 +111,7 @@ def apply(self, model: ModelWrapper):
                     )
                     graph.value_info.append(out_zeropt)
                     out_zeropt_node = helper.make_node("Sub", [out_zeropt_nm, zeropt_nm], [final_output])
-                    if hasattr(node, "metadata_props"):
-                        out_zeropt_node.metadata_props.extend(node.metadata_props)
+                    copy_metadata_props(node, out_zeropt_node)
                     last_node.output[0] = out_zeropt_nm
                     graph.node.append(out_zeropt_node)
                     # important: when tracking a pointer to newly added nodes,
@@ -133,8 +131,7 @@ def apply(self, model: ModelWrapper):
                     last_node.output[0] = out_scale_nm
                     graph.value_info.append(out_scale)
                     out_scale_node = helper.make_node("Mul", [out_scale_nm, scale_nm], [final_output])
-                    if hasattr(node, "metadata_props"):
-                        out_scale_node.metadata_props.extend(node.metadata_props)
+                    copy_metadata_props(node, out_scale_node)
                     graph.node.append(out_scale_node)
 
                 if extract_scale or extract_zeropt:
diff --git a/src/qonnx/transformation/gemm_to_matmul.py b/src/qonnx/transformation/gemm_to_matmul.py
index 1298f3d6..245a0a2a 100644
--- a/src/qonnx/transformation/gemm_to_matmul.py
+++ b/src/qonnx/transformation/gemm_to_matmul.py
@@ -32,7 +32,7 @@
 from qonnx.core.datatype import DataType
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.remove import RemoveIdentityOps
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import copy_metadata_props, get_by_name
 
 
 class GemmToMatMul(Transformation):
@@ -76,8 +76,7 @@ def apply(self, model):
                     )
                     graph.value_info.append(inp_trans_out)
                     inp_trans_node = helper.make_node("Transpose", [n.input[0]], [inp_trans_out.name])
-                    if hasattr(n, "metadata_props"):
-                        inp_trans_node.metadata_props.extend(n.metadata_props)
+                    copy_metadata_props(n, inp_trans_node)
                     graph.node.insert(running_node_index, inp_trans_node)
                     running_node_index += 1
                     dt = model.get_tensor_datatype(n.input[0])
@@ -100,8 +99,7 @@ def apply(self, model):
                     )
                     graph.value_info.append(inp_trans_out)
                     inp_trans_node = helper.make_node("Transpose", [n.input[1]], [inp_trans_out.name])
-                    if hasattr(n, "metadata_props"):
-                        inp_trans_node.metadata_props.extend(n.metadata_props)
+                    copy_metadata_props(n, inp_trans_node)
                     graph.node.insert(running_node_index, inp_trans_node)
                     running_node_index += 1
                     # Copy over the datatype
@@ -113,8 +111,7 @@ def apply(self, model):
 
                 # Insert MatMul: A * B
                 matMul_node = helper.make_node("MatMul", [n.input[0], n.input[1]], [n.output[0]])
-                if hasattr(n, "metadata_props"):
-                    matMul_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, matMul_node)
                 graph.node.insert(running_node_index, matMul_node)
                 matMul_node = graph.node[running_node_index]
                 running_node_index += 1
@@ -150,8 +147,7 @@ def apply(self, model):
                     [act_mul_tensor.name, mul_tensor.name],
                     [n.output[0]],
                 )
-                if hasattr(n, "metadata_props"):
-                    mul_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, mul_node)
                 graph.node.insert(running_node_index, mul_node)
                 mul_node_main_branch = graph.node[running_node_index]
                 running_node_index += 1
@@ -183,8 +179,7 @@ def apply(self, model):
                     [n.input[2], mul_tensor.name],
                     [act_mul_tensor.name],
                 )
-                if hasattr(n, "metadata_props"):
-                    mul_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, mul_node)
                 graph.node.insert(running_node_index, mul_node)
                 running_node_index += 1
                 dt = model.get_tensor_datatype(n.input[2])
@@ -206,8 +201,7 @@ def apply(self, model):
                     [act_add_tensor.name, n.input[2]],
                     [n.output[0]],
                 )
-                if hasattr(n, "metadata_props"):
-                    add_node.metadata_props.extend(n.metadata_props)
+                copy_metadata_props(n, add_node)
                 graph.node.insert(running_node_index, add_node)
                 running_node_index += 1
 
diff --git a/src/qonnx/transformation/lower_convs_to_matmul.py b/src/qonnx/transformation/lower_convs_to_matmul.py
index d864d8d2..5140b71d 100644
--- a/src/qonnx/transformation/lower_convs_to_matmul.py
+++ b/src/qonnx/transformation/lower_convs_to_matmul.py
@@ -32,7 +32,7 @@
 
