diff --git a/onnxslim/core/__init__.py b/onnxslim/core/__init__.py
index 1a3f1e4..6e6e2b5 100644
--- a/onnxslim/core/__init__.py
+++ b/onnxslim/core/__init__.py
@@ -8,9 +8,8 @@
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
 from onnxslim.core.optimization import optimize_model
-from onnxslim.core.utils import delete_node
 from onnxslim.third_party.onnx_graphsurgeon.exporters.onnx_exporter import dtype_to_onnx
-from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Constant
+from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Constant, Variable
 from onnxslim.third_party.symbolic_shape_infer import SymbolicShapeInference
 from onnxslim.utils import save
 
@@ -173,7 +172,7 @@ def convert_data_format(model: onnx.ModelProto, dtype: str) -> onnx.ModelProto:
             if node.op == "Cast":
                 inp_dtype = [input.dtype for input in node.inputs][0]
                 if inp_dtype in [np.float16, np.float32]:
-                    delete_node(node)
+                    node.replace_all_uses_with(node.inputs[0])
                 else:
                     outp_dtype = [output.dtype for output in node.outputs][0]
                     if outp_dtype == np.float16:
diff --git a/onnxslim/core/optimization/__init__.py b/onnxslim/core/optimization/__init__.py
index d413ffd..7161432 100644
--- a/onnxslim/core/optimization/__init__.py
+++ b/onnxslim/core/optimization/__init__.py
@@ -5,7 +5,6 @@
 import onnx
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import get_node_feeds
 from onnxslim.core.pattern.registry import get_fusion_patterns
 from onnxslim.third_party.onnx_graphsurgeon.ir.graph import Graph
 
@@ -81,7 +80,7 @@ def get_previous_node_by_type(node, op_type, trajectory=None):
     """Recursively find and return the first preceding node of a specified type in the computation graph."""
     if trajectory is None:
         trajectory = []
-    node_feeds = get_node_feeds(node)
+    node_feeds = node.feeds
     for node_feed in node_feeds:
         trajectory.append(node_feed)
         if node_feed.op == op_type:
diff --git a/onnxslim/core/optimization/dead_node_elimination.py b/onnxslim/core/optimization/dead_node_elimination.py
index e686ac4..43aaf62 100644
--- a/onnxslim/core/optimization/dead_node_elimination.py
+++ b/onnxslim/core/optimization/dead_node_elimination.py
@@ -3,7 +3,6 @@
 import numpy as np
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.utils import delete_node
 from onnxslim.third_party.onnx_graphsurgeon.exporters.onnx_exporter import dtype_to_onnx
 from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Constant, Variable
 
