diff --git a/nncf/torch/graph/operator_metatypes.py b/nncf/torch/graph/operator_metatypes.py
index 97835f2162a..ca038b77f24 100644
--- a/nncf/torch/graph/operator_metatypes.py
+++ b/nncf/torch/graph/operator_metatypes.py
@@ -545,7 +545,13 @@ class PTSigmoidMetatype(PTOperatorMetatype):
 class PTAddMetatype(PTOperatorMetatype):
     name = "AddOp"
     module_to_function_names = {
-        NamespaceTarget.TORCH_TENSOR: ["add", "__add__", "__iadd__", "__radd__"],
+        NamespaceTarget.TORCH_TENSOR: [
+            "add",
+            "add_",
+            "__add__",
+            "__iadd__",
+            "__radd__",
+        ],
         NamespaceTarget.TORCH: ["add"],
     }
     hw_config_names = [HWConfigOpName.ADD]
@@ -556,7 +562,13 @@ class PTAddMetatype(PTOperatorMetatype):
 class PTSubMetatype(PTOperatorMetatype):
     name = "SubOp"
     module_to_function_names = {
-        NamespaceTarget.TORCH_TENSOR: ["sub", "__sub__", "__isub__", "__rsub__"],
+        NamespaceTarget.TORCH_TENSOR: [
+            "sub",
+            "sub_",
+            "__sub__",
+            "__isub__",
+            "__rsub__",
+        ],
         NamespaceTarget.TORCH: ["sub"],
     }
     hw_config_names = [HWConfigOpName.SUBTRACT]
@@ -567,7 +579,7 @@ class PTSubMetatype(PTOperatorMetatype):
 class PTMulMetatype(PTOperatorMetatype):
     name = "MulOp"
     module_to_function_names = {
-        NamespaceTarget.TORCH_TENSOR: ["mul", "__mul__", "__imul__", "__rmul__"],
+        NamespaceTarget.TORCH_TENSOR: ["mul", "mul_", "__mul__", "__imul__", "__rmul__"],
         NamespaceTarget.TORCH: ["mul"],
     }
     hw_config_names = [HWConfigOpName.MULTIPLY]
@@ -580,6 +592,7 @@ class PTDivMetatype(PTOperatorMetatype):
     module_to_function_names = {
         NamespaceTarget.TORCH_TENSOR: [
             "div",
+            "div_",
             "__div__",
             "__idiv__",
             "__rdiv__",
@@ -691,13 +704,17 @@ class PTThresholdMetatype(PTOperatorMetatype):
 @PT_OPERATOR_METATYPES.register(is_subtype=True)
 class PTModuleBatchNormMetatype(PTModuleOperatorSubtype):
     name = "BatchNormOp"
-    module_to_function_names = {NamespaceTarget.TORCH_NN_FUNCTIONAL: ["batch_norm"]}
+    module_to_function_names = {
+        NamespaceTarget.TORCH_NN_FUNCTIONAL: ["batch_norm"],
+    }
 
 
 @PT_OPERATOR_METATYPES.register()
 class PTBatchNormMetatype(PTOperatorMetatype):
     name = "BatchNormOp"
-    module_to_function_names = {NamespaceTarget.TORCH_NN_FUNCTIONAL: ["batch_norm"]}
+    module_to_function_names = {
+        NamespaceTarget.TORCH_NN_FUNCTIONAL: ["batch_norm"],
+    }
     subtypes = [PTModuleBatchNormMetatype]
     weight_port_ids = [3]
     bias_port_id = 4
@@ -826,7 +843,7 @@ class PTGatherMetatype(PTOperatorMetatype):
     name = "GatherOp"
     module_to_function_names = {
         NamespaceTarget.TORCH_TENSOR: ["index_select", "__getitem__"],
-        NamespaceTarget.TORCH: ["gather", "index_select", "where"],
+        NamespaceTarget.TORCH: ["gather", "index_select", "select", "where"],
     }
 
 
@@ -841,7 +858,7 @@ class PTReshapeMetatype(PTOperatorMetatype):
     name = "ReshapeOp"
     module_to_function_names = {
         NamespaceTarget.TORCH_TENSOR: ["reshape", "view", "flatten", "unsqueeze"],
-        NamespaceTarget.TORCH: ["flatten", "unsqueeze"],
+        NamespaceTarget.TORCH: ["flatten", "unflatten", "unsqueeze"],
     }
     hw_config_names = [HWConfigOpName.RESHAPE, HWConfigOpName.UNSQUEEZE, HWConfigOpName.FLATTEN]
 