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.extract_conv_bias import ExtractBiasFromConv
-from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
+from qonnx.util.basic import auto_pad_to_explicit_padding, copy_metadata_props, get_by_name
 
 
 class LowerConvsToMatMul(Transformation):
@@ -178,12 +178,10 @@ def apply(self, model):
             matmul_input = im2col_out if need_im2col else inp_trans_out
             # do matmul
             matmul_node = helper.make_node("MatMul", [matmul_input, conv_weight_inp_name], [matmul_out])
-            if hasattr(node, "metadata_props"):
-                matmul_node.metadata_props.extend(node.metadata_props)
+            copy_metadata_props(node, matmul_node)
             # NHWC -> NCHW
             out_trans_node = helper.make_node("Transpose", [matmul_out], [cnv_output], perm=[0, 3, 1, 2])
-            if hasattr(node, "metadata_props"):
-                out_trans_node.metadata_props.extend(node.metadata_props)
+            copy_metadata_props(node, out_trans_node)
 
             nodes_to_insert.extend([matmul_node, out_trans_node])
 
diff --git a/src/qonnx/transformation/qcdq_to_qonnx.py b/src/qonnx/transformation/qcdq_to_qonnx.py
index b122d840..7aaf9271 100644
--- a/src/qonnx/transformation/qcdq_to_qonnx.py
+++ b/src/qonnx/transformation/qcdq_to_qonnx.py
@@ -34,7 +34,7 @@
 
 from qonnx.core.modelwrapper import ModelWrapper
 from qonnx.transformation.base import Transformation
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import copy_metadata_props, get_by_name
 
 
 def extract_elem_type(elem_type: int, clip_range=None) -> Tuple[int, int, bool]:
@@ -203,10 +203,8 @@ def apply(self, model: ModelWrapper) -> Tuple[ModelWrapper, bool]:
                     rounding_mode="ROUND",  # round-to-even
                     signed=signed,
                 )
-                # Pass on metadata from DequantizeLinear node since it's the only node that
-                # must be present to be able to perform this transformation.
-                if hasattr(node, "metadata_props"):
-                    fused_node.metadata_props.extend(node.metadata_props)
+                # Preserve metadata from all nodes being fused
+                copy_metadata_props(nodes_to_remove, fused_node)
                 model.graph.node.insert(dequant_node_index, fused_node)
             for node_to_remove in nodes_to_remove:
                 model.graph.node.remove(node_to_remove)
diff --git a/src/qonnx/transformation/resize_conv_to_deconv.py b/src/qonnx/transformation/resize_conv_to_deconv.py
index 30bc6c3c..7eda4fa7 100644
--- a/src/qonnx/transformation/resize_conv_to_deconv.py
+++ b/src/qonnx/transformation/resize_conv_to_deconv.py
@@ -33,7 +33,7 @@
 from qonnx.core.datatype import DataType
 from qonnx.custom_op.general.quant import quant, resolve_rounding_mode
 from qonnx.transformation.base import Transformation
-from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
+from qonnx.util.basic import auto_pad_to_explicit_padding, copy_metadata_props, get_by_name
 
 
 def _weight_convolution(cnv_weights: np.ndarray, scale: int) -> np.ndarray:
@@ -242,9 +242,7 @@ def apply(self, model):
                         group=group,
                         dilations=dilation,
                     )
-                    # Save metadata from the convolution node
-                    if hasattr(conv, "metadata_props"):
-                        deconv_node.metadata_props.extend(conv.metadata_props)
+                    copy_metadata_props(conv, deconv_node)
                     W_deconv_init = weight_name
                     if weight_prod is not None:
                         W_deconv_init = q_w_name
diff --git a/src/qonnx/transformation/subpixel_to_deconv.py b/src/qonnx/transformation/subpixel_to_deconv.py
index 241422c8..73ef3f8f 100644
--- a/src/qonnx/transformation/subpixel_to_deconv.py
+++ b/src/qonnx/transformation/subpixel_to_deconv.py
@@ -31,7 +31,7 @@
 from onnx import helper
 
 from qonnx.transformation.base import Transformation
-from qonnx.util.basic import auto_pad_to_explicit_padding, get_by_name
+from qonnx.util.basic import auto_pad_to_explicit_padding, copy_metadata_props, get_by_name
 
 
 def _weight_shuffle(cnv_weights: np.ndarray, block_size: int) -> np.ndarray:
@@ -197,9 +197,7 @@ def apply(self, model):
                         group=group,
                         dilations=dilation,
                     )
-                    # Save metadata from the original convolution node
-                    if hasattr(n, "metadata_props"):
-                        deconv_node.metadata_props.extend(n.metadata_props)
+                    copy_metadata_props(n, deconv_node)
                     W_deconv_init = weight_name
                     if weight_prod is not None:
                         W_deconv_init = q_w_name
diff --git a/src/qonnx/util/basic.py b/src/qonnx/util/basic.py
index 4e300dd1..1696c42b 100644
--- a/src/qonnx/util/basic.py
+++ b/src/qonnx/util/basic.py
@@ -350,3 +350,35 @@ def auto_pad_to_explicit_padding(autopad_str, idim_h, idim_w, k_h, k_w, stride_h
         return [pad_half_large_h, pad_half_large_w, pad_half_small_h, pad_half_small_w]
     else:
         raise Exception("Unsupported auto_pad: " + autopad_str)
+
+
+def copy_metadata_props(source_node, target_node):
+    """Copy metadata properties from source node(s) to target node.
+    
+    Parameters
+    ----------
+    source_node : onnx.NodeProto or list of onnx.NodeProto
+        Source node(s) from which to copy metadata_props. If a list is provided,
+        metadata from all nodes will be merged into the target node.
+    target_node : onnx.NodeProto
+        Target node to which metadata_props will be copied.
+    
+    Returns
+    -------
+    None
+        Modifies target_node in place by extending its metadata_props.
+    
+    Examples
+    --------
+    >>> # Copy from single node
+    >>> copy_metadata_props(old_node, new_node)
+    >>> 
+    >>> # Copy from multiple nodes (e.g., when fusing)
+    >>> copy_metadata_props([quant_node, dequant_node], fused_node)
+    """
+    # Handle both single node and list of nodes
+    source_nodes = source_node if isinstance(source_node, list) else [source_node]
+    
+    for node in source_nodes:
+        if hasattr(node, "metadata_props"):
+            target_node.metadata_props.extend(node.metadata_props)