@@ -20,28 +19,28 @@ def dead_node_elimination(graph, is_subgraph=False):
     for node in graph.nodes:
         if node.op in {"Identity", "Dropout"}:
             if not is_subgraph:
-                delete_node(node)
+                node.replace_all_uses_with(node.feeds[0])
                 logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Pad":
             if len(node.inputs) > 1 and isinstance(node.inputs[1], Constant):
                 pad_value = node.inputs[1].values.tolist()
                 pad_value = pad_value if isinstance(pad_value, list) else [pad_value]
                 if all(value == 0 for value in pad_value):
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Cast":
             inp_dtype = [dtype_to_onnx(input.dtype) for input in node.inputs][0]
             if inp_dtype == node.attrs["to"]:
-                delete_node(node)
+                node.replace_all_uses_with(node.feeds[0])
                 logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Reshape":
             if (node.inputs[0].shape and len(node.inputs[0].shape) == 1) and (
                 node.outputs[0].shape and len(node.outputs[0].shape) == 1
             ):
-                delete_node(node)
+                node.replace_all_uses_with(node.feeds[0])
                 logger.debug(f"removing {node.op} op: {node.name}")
             elif node.inputs[0].shape and node.outputs[0].shape and node.inputs[0].shape == node.outputs[0].shape:
-                delete_node(node)
+                node.replace_all_uses_with(node.feeds[0])
                 logger.debug(f"removing {node.op} op: {node.name}")
             else:
                 node_output_shape = node.outputs[0].shape
@@ -61,7 +60,7 @@ def dead_node_elimination(graph, is_subgraph=False):
                 idx, constant_variable = get_constant_variable(node, return_idx=True)
                 if np.all(constant_variable.values == 1):
                     var_idx = 0 if idx == 1 else 1
-                    delete_node(node, var_idx)
+                    node.replace_all_uses_with(node.feeds[var_idx])
                     logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Add":
             if (isinstance(node.inputs[1], Constant) and isinstance(node.inputs[0], Variable)) or (
@@ -71,10 +70,10 @@ def dead_node_elimination(graph, is_subgraph=False):
                 value = constant_variable.values
                 var_idx = 0 if idx == 1 else 1
                 if value.ndim == 0 and value == 0:
-                    delete_node(node, var_idx)
+                    node.replace_all_uses_with(node.feeds[var_idx])
                     logger.debug(f"removing {node.op} op: {node.name}")
                 elif np.all(value == 0) and (node.inputs[var_idx].shape == node.outputs[0].shape):
-                    delete_node(node, var_idx)
+                    node.replace_all_uses_with(node.feeds[var_idx])
                     logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Expand":
             # tests/test_onnx_nets.py::TestTimmClass::test_timm[lambda_resnet26rpt_256]
@@ -82,14 +81,14 @@ def dead_node_elimination(graph, is_subgraph=False):
                 constant_variable = node.inputs[1]
                 value = constant_variable.values
                 if node.inputs[0].shape == node.outputs[0].shape:
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
                 elif value.ndim == 0 and value == 1:
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Concat":
             if len(node.inputs) == 1:
-                delete_node(node)
+                node.replace_all_uses_with(node.feeds[0])
                 logger.debug(f"removing {node.op} op: {node.name}")
             else:
                 for input in node.inputs:
@@ -100,20 +99,20 @@ def dead_node_elimination(graph, is_subgraph=False):
                 constant_variable = node.inputs[1]
                 value = constant_variable.values
                 if value.ndim == 0 and value == 0:
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
                 elif np.all(value == 0) and (node.inputs[0].shape == node.outputs[0].shape):
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
         elif node.op == "Div":
             if isinstance(node.inputs[1], Constant) and isinstance(node.inputs[0], Variable):
                 constant_variable = node.inputs[1]
                 value = constant_variable.values
                 if value.ndim == 0 and value == 1:
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
                 elif np.all(value == 1) and (node.inputs[0].shape == node.outputs[0].shape):
-                    delete_node(node)
+                    node.replace_all_uses_with(node.feeds[0])
                     logger.debug(f"removing {node.op} op: {node.name}")
 
 
diff --git a/onnxslim/core/optimization/subexpression_elimination.py b/onnxslim/core/optimization/subexpression_elimination.py
index 23215ae..ec370f8 100644
--- a/onnxslim/core/optimization/subexpression_elimination.py
+++ b/onnxslim/core/optimization/subexpression_elimination.py
@@ -1,6 +1,5 @@
 import logging
 
-from onnxslim.core.pattern import get_node_users
 from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Variable
 
 logger = logging.getLogger("onnxslim")
@@ -17,7 +16,7 @@ def get_node_key(node):
         return "_".join(input_names) if input_names else None
 
     def replace_node_references(existing_node, to_be_removed_node):
-        users = get_node_users(to_be_removed_node)
+        users = to_be_removed_node.users
         for user in users:
             for inp in user.inputs:
                 if inp in to_be_removed_node.outputs:
diff --git a/onnxslim/core/pattern/__init__.py b/onnxslim/core/pattern/__init__.py
index 32bf0d5..ba929c6 100644
--- a/onnxslim/core/pattern/__init__.py
+++ b/onnxslim/core/pattern/__init__.py
@@ -8,29 +8,6 @@
 logger = logging.getLogger("onnxslim")
 
 
-def get_node_users(node):
-    """Retrieve the list of nodes that use the outputs of the given node."""
-    users = []
-    for output in node.outputs:  # output is a Variable
-        if output.is_output:
-            users.append(output)
-        users.extend(iter(output.outputs))
-    return users
-
-
-def get_node_feeds(node):
-    """Retrieve the list of nodes that provide inputs to the given node."""
-    feeds = []
-    for input in node.inputs:
-        if len(input.inputs) == 0 and not isinstance(input, Constant):
-            feeds.append(input)
-        elif isinstance(input, Constant):
-            feeds.append(input)
-        else:
-            feeds.extend(input if feed.op == "Split" else feed for feed in input.inputs)
-    return feeds
-
-
 def get_name(name):
     """Sanitizes the input string by replacing illegal characters with underscores and prefixing with an underscore if
     numeric.
@@ -142,7 +119,7 @@ def match_(node, pattern_node):
             if node.op == pattern_node.op:
                 setattr(self, pattern_node.name, node)
 