@@ -1028,7 +1045,9 @@ class PTSqrtMetatype(PTOperatorMetatype):
 @PT_OPERATOR_METATYPES.register()
 class PTInterpolateMetatype(PTOperatorMetatype):
     name = "InterpolateOp"
-    module_to_function_names = {NamespaceTarget.TORCH_NN_FUNCTIONAL: ["interpolate"]}
+    module_to_function_names = {
+        NamespaceTarget.TORCH_NN_FUNCTIONAL: ["interpolate"],
+    }
     hw_config_names = [HWConfigOpName.INTERPOLATE]
     num_expected_input_edges = 1
 
diff --git a/nncf/torch/graph/pattern_operations.py b/nncf/torch/graph/pattern_operations.py
index d9957871d87..1190079a5a6 100644
--- a/nncf/torch/graph/pattern_operations.py
+++ b/nncf/torch/graph/pattern_operations.py
@@ -10,54 +10,79 @@
 # limitations under the License.
 from nncf.common.graph.patterns import GraphPattern
 from nncf.common.graph.patterns import merge_two_types_of_operations
+from nncf.torch.graph import operator_metatypes as om
 
 LINEAR_OPERATIONS = {
     GraphPattern.METATYPE_ATTR: [
-        "linear",
-        "conv1d",
-        "conv2d",
-        "conv3d",
-        "conv_transpose1d",
-        "conv_transpose2d",
-        "conv_transpose3d",
-        "deform_conv2d",
-        "addmm",
-        "bmm",
-        "matmul",
-        "mm",
-        "baddbmm",
+        # Linear
+        om.PTLinearMetatype,
+        om.PTModuleLinearMetatype,
+        # Conv1D
+        om.PTConv1dMetatype,
+        om.PTDepthwiseConv1dSubtype,
+        om.PTModuleConv1dMetatype,
+        om.PTModuleDepthwiseConv1dSubtype,
+        # Conv2D
+        om.PTConv2dMetatype,
+        om.PTDepthwiseConv2dSubtype,
+        om.PTModuleConv2dMetatype,
+        om.PTModuleDepthwiseConv2dSubtype,
+        # Conv3D
+        om.PTConv3dMetatype,
+        om.PTDepthwiseConv3dSubtype,
+        om.PTModuleConv3dMetatype,
+        om.PTModuleDepthwiseConv3dSubtype,
+        # Transposed conv
+        om.PTConvTranspose1dMetatype,
+        om.PTModuleConvTranspose1dMetatype,
+        om.PTConvTranspose2dMetatype,
+        om.PTModuleConvTranspose2dMetatype,
+        om.PTConvTranspose3dMetatype,
+        om.PTModuleConvTranspose3dMetatype,
+        # Deform conv
+        om.PTDeformConv2dMetatype,
+        om.PTModuleDeformConv2dMetatype,
+        # MatMul
+        om.PTMatMulMetatype,
+        # Addmm
+        om.PTAddmmMetatype,
     ],
     GraphPattern.LABEL_ATTR: "LINEAR",
 }
 
 BATCH_NORMALIZATION_OPERATIONS = {
-    GraphPattern.METATYPE_ATTR: ["batch_norm", "batch_norm1d", "batch_norm2d", "batch_norm3d"],
+    GraphPattern.METATYPE_ATTR: [om.PTBatchNormMetatype, om.PTModuleBatchNormMetatype],
     GraphPattern.LABEL_ATTR: "BATCH_NORMALIZATION",
 }
 
 GROUP_NORMALIZATION_OPERATIONS = {
-    GraphPattern.METATYPE_ATTR: ["group_norm"],
+    GraphPattern.METATYPE_ATTR: [om.PTGroupNormMetatype, om.PTModuleGroupNormMetatype],
     GraphPattern.LABEL_ATTR: "GROUP_NORMALIZATION",
 }
 
 LAYER_NORMALIZATION_OPERATIONS = {
-    GraphPattern.METATYPE_ATTR: ["layer_norm"],
+    GraphPattern.METATYPE_ATTR: [om.PTLayerNormMetatype, om.PTModuleLayerNormMetatype],
     GraphPattern.LABEL_ATTR: "LAYER_NORMALIZATION",
 }
 