From 6f3a631abc80d1a9bed7865fcd485d5a9bb212ad Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Thu, 30 Oct 2025 22:19:46 +0000
Subject: [PATCH 04/12] convert missed functions

---
 src/qonnx/transformation/channels_last.py     | 11 ++++-------
 src/qonnx/transformation/extract_conv_bias.py |  4 ++--
 src/qonnx/transformation/rebalance_conv.py    |  4 ++--
 3 files changed, 8 insertions(+), 11 deletions(-)

diff --git a/src/qonnx/transformation/channels_last.py b/src/qonnx/transformation/channels_last.py
index 8c934190..444a326c 100644
--- a/src/qonnx/transformation/channels_last.py
+++ b/src/qonnx/transformation/channels_last.py
@@ -40,7 +40,7 @@
 from qonnx.transformation.infer_shapes import InferShapes
 from qonnx.transformation.make_input_chanlast import MakeInputChannelsLast
 from qonnx.transformation.quant_constant_folding import FoldTransposeIntoQuantInit
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import copy_metadata_props, get_by_name
 from qonnx.util.onnx import is_eltwise_optype
 
 # Standard ONNX nodes which require a ChannelsLast data format to function properly
@@ -96,8 +96,7 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             new_t_inp = model.make_new_valueinfo_name()
             inv_perm = np.argsort(perm)
             new_transpose_node = helper.make_node("Transpose", [eltwise_inp], [new_t_inp], perm=inv_perm)
-            if hasattr(transpose_node, "metadata_props"):
-                new_transpose_node.metadata_props.extend(transpose_node.metadata_props)
+            copy_metadata_props(transpose_node, new_transpose_node)
             t_shape = np.transpose(np.empty(inp_shape), axes=inv_perm).shape
             model.set_tensor_shape(new_t_inp, t_shape)
             eltwise_node.input[ind] = new_t_inp
@@ -109,8 +108,7 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             model.set_initializer(unsqueeze_param_name, np.asarray(list(range(ndim_inp - ndim)), dtype=np.int64))
             unsqueeze_out_name = model.make_new_valueinfo_name()
             new_unsqueeze_node = helper.make_node("Unsqueeze", [eltwise_inp, unsqueeze_param_name], [unsqueeze_out_name])
-            if hasattr(eltwise_inp, "metadata_props"):
-                new_unsqueeze_node.metadata_props.extend(eltwise_inp.metadata_props)
+            copy_metadata_props(eltwise_inp, new_unsqueeze_node)
             unsqueeze_out_shape = np.expand_dims(np.empty(inp_shape), axis=tuple(range(ndim_inp - ndim))).shape
             model.set_tensor_shape(unsqueeze_out_name, unsqueeze_out_shape)
             model.graph.node.append(new_unsqueeze_node)
@@ -118,8 +116,7 @@ def move_transpose_past_eltwise(transpose_node, eltwise_node, model: ModelWrappe
             new_t_inp = model.make_new_valueinfo_name()
             inv_perm = np.argsort(perm)
             new_transpose_node = helper.make_node("Transpose", [unsqueeze_out_name], [new_t_inp], perm=inv_perm)
-            if hasattr(transpose_node, "metadata_props"):
-                new_transpose_node.metadata_props.extend(transpose_node.metadata_props)
+            copy_metadata_props(transpose_node, new_transpose_node)
             t_shape = np.transpose(np.empty(unsqueeze_out_shape), axes=inv_perm).shape
             model.set_tensor_shape(new_t_inp, t_shape)
             eltwise_node.input[ind] = new_t_inp
diff --git a/src/qonnx/transformation/extract_conv_bias.py b/src/qonnx/transformation/extract_conv_bias.py
index 1bf264e3..34b017bd 100644
--- a/src/qonnx/transformation/extract_conv_bias.py
+++ b/src/qonnx/transformation/extract_conv_bias.py
@@ -30,6 +30,7 @@
 from onnx import helper
 
 from qonnx.transformation.base import Transformation
+from qonnx.util.basic import copy_metadata_props
 
 
 class ExtractBiasFromConv(Transformation):
@@ -75,8 +76,7 @@ def apply(self, model):
                         [act_add_tensor.name, n.input[2]],
                         [n.output[0]],
                     )
-                    if hasattr(n, "metadata_props"):
-                        add_node.metadata_props.extend(n.metadata_props)
+                    copy_metadata_props(n, add_node)
                     graph.node.insert(node_ind, add_node)
 
                     # Repoint Conv output and remove bias tensor
diff --git a/src/qonnx/transformation/rebalance_conv.py b/src/qonnx/transformation/rebalance_conv.py
index 098bff20..0107a62a 100644
--- a/src/qonnx/transformation/rebalance_conv.py
+++ b/src/qonnx/transformation/rebalance_conv.py
@@ -31,6 +31,7 @@
 
 from qonnx.custom_op.registry import getCustomOp
 from qonnx.transformation.base import Transformation
+from qonnx.util.basic import copy_metadata_props
 
 
 class RebalanceIm2Col(Transformation):
@@ -103,8 +104,7 @@ def apply(self, model):
                     inp_reshape_node = helper.make_node(
                         "Reshape", [node.input[0], inp_shapedata.name], [inp_reshape_out.name]
                     )
-                    if hasattr(node, "metadata_props"):
-                        inp_reshape_node.metadata_props.extend(node.metadata_props)
+                    copy_metadata_props(node, inp_reshape_node)
                     graph.node.insert(running_node_index, inp_reshape_node)
                     # rewire Im2Col input
                     node.input[0] = inp_reshape_out.name