-                node_feeds = get_node_feeds(node)
+                node_feeds = node.feeds
                 if pattern_node.coarse_input_num:
                     if len(node_feeds) < len(pattern_node.input_names):
                         return False
@@ -207,8 +184,8 @@ def generate(self):
         for node in nodes:
             if node.op != "Constant":
                 name = get_name(node.name)
-                feeds = get_node_feeds(node)
-                users = get_node_users(node)
+                feeds = node.feeds
+                users = node.users
                 template.append(
                     " ".join(
                         [node.op, name, str(len(feeds)), str(len(users))]
diff --git a/onnxslim/core/pattern/elimination/reshape.py b/onnxslim/core/pattern/elimination/reshape.py
index 617f12f..26da8ab 100644
--- a/onnxslim/core/pattern/elimination/reshape.py
+++ b/onnxslim/core/pattern/elimination/reshape.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -33,7 +33,7 @@ def rewrite(self, opset=11):
         node = self.reshape_1
         first_reshape_node = node.i(0)
         first_reshape_node_inputs = list(first_reshape_node.inputs)
-        first_reshape_node_users = get_node_users(first_reshape_node)
+        first_reshape_node_users = first_reshape_node.users
         if len(first_reshape_node_users) == 1:
             second_reshape_node = node
 
diff --git a/onnxslim/core/pattern/elimination/slice.py b/onnxslim/core/pattern/elimination/slice.py
index 14bec9c..867ce62 100644
--- a/onnxslim/core/pattern/elimination/slice.py
+++ b/onnxslim/core/pattern/elimination/slice.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -29,7 +29,7 @@ def rewrite(self, opset=11):
         first_slice_node = self.slice_0
         first_slice_node_inputs = list(first_slice_node.inputs)
         if all(isinstance(input, gs.Constant) for input in first_slice_node_inputs[1:]):
-            first_slice_node_users = get_node_users(first_slice_node)
+            first_slice_node_users = first_slice_node.users
             if all(
                 user.op == "Slice" and all(isinstance(input, gs.Constant) for input in list(user.inputs)[1:])
                 for user in first_slice_node_users
diff --git a/onnxslim/core/pattern/elimination/unsqueeze.py b/onnxslim/core/pattern/elimination/unsqueeze.py
index c4fcf8d..a7f35c4 100644
--- a/onnxslim/core/pattern/elimination/unsqueeze.py
+++ b/onnxslim/core/pattern/elimination/unsqueeze.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -27,7 +27,7 @@ def rewrite(self, opset=11):
         """Rewrites an elimination pattern for unsqueeze nodes by optimizing nested slice operations."""
         match_case = {}
         node_unsqueeze_0 = self.unsqueeze_0
-        users_node_unsqueeze_0 = get_node_users(node_unsqueeze_0)
+        users_node_unsqueeze_0 = node_unsqueeze_0.users
         node_unsqueeze_1 = self.unsqueeze_1
         if len(users_node_unsqueeze_0) == 1 and node_unsqueeze_0.inputs[0].shape and node_unsqueeze_1.inputs[0].shape:
             if opset < 13 or (
diff --git a/onnxslim/core/pattern/fusion/convadd.py b/onnxslim/core/pattern/fusion/convadd.py
index dbf243d..96bc028 100644
--- a/onnxslim/core/pattern/fusion/convadd.py
+++ b/onnxslim/core/pattern/fusion/convadd.py
@@ -1,5 +1,5 @@
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -25,7 +25,7 @@ def rewrite(self, opset=11):
         match_case = {}
         conv_node = self.conv_0
         conv_weight = list(conv_node.inputs)[1]
-        conv_node_users = get_node_users(conv_node)
+        conv_node_users = conv_node.users
         node = self.add_0
         if (
             len(conv_node_users) == 1
diff --git a/onnxslim/core/pattern/fusion/convbn.py b/onnxslim/core/pattern/fusion/convbn.py
index f4aa0e0..4801600 100644
--- a/onnxslim/core/pattern/fusion/convbn.py
+++ b/onnxslim/core/pattern/fusion/convbn.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -27,7 +27,7 @@ def rewrite(self, opset=11):
         """Rewrites the weights and biases of a BatchNormalization layer fused with a convolution layer."""
         match_case = {}
         conv_transpose_node = self.conv_0
-        conv_transpose_node_users = get_node_users(conv_transpose_node)
+        conv_transpose_node_users = conv_transpose_node.users
         node = self.bn_0
         if len(conv_transpose_node_users) == 1:
             conv_transpose_weight = conv_transpose_node.inputs[1].values
diff --git a/onnxslim/core/pattern/fusion/gemm.py b/onnxslim/core/pattern/fusion/gemm.py
index 0ef1a0f..750f4f7 100644
--- a/onnxslim/core/pattern/fusion/gemm.py
+++ b/onnxslim/core/pattern/fusion/gemm.py
@@ -2,7 +2,7 @@
 