-RELU_OPERATIONS = {GraphPattern.METATYPE_ATTR: ["relu", "relu_", "hardtanh"], GraphPattern.LABEL_ATTR: "RELU"}
+RELU_OPERATIONS = {
+    GraphPattern.METATYPE_ATTR: [
+        om.PTRELUMetatype,
+        om.PTHardTanhMetatype,
+    ],
+    GraphPattern.LABEL_ATTR: "RELU",
+}
 
 NON_RELU_ACTIVATIONS_OPERATIONS = {
     GraphPattern.METATYPE_ATTR: [
-        "elu",
-        "elu_",
-        "prelu",
-        "leaky_relu",
-        "sigmoid",
-        "gelu",
-        "silu",
-        "hardsigmoid",
-        "hardswish",
+        om.PTELUMetatype,
+        om.PTPRELUMetatype,
+        om.PTLeakyRELUMetatype,
+        om.PTSigmoidMetatype,
+        om.PTGELUMetatype,
+        om.PTSILUMetatype,
+        om.PTHardSigmoidMetatype,
+        om.PTHardSwishMetatype,
     ],
     GraphPattern.LABEL_ATTR: "NON_RELU_ACTIVATIONS",
 }
@@ -67,13 +92,6 @@
 )
 
 ARITHMETIC_OPERATIONS = {
-    GraphPattern.METATYPE_ATTR: ["__iadd__", "__add__", "__mul__", "__rmul__", "__truediv__"],
+    GraphPattern.METATYPE_ATTR: [om.PTAddMetatype, om.PTSubMetatype, om.PTMulMetatype, om.PTDivMetatype],
     GraphPattern.LABEL_ATTR: "ARITHMETIC",
 }
-
-# This type may be useful in the future
-
-POOLING_OPERATIONS = {
-    GraphPattern.METATYPE_ATTR: ["adaptive_avg_pool2d", "adaptive_avg_pool3d", "avg_pool2d", "avg_pool3d"],
-    GraphPattern.LABEL_ATTR: "POOLING",
-}
diff --git a/nncf/torch/hardware/fused_patterns.py b/nncf/torch/hardware/fused_patterns.py
index 3cff4d1ce98..48c6a38ba40 100644
--- a/nncf/torch/hardware/fused_patterns.py
+++ b/nncf/torch/hardware/fused_patterns.py
@@ -12,6 +12,7 @@
 from nncf.common.graph.patterns import GraphPattern
 from nncf.common.graph.patterns import HWFusedPatternNames
 from nncf.common.utils.registry import Registry
+from nncf.torch.graph import operator_metatypes as om
 from nncf.torch.graph.operator_metatypes import PTInputNoopMetatype
 from nncf.torch.graph.pattern_operations import ARITHMETIC_OPERATIONS
 from nncf.torch.graph.pattern_operations import ATOMIC_ACTIVATIONS_OPERATIONS
@@ -30,12 +31,12 @@ def create_l2_norm_operations() -> GraphPattern:
     pattern = GraphPattern()
 
     outside_pattern_node = pattern.add_node(label="*OUTSIDE_PATTERN_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    pow_node = pattern.add_node(label="POW", type="pow")
-    sum_node = pattern.add_node(label="SUM", type="sum")
-    sqrt_node = pattern.add_node(label="SQRT", type="sqrt")
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    div_node = pattern.add_node(label="DIV", type="div")
-    mul_node = pattern.add_node(label="MUL", type="__rmul__")
+    pow_node = pattern.add_node(label="POW", type=om.PTPowerMetatype)
+    sum_node = pattern.add_node(label="SUM", type=om.PTSumMetatype)
+    sqrt_node = pattern.add_node(label="SQRT", type=om.PTSqrtMetatype)
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    div_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
 
     pattern.add_edge(outside_pattern_node, pow_node)
     pattern.add_edge(pow_node, sum_node)
@@ -53,8 +54,8 @@ def create_l2_norm_operations() -> GraphPattern:
 @PT_HW_FUSED_PATTERNS.register(HWFusedPatternNames.SHIFT_SCALE)
 def create_shift_scale() -> GraphPattern:
     pattern = GraphPattern()
-    add_node = pattern.add_node(label="ADD, SUB", type=["__add__", "__sub__"])
-    truediv_node = pattern.add_node(label="MUL, DIV", type=["__mul__", "__truediv__"])
+    add_node = pattern.add_node(label="ADD, SUB", type=[om.PTAddMetatype, om.PTSubMetatype])
+    truediv_node = pattern.add_node(label="MUL, DIV", type=[om.PTMulMetatype, om.PTDivMetatype])
     pattern.add_edge(add_node, truediv_node)
     return pattern
 