From 59ca168ebd4fa744b1ee4de15f8ac849f43464e1 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Thu, 30 Oct 2025 22:23:11 +0000
Subject: [PATCH 05/12] correct fused node source mistake

---
 src/qonnx/transformation/qcdq_to_qonnx.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/qonnx/transformation/qcdq_to_qonnx.py b/src/qonnx/transformation/qcdq_to_qonnx.py
index 7aaf9271..b4e18f25 100644
--- a/src/qonnx/transformation/qcdq_to_qonnx.py
+++ b/src/qonnx/transformation/qcdq_to_qonnx.py
@@ -204,7 +204,7 @@ def apply(self, model: ModelWrapper) -> Tuple[ModelWrapper, bool]:
                     signed=signed,
                 )
                 # Preserve metadata from all nodes being fused
-                copy_metadata_props(nodes_to_remove, fused_node)
+                copy_metadata_props(node, fused_node)
                 model.graph.node.insert(dequant_node_index, fused_node)
             for node_to_remove in nodes_to_remove:
                 model.graph.node.remove(node_to_remove)

From 159060670cf5692ffb6b79d88b65e66bec39327c Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Sat, 22 Nov 2025 00:41:31 +0000
Subject: [PATCH 06/12] add metadata preservation to batchnorm transform.

---
 src/qonnx/transformation/batchnorm_to_affine.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/src/qonnx/transformation/batchnorm_to_affine.py b/src/qonnx/transformation/batchnorm_to_affine.py
index c89d2bdc..d63dd178 100644
--- a/src/qonnx/transformation/batchnorm_to_affine.py
+++ b/src/qonnx/transformation/batchnorm_to_affine.py
@@ -32,7 +32,7 @@
 
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.infer_shapes import InferShapes
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import get_by_name, copy_metadata_props
 
 
 class BatchNormToAffine(Transformation):
@@ -89,6 +89,9 @@ def apply(self, model):
                 # create Mul and Add nodes to replace the batchnorm
                 mul_node = oh.make_node("Mul", [bn_input, mul_const.name], [mul_output.name])
                 add_node = oh.make_node("Add", [mul_output.name, add_const.name], [bn_output])
+                # preserve metadata from original batchnorm node
+                copy_metadata_props(n, mul_node)
+                copy_metadata_props(n, add_node)
                 # insert where the batchnorm is to preserve topological ordering
                 graph.node.insert(node_ind, mul_node)
                 graph.node.insert(node_ind + 1, add_node)

From 5690a790291a0cc9a54fd9fb96d8a25080d63101 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Sat, 22 Nov 2025 01:00:42 +0000
Subject: [PATCH 07/12] adding more copy metadata nodes.

---
 src/qonnx/transformation/batchnorm_to_affine.py   | 2 +-
 src/qonnx/transformation/bipolar_to_xnor.py       | 5 ++++-
 src/qonnx/transformation/channels_last.py         | 5 ++++-
 src/qonnx/transformation/lower_convs_to_matmul.py | 2 ++
 4 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/src/qonnx/transformation/batchnorm_to_affine.py b/src/qonnx/transformation/batchnorm_to_affine.py
index d63dd178..6190f867 100644
--- a/src/qonnx/transformation/batchnorm_to_affine.py
+++ b/src/qonnx/transformation/batchnorm_to_affine.py
@@ -32,7 +32,7 @@
 
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.infer_shapes import InferShapes
-from qonnx.util.basic import get_by_name, copy_metadata_props
+from qonnx.util.basic import copy_metadata_props, get_by_name 
 
 
 class BatchNormToAffine(Transformation):
diff --git a/src/qonnx/transformation/bipolar_to_xnor.py b/src/qonnx/transformation/bipolar_to_xnor.py
index 37f939a2..0b764ef8 100644
--- a/src/qonnx/transformation/bipolar_to_xnor.py
+++ b/src/qonnx/transformation/bipolar_to_xnor.py
@@ -36,7 +36,7 @@
 from qonnx.transformation.base import Transformation
 from qonnx.transformation.infer_datatypes import InferDataTypes
 from qonnx.transformation.infer_shapes import InferShapes
-from qonnx.util.basic import get_by_name
+from qonnx.util.basic import copy_metadata_props, get_by_name
 
 
 class ConvertBipolarMatMulToXnorPopcount(Transformation):
@@ -132,6 +132,9 @@ def find_prod_mt(x):
                     # create Mul and Add nodes to replace the batchnorm
                     mul_node = oh.make_node("Mul", [xnorpcout.name, mul_const.name], [mul_output.name])
                     add_node = oh.make_node("Add", [mul_output.name, add_const.name], [mm_output])
+                    # preserve metadata from original MatMul node
+                    copy_metadata_props(n, mul_node)
+                    copy_metadata_props(n, add_node)
                     # insert where the batchnorm is to preserve topological ordering
                     graph.node.insert(node_ind, mul_node)
                     graph.node.insert(node_ind + 1, add_node)
diff --git a/src/qonnx/transformation/channels_last.py b/src/qonnx/transformation/channels_last.py
index 1a2a0dcd..f9ca62bb 100644
--- a/src/qonnx/transformation/channels_last.py
+++ b/src/qonnx/transformation/channels_last.py
@@ -242,6 +242,7 @@ def apply(self, model):
                     # channels last transpose
                     inp_trans_node = helper.make_node("Transpose", [inp], [inp_trans_out], perm=to_channels_last_args(ndim))
                     graph.node.insert(running_node_index, inp_trans_node)
+                    copy_metadata_props(n, inp_trans_node)
                     running_node_index += 1
 