 import onnxslim.third_party.onnx_graphsurgeon as gs
 from onnxslim.core.optimization.dead_node_elimination import get_constant_variable
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -35,7 +35,7 @@ def rewrite(self, opset=11):
         input_variable = (
             matmul_node.inputs[0] if isinstance(matmul_node.inputs[1], gs.Constant) else matmul_node.inputs[1]
         )
-        users = get_node_users(matmul_node)
+        users = matmul_node.users
         if len(users) == 1 and matmul_bias_variable and len(matmul_bias_variable.shape) == 2:
             if (
                 input_variable.shape
diff --git a/onnxslim/core/pattern/fusion/padconv.py b/onnxslim/core/pattern/fusion/padconv.py
index 42bf176..df4132f 100644
--- a/onnxslim/core/pattern/fusion/padconv.py
+++ b/onnxslim/core/pattern/fusion/padconv.py
@@ -1,5 +1,5 @@
 import onnxslim.third_party.onnx_graphsurgeon as gs
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -33,7 +33,7 @@ def rewrite(self, opset=11):
         match_case = {}
         conv_node = self.conv_0
         pad_node = self.pad_0
-        pad_node_users = get_node_users(pad_node)
+        pad_node_users = pad_node.users
 
         pad_inputs = len(pad_node.inputs)
         if pad_inputs < 3 or (
diff --git a/onnxslim/core/pattern/fusion/reduce.py b/onnxslim/core/pattern/fusion/reduce.py
index 29f31d0..3322080 100644
--- a/onnxslim/core/pattern/fusion/reduce.py
+++ b/onnxslim/core/pattern/fusion/reduce.py
@@ -1,4 +1,4 @@
-from onnxslim.core.pattern import Pattern, PatternMatcher, get_node_users
+from onnxslim.core.pattern import Pattern, PatternMatcher
 from onnxslim.core.pattern.registry import register_fusion_pattern
 
 
@@ -25,7 +25,7 @@ def rewrite(self, opset=11):
         match_case = {}
         node = self.unsqueeze_0
         reduce_node = self.reduce_0
-        reduce_node_node_users = get_node_users(reduce_node)
+        reduce_node_node_users = reduce_node.users
         if len(reduce_node_node_users) == 1:
             unsqueeze_node = node
 