                     # Attach to original node
@@ -268,6 +269,7 @@ def apply(self, model):
                         "Transpose", [outp_trans_in], [outp], perm=to_channels_first_args(ndim)
                     )
                     graph.node.insert(running_node_index, outp_trans_node)
+                    copy_metadata_props(n, outp_trans_node)
                     running_node_index += 1
 
                     # Attach to original node
@@ -570,7 +572,8 @@ def apply(self, model):
                                     axis=1,
                                 )
                                 graph.node.insert(node_ind, flat_node)
-
+                                copy_metadata_props(n, flat_node)
+                                
                                 graph_modified = True
                             else:
                                 warnings.warn(
diff --git a/src/qonnx/transformation/lower_convs_to_matmul.py b/src/qonnx/transformation/lower_convs_to_matmul.py
index 5140b71d..f0981b34 100644
--- a/src/qonnx/transformation/lower_convs_to_matmul.py
+++ b/src/qonnx/transformation/lower_convs_to_matmul.py
@@ -152,6 +152,7 @@ def apply(self, model):
             # create new nodes
             # NCHW -> NHWC
             inp_trans_node = helper.make_node("Transpose", [cnv_input], [inp_trans_out], perm=[0, 2, 3, 1])
+            copy_metadata_props(node, inp_trans_node)
             nodes_to_insert = [inp_trans_node]
 
             if need_im2col:
@@ -174,6 +175,7 @@ def apply(self, model):
                     dilations=dilation,
                 )
                 nodes_to_insert.append(im2col_node)
+                copy_metadata_props(node, im2col_node)
 
             matmul_input = im2col_out if need_im2col else inp_trans_out
             # do matmul

From 7c04726f8bb9c51fef07ca4a05dd647053a70e2a Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Tue, 25 Nov 2025 23:42:20 +0000
Subject: [PATCH 08/12] added overwrite mode flag and basic unit tests

---
 src/qonnx/util/basic.py          | 22 ++++++++++--
 tests/util/test_copy_metadata.py | 61 ++++++++++++++++++++++++++++++++
 2 files changed, 81 insertions(+), 2 deletions(-)
 create mode 100644 tests/util/test_copy_metadata.py

diff --git a/src/qonnx/util/basic.py b/src/qonnx/util/basic.py
index 73f4cca2..2c52285a 100644
--- a/src/qonnx/util/basic.py
+++ b/src/qonnx/util/basic.py
@@ -362,7 +362,7 @@ def auto_pad_to_explicit_padding(autopad_str, idim_h, idim_w, k_h, k_w, stride_h
         raise Exception("Unsupported auto_pad: " + autopad_str)
 
 
-def copy_metadata_props(source_node, target_node):
+def copy_metadata_props(source_node, target_node, mode="overwrite"):
     """Copy metadata properties from source node(s) to target node.
     
     Parameters
@@ -386,9 +386,27 @@ def copy_metadata_props(source_node, target_node):
     >>> # Copy from multiple nodes (e.g., when fusing)
     >>> copy_metadata_props([quant_node, dequant_node], fused_node)
     """
+    assert mode in ["overwrite", "keep_existing"], "Copy Metadata Mode must be either 'overwrite' or 'keep_existing'."
+    
     # Handle both single node and list of nodes
     source_nodes = source_node if isinstance(source_node, list) else [source_node]
     
     for node in source_nodes:
         if hasattr(node, "metadata_props"):
-            target_node.metadata_props.extend(node.metadata_props)
+            
+            # check for existing keys in target_node to avoid duplicates
+            if hasattr(target_node, "metadata_props"):
+                existing_keys = {prop.key for prop in target_node.metadata_props}
+            else:
+                existing_keys = set()
+                
+            for prop in node.metadata_props:
+                if prop.key in existing_keys:
+                    if mode == "overwrite":
+                        # Overwrite existing metadata property 
+                        for existing_prop in target_node.metadata_props:
+                            if existing_prop.key == prop.key:
+                                existing_prop.value = prop.value
+                                break
+                else:
+                    target_node.metadata_props.append(prop)
\ No newline at end of file
diff --git a/tests/util/test_copy_metadata.py b/tests/util/test_copy_metadata.py
new file mode 100644
index 00000000..f976eabb
--- /dev/null
+++ b/tests/util/test_copy_metadata.py
@@ -0,0 +1,61 @@
+
+import onnx
+import pytest
+from qonnx.util.basic import copy_metadata_props
+
+
+def add_metadata(key, value):
+    return onnx.StringStringEntryProto(key=key, value=value)
+
+
+def test_copy_metadata_props():
+    
+    # Create source node with metadata
+    src_node = onnx.NodeProto(
+        metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")]
+    )
+    dst_node = onnx.NodeProto()
+    
+    copy_metadata_props(src_node, dst_node)
+    
+    assert len(dst_node.metadata_props) == 2
+    assert dst_node.metadata_props[0].key == "key1"
+    assert dst_node.metadata_props[0].value == "value1"
+    assert dst_node.metadata_props[1].key == "key2"
+    assert dst_node.metadata_props[1].value == "value2"
+
+
+@pytest.mark.parametrize("mode", ["keep_existing", "overwrite"])
+def test_copy_metadata_props_existing_target_md(mode):
+    
+    # Create source node with metadata
+    src_node = onnx.NodeProto(
+        metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")]
+    )
+    # Create destination node with existing metadata
+    dst_node = onnx.NodeProto(
+        metadata_props=[add_metadata("key1", "value3")]
+    )
+    
+    copy_metadata_props(src_node, dst_node, mode=mode)
+    
+    assert len(dst_node.metadata_props) == 2
+    assert dst_node.metadata_props[0].key == "key1"
+    
+    if mode == "keep_existing":
+        assert dst_node.metadata_props[0].value == "value3"  # Should keep existing
+    elif mode == "overwrite":
+        assert dst_node.metadata_props[0].value == "value1"  # Should be overwritten
+        
+    assert dst_node.metadata_props[1].key == "key2"
+    assert dst_node.metadata_props[1].value == "value2"
+    
+    
+def test_copy_metadata_props_bad_mode():
+    src_node = onnx.NodeProto(
+        metadata_props=[add_metadata("key1", "value1")]
+    )
+    dst_node = onnx.NodeProto()
+    
+    with pytest.raises(AssertionError):
+        copy_metadata_props(src_node, dst_node, mode="invalid_mode")
\ No newline at end of file

From 3085eee25c656cca08eed48b89f9e61be45e562f Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Tue, 25 Nov 2025 23:43:15 +0000
Subject: [PATCH 09/12] update documention copy_metadata_props

---
 src/qonnx/util/basic.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/src/qonnx/util/basic.py b/src/qonnx/util/basic.py
index 2c52285a..2752212b 100644
--- a/src/qonnx/util/basic.py
+++ b/src/qonnx/util/basic.py
@@ -372,6 +372,14 @@ def copy_metadata_props(source_node, target_node, mode="overwrite"):
         metadata from all nodes will be merged into the target node.
     target_node : onnx.NodeProto
         Target node to which metadata_props will be copied.
+    mode : str, optional
+        Mode for handling existing metadata properties in the target node.
+        Options are:
+        - "overwrite": Existing properties in the target node will be overwritten
+          by those from the source node(s) if they share the same key.
+        - "keep_existing": Existing properties in the target node will be kept,
+          and only new properties from the source node(s) will be added.
+        Default is "overwrite".
     
     Returns
     -------

From 43793044915aa32ab47c2430a11f7dd80b74d987 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Wed, 26 Nov 2025 17:25:56 +0000
Subject: [PATCH 10/12] add gemm2matmul test

---
 tests/util/test_copy_metadata.py | 34 +++++++++++++++++++++++++++++++-
 1 file changed, 33 insertions(+), 1 deletion(-)

diff --git a/tests/util/test_copy_metadata.py b/tests/util/test_copy_metadata.py
index f976eabb..81f39a09 100644
--- a/tests/util/test_copy_metadata.py
+++ b/tests/util/test_copy_metadata.py
@@ -1,6 +1,7 @@
 
 import onnx
 import pytest
+from qonnx.transformation.infer_shapes import InferShapes
 from qonnx.util.basic import copy_metadata_props
 
 
@@ -58,4 +59,35 @@ def test_copy_metadata_props_bad_mode():
     dst_node = onnx.NodeProto()
     
     with pytest.raises(AssertionError):
-        copy_metadata_props(src_node, dst_node, mode="invalid_mode")
\ No newline at end of file
+        copy_metadata_props(src_node, dst_node, mode="invalid_mode")
+        
+
+from onnxscript import script
+from onnxscript import opset9 as op
+from onnxscript import FLOAT
+from qonnx.core.modelwrapper import ModelWrapper
+from qonnx.transformation.gemm_to_matmul import GemmToMatMul
+        
+def test_copy_metadata_props_gemm2matmul():
+
+    @script()
+    def MyGemm(A: FLOAT[4, 5], B: FLOAT[5, 4], C: FLOAT[4, 4]) -> FLOAT[4, 4]:
+        return op.Gemm(A, B, C)
+
+    model_proto = MyGemm.to_model_proto()
+    gemm_node = model_proto.graph.node[0]
+    gemm_node.metadata_props.extend([
+       add_metadata("key1", "value1"),
+       add_metadata("key2", "value2")
+    ])
+
+    # Create Model Wrapper
+    mw = ModelWrapper(model_proto)
+    
+    transformed_mw = mw.transform(GemmToMatMul())
+   
+    for node in transformed_mw.graph.node:
+        assert node.metadata_props[0].key == 'key1'
+        assert node.metadata_props[0].value == 'value1'
+        assert node.metadata_props[1].key == 'key2'
+        assert node.metadata_props[1].value == 'value2'
\ No newline at end of file

From 9cbd803969fe0d844aef65ef96e9754130a63af8 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Wed, 26 Nov 2025 18:55:18 +0000
Subject: [PATCH 11/12] add batchnorm to affine test