diff --git a/onnxslim/core/utils.py b/onnxslim/core/utils.py
deleted file mode 100644
index 33700db..0000000
--- a/onnxslim/core/utils.py
+++ /dev/null
@@ -1,32 +0,0 @@
-from onnxslim.core.pattern import get_node_feeds, get_node_users
-from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Constant, Variable
-
-
-def delete_node(node, input_var_idx=0, output_var_idx=0):
-    """Delete a node from the computation graph while re-linking its input and output to maintain graph integrity."""
-    input_variable = node.inputs[input_var_idx]
-    node_variable = node.outputs[output_var_idx]
-    next_nodes = get_node_users(node)
-
-    output_var = None
-    for next_node in next_nodes:
-        if isinstance(next_node, Variable) and next_node.is_output:
-            output_var = next_node
-            break
-
-    if output_var:
-        feeds = get_node_feeds(node)
-        feed = feeds[0]
-        if not isinstance(feed, (Variable, Constant)):
-            feed.outputs.remove(node.inputs[input_var_idx])
-            feed.outputs.append(node.outputs[output_var_idx])
-            for user in list(node.inputs[input_var_idx].outputs):
-                for i, input in enumerate(user.inputs):
-                    if input == node.inputs[input_var_idx]:
-                        user.inputs[i] = node.outputs[output_var_idx]
-            node.outputs.clear()
-    else:
-        for next_node in next_nodes:
-            index = next_node.inputs.index(node_variable)
-            next_node.inputs.pop(index)
-            next_node.inputs.insert(index, input_variable)
diff --git a/onnxslim/third_party/onnx_graphsurgeon/ir/node.py b/onnxslim/third_party/onnx_graphsurgeon/ir/node.py
index fccf357..b1cef6c 100644
--- a/onnxslim/third_party/onnx_graphsurgeon/ir/node.py
+++ b/onnxslim/third_party/onnx_graphsurgeon/ir/node.py
@@ -17,9 +17,9 @@
 
 from collections import OrderedDict
 from dataclasses import dataclass
-from typing import Dict, List
+from typing import Dict, List, Union
 
-from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Tensor
+from onnxslim.third_party.onnx_graphsurgeon.ir.tensor import Constant, Tensor, Variable
 from onnxslim.third_party.onnx_graphsurgeon.logger import G_LOGGER
 from onnxslim.third_party.onnx_graphsurgeon.util import misc
 
@@ -215,3 +215,57 @@ def __eq__(self, other):
 
         outputs_match = misc.sequences_equal(self.outputs, other.outputs)
         return self.domain == other.domain if outputs_match else False
+
+    @property
+    def users(self):
+        users = []
+        for output in self.outputs:  # output is a Variable
+            if output.is_output:
+                users.append(output)
+            users.extend(iter(output.outputs))
+        return users
+
+    @property
+    def feeds(self):
+        """Retrieve the list of nodes that provide inputs to the given node."""
+        feeds = []
+        for input in self.inputs:
+            if len(input.inputs) == 0 and not isinstance(input, Constant):
+                feeds.append(input)
+            elif isinstance(input, Constant):
+                feeds.append(input)
+            else:
+                feeds.extend(input if feed.op == "Split" else feed for feed in input.inputs)
+        return feeds
+
+    def replace_all_uses_with(self, node: Union["Node", "Tensor"], input_var_idx=0, output_var_idx=0):
+        """Replace all uses of this node with the given node."""
+        if isinstance(node, Node):
+            input_var = node.outputs[output_var_idx]
+        else:
+            input_var = node
+
+        output_var = None
+        for output in self.outputs:
+            if isinstance(output, Variable) and output.is_output:
+                output_var = output
+                break
+
+        if output_var:
+            feed = self.feeds[0]
+            if not isinstance(feed, (Variable, Constant)):
+                index = feed.outputs.index(self.inputs[input_var_idx])
+                feed.outputs.pop(index)
+                feed.outputs.insert(index, self.outputs[output_var_idx])
+                for user in list(self.inputs[input_var_idx].outputs):
+                    # do not use index here, because index will only return the first index of the input
+                    for i, input in enumerate(user.inputs):
+                        if input == self.inputs[input_var_idx]:
+                            user.inputs[i] = self.outputs[output_var_idx]
+                self.outputs.clear()
+        else:
+            for output in self.outputs:
+                for node_ in output.outputs:
+                    index = node_.inputs.index(output)
+                    node_.inputs.pop(index)
+                    node_.inputs.insert(index, input_var)
diff --git a/tests/test_modelzoo.py b/tests/test_modelzoo.py
index 6412ded..fe1c956 100644
--- a/tests/test_modelzoo.py
+++ b/tests/test_modelzoo.py
@@ -86,6 +86,8 @@ def test_layer_normalization_2d_axis0_expanded_ver18(self, request):
 
         with tempfile.TemporaryDirectory() as tempdir:
             slim(filename, os.path.join(tempdir, f"{name}_slim.onnx"), model_check=True)
+            summary = summarize_model(os.path.join(tempdir, f"{name}_slim.onnx"), tag=request.node.name)
+            assert summary.op_type_counts["Reshape"] == 1
 
     def test_padconv(self, request):
         name = request.node.originalname[len("test_") :]