---
 tests/util/test_copy_metadata.py | 46 +++++++++++++++++++++++++++++++-
 1 file changed, 45 insertions(+), 1 deletion(-)

diff --git a/tests/util/test_copy_metadata.py b/tests/util/test_copy_metadata.py
index 81f39a09..32a9ed1f 100644
--- a/tests/util/test_copy_metadata.py
+++ b/tests/util/test_copy_metadata.py
@@ -63,7 +63,7 @@ def test_copy_metadata_props_bad_mode():
         
 
 from onnxscript import script
-from onnxscript import opset9 as op
+from onnxscript import opset17 as op
 from onnxscript import FLOAT
 from qonnx.core.modelwrapper import ModelWrapper
 from qonnx.transformation.gemm_to_matmul import GemmToMatMul
@@ -86,6 +86,50 @@ def MyGemm(A: FLOAT[4, 5], B: FLOAT[5, 4], C: FLOAT[4, 4]) -> FLOAT[4, 4]:
     
     transformed_mw = mw.transform(GemmToMatMul())
    
+    for node in transformed_mw.graph.node:
+        assert node.metadata_props[0].key == 'key1'
+        assert node.metadata_props[0].value == 'value1'
+        assert node.metadata_props[1].key == 'key2'
+        assert node.metadata_props[1].value == 'value2'
+        
+
+from onnx import helper as oh
+import numpy as np
+import onnxscript
+from onnxscript.ir.passes.common import LiftConstantsToInitializersPass
+    
+    
+def test_copy_metadata_props_batchnorm2affine():
+    @script()
+    def MyBatchNorm(X: FLOAT[1, 3, 4, 4]) -> FLOAT[1, 3, 4, 4]:
+        scale = op.Constant(value=[[1.0, 1.0, 1.0]])
+        B = op.Constant(value=[[0.0, 0.0, 0.0]])
+        var = op.Constant(value=[[1.0, 1.0, 1.0]])
+        mean = op.Constant(value=[[0.0, 0.0, 0.0]])
+        return op.BatchNormalization(X, scale, B, mean, var, epsilon=1e-5, momentum=0.9)
+    
+    # remove cast-like nodes
+    model_proto = onnxscript.optimizer.optimize(MyBatchNorm.to_model_proto())    
+    
+    # batchnorm_to_affine requires initializers for scale/mean/var/bias
+    model_ir = onnxscript.ir.serde.deserialize_model(model_proto)
+    pass_ = LiftConstantsToInitializersPass(lift_all_constants=True, size_limit=1)
+    PassResult = pass_.call(model_ir)
+    model_proto = onnxscript.ir.serde.serialize_model(PassResult.model)
+    
+    # Add metadata to BatchNorm node
+    bn_node = model_proto.graph.node[0]
+    bn_node.metadata_props.extend([
+       add_metadata("key1", "value1"),
+       add_metadata("key2", "value2")
+    ])
+    
+    # Create Model Wrapper
+    mw = ModelWrapper(model_proto)
+    from qonnx.transformation.batchnorm_to_affine import BatchNormToAffine
+    transformed_mw = mw.transform(BatchNormToAffine())
+    
+    # Check that metadata was copied
     for node in transformed_mw.graph.node:
         assert node.metadata_props[0].key == 'key1'
         assert node.metadata_props[0].value == 'value1'

From 47c9bb855417e97bbda776c527f1a67a155811e1 Mon Sep 17 00:00:00 2001
From: Joshua Monson <joshmonson@microsoft.com>
Date: Wed, 26 Nov 2025 19:05:44 +0000
Subject: [PATCH 12/12] force precommit run

---
 tests/util/test_copy_metadata.py | 109 +++++++++++++------------------
 1 file changed, 44 insertions(+), 65 deletions(-)

diff --git a/tests/util/test_copy_metadata.py b/tests/util/test_copy_metadata.py
index 32a9ed1f..1cc913b9 100644
--- a/tests/util/test_copy_metadata.py
+++ b/tests/util/test_copy_metadata.py
@@ -1,7 +1,14 @@
+import pytest
 
 import onnx
-import pytest
-from qonnx.transformation.infer_shapes import InferShapes
+import onnxscript
+from onnxscript import FLOAT
+from onnxscript import opset17 as op
+from onnxscript import script
+from onnxscript.ir.passes.common import LiftConstantsToInitializersPass
+
+from qonnx.core.modelwrapper import ModelWrapper
+from qonnx.transformation.gemm_to_matmul import GemmToMatMul
 from qonnx.util.basic import copy_metadata_props
 
 
@@ -10,15 +17,12 @@ def add_metadata(key, value):
 
 
 def test_copy_metadata_props():
-    
     # Create source node with metadata
-    src_node = onnx.NodeProto(
-        metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")]
-    )
+    src_node = onnx.NodeProto(metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")])
     dst_node = onnx.NodeProto()
-    
+
     copy_metadata_props(src_node, dst_node)
-    
+
     assert len(dst_node.metadata_props) == 2
     assert dst_node.metadata_props[0].key == "key1"
     assert dst_node.metadata_props[0].value == "value1"
@@ -28,77 +32,54 @@ def test_copy_metadata_props():
 
 @pytest.mark.parametrize("mode", ["keep_existing", "overwrite"])
 def test_copy_metadata_props_existing_target_md(mode):
-    
     # Create source node with metadata
-    src_node = onnx.NodeProto(
-        metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")]
-    )
+    src_node = onnx.NodeProto(metadata_props=[add_metadata("key1", "value1"), add_metadata("key2", "value2")])
     # Create destination node with existing metadata
-    dst_node = onnx.NodeProto(
-        metadata_props=[add_metadata("key1", "value3")]
-    )
-    
+    dst_node = onnx.NodeProto(metadata_props=[add_metadata("key1", "value3")])
+
     copy_metadata_props(src_node, dst_node, mode=mode)
-    
+
     assert len(dst_node.metadata_props) == 2
     assert dst_node.metadata_props[0].key == "key1"
-    
+
     if mode == "keep_existing":
         assert dst_node.metadata_props[0].value == "value3"  # Should keep existing
     elif mode == "overwrite":
         assert dst_node.metadata_props[0].value == "value1"  # Should be overwritten
-        
+
     assert dst_node.metadata_props[1].key == "key2"
     assert dst_node.metadata_props[1].value == "value2"
-    
-    
+
+
 def test_copy_metadata_props_bad_mode():
-    src_node = onnx.NodeProto(
-        metadata_props=[add_metadata("key1", "value1")]
-    )
+    src_node = onnx.NodeProto(metadata_props=[add_metadata("key1", "value1")])
     dst_node = onnx.NodeProto()
-    
+
     with pytest.raises(AssertionError):
         copy_metadata_props(src_node, dst_node, mode="invalid_mode")
-        
 
-from onnxscript import script
-from onnxscript import opset17 as op
-from onnxscript import FLOAT
-from qonnx.core.modelwrapper import ModelWrapper
-from qonnx.transformation.gemm_to_matmul import GemmToMatMul
-        
-def test_copy_metadata_props_gemm2matmul():
 
+def test_copy_metadata_props_gemm2matmul():
     @script()
     def MyGemm(A: FLOAT[4, 5], B: FLOAT[5, 4], C: FLOAT[4, 4]) -> FLOAT[4, 4]:
         return op.Gemm(A, B, C)
 
     model_proto = MyGemm.to_model_proto()
     gemm_node = model_proto.graph.node[0]
-    gemm_node.metadata_props.extend([
-       add_metadata("key1", "value1"),
-       add_metadata("key2", "value2")
-    ])
+    gemm_node.metadata_props.extend([add_metadata("key1", "value1"), add_metadata("key2", "value2")])
 
     # Create Model Wrapper
     mw = ModelWrapper(model_proto)
-    
+
     transformed_mw = mw.transform(GemmToMatMul())
-   
+
     for node in transformed_mw.graph.node:
-        assert node.metadata_props[0].key == 'key1'
-        assert node.metadata_props[0].value == 'value1'
-        assert node.metadata_props[1].key == 'key2'
-        assert node.metadata_props[1].value == 'value2'
-        
-
-from onnx import helper as oh
-import numpy as np
-import onnxscript
-from onnxscript.ir.passes.common import LiftConstantsToInitializersPass
-    
-    
+        assert node.metadata_props[0].key == "key1"
+        assert node.metadata_props[0].value == "value1"
+        assert node.metadata_props[1].key == "key2"
+        assert node.metadata_props[1].value == "value2"
+
+
 def test_copy_metadata_props_batchnorm2affine():
     @script()
     def MyBatchNorm(X: FLOAT[1, 3, 4, 4]) -> FLOAT[1, 3, 4, 4]:
@@ -107,31 +88,29 @@ def MyBatchNorm(X: FLOAT[1, 3, 4, 4]) -> FLOAT[1, 3, 4, 4]:
         var = op.Constant(value=[[1.0, 1.0, 1.0]])
         mean = op.Constant(value=[[0.0, 0.0, 0.0]])
         return op.BatchNormalization(X, scale, B, mean, var, epsilon=1e-5, momentum=0.9)
-    
+
     # remove cast-like nodes
-    model_proto = onnxscript.optimizer.optimize(MyBatchNorm.to_model_proto())    
-    
+    model_proto = onnxscript.optimizer.optimize(MyBatchNorm.to_model_proto())
+
     # batchnorm_to_affine requires initializers for scale/mean/var/bias
     model_ir = onnxscript.ir.serde.deserialize_model(model_proto)
     pass_ = LiftConstantsToInitializersPass(lift_all_constants=True, size_limit=1)
     PassResult = pass_.call(model_ir)
     model_proto = onnxscript.ir.serde.serialize_model(PassResult.model)
-    
+
     # Add metadata to BatchNorm node
     bn_node = model_proto.graph.node[0]
-    bn_node.metadata_props.extend([
-       add_metadata("key1", "value1"),
-       add_metadata("key2", "value2")
-    ])
-    
+    bn_node.metadata_props.extend([add_metadata("key1", "value1"), add_metadata("key2", "value2")])
+
     # Create Model Wrapper
     mw = ModelWrapper(model_proto)
     from qonnx.transformation.batchnorm_to_affine import BatchNormToAffine
+
     transformed_mw = mw.transform(BatchNormToAffine())
-    
+
     # Check that metadata was copied
     for node in transformed_mw.graph.node:
-        assert node.metadata_props[0].key == 'key1'
-        assert node.metadata_props[0].value == 'value1'
-        assert node.metadata_props[1].key == 'key2'
-        assert node.metadata_props[1].value == 'value2'
\ No newline at end of file
+        assert node.metadata_props[0].key == "key1"
+        assert node.metadata_props[0].value == "value1"
+        assert node.metadata_props[1].key == "key2"
+        assert node.metadata_props[1].value == "value2"