@@ -62,7 +63,7 @@ def create_shift_scale() -> GraphPattern:
 @PT_HW_FUSED_PATTERNS.register(HWFusedPatternNames.INPUT_SHIFT_SCALE)
 def create_input_shift_scale() -> GraphPattern:
     pattern = GraphPattern()
-    pattern.add_node(**{GraphPattern.LABEL_ATTR: "MODEL_INPUT", GraphPattern.METATYPE_ATTR: PTInputNoopMetatype})
+    pattern.add_node(label="MODEL_INPUT", type=PTInputNoopMetatype)
     shift_scale = create_shift_scale()
     pattern.join_patterns(shift_scale)
     return pattern
@@ -177,8 +178,8 @@ def create_group_norm_relu_operations() -> GraphPattern:
 @PT_HW_FUSED_PATTERNS.register(HWFusedPatternNames.LINEAR_CONST_MULTIPLY)
 def create_linear_const_multiply() -> GraphPattern:
     pattern = GraphPattern()
-    linear_node = pattern.add_node(label="linear", type="linear")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
+    linear_node = pattern.add_node(label="linear", type=[om.PTLinearMetatype, om.PTModuleLinearMetatype])
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
     pattern.add_edge(linear_node, mul_node)
 
     return pattern
@@ -220,8 +221,8 @@ def activation_operations() -> GraphPattern:
 def create_swish_act() -> GraphPattern:
     pattern = GraphPattern()
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    sigmoid_node = pattern.add_node(label="SIGMOID", type="sigmoid")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
+    sigmoid_node = pattern.add_node(label="SIGMOID", type=om.PTSigmoidMetatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
 
     pattern.add_edge(input_pattern_node, sigmoid_node)
     pattern.add_edge(sigmoid_node, mul_node)
@@ -235,10 +236,10 @@ def create_h_swish_act() -> GraphPattern:
     # Mul -> Div version
     pattern = GraphPattern()
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    hardtanh_node = pattern.add_node(label="HARDTANH", type="hardtanh")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    hardtanh_node = pattern.add_node(label="HARDTANH", type=om.PTHardTanhMetatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(input_pattern_node, mul_node)
@@ -250,10 +251,10 @@ def create_h_swish_act() -> GraphPattern:
     # Div -> Mul version
     pattern = GraphPattern()
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    hardtanh_node = pattern.add_node(label="HARDTANH", type="hardtanh")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    hardtanh_node = pattern.add_node(label="HARDTANH", type=om.PTHardTanhMetatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(input_pattern_node, mul_node)
@@ -265,10 +266,10 @@ def create_h_swish_act() -> GraphPattern:
     # ReLU6 version - Mul -> Div
     pattern = GraphPattern()
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    relu6_node = pattern.add_node(label="RELU6", type="relu6")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    relu6_node = pattern.add_node(label="RELU6", type=om.PTRELU6Metatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(input_pattern_node, mul_node)
@@ -280,10 +281,10 @@ def create_h_swish_act() -> GraphPattern:
     # ReLU6 version - Div -> Mul
     pattern = GraphPattern()
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    relu6_node = pattern.add_node(label="RELU6", type="relu6")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
-    mul_node = pattern.add_node(label="MUL", type="__mul__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    relu6_node = pattern.add_node(label="RELU6", type=om.PTRELU6Metatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
+    mul_node = pattern.add_node(label="MUL", type=om.PTMulMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(input_pattern_node, mul_node)
@@ -303,9 +304,9 @@ def create_h_sigmoid_act() -> GraphPattern:
     pattern = GraphPattern()
 
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    hardtanh_node = pattern.add_node(label="HARDTANH", type="hardtanh")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    hardtanh_node = pattern.add_node(label="HARDTANH", type=om.PTHardTanhMetatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(add_node, hardtanh_node)
@@ -317,9 +318,9 @@ def create_h_sigmoid_act() -> GraphPattern:
     pattern = GraphPattern()
 
     input_pattern_node = pattern.add_node(label="*INPUT_NODE*", type=GraphPattern.NON_PATTERN_NODE_TYPE)
-    add_node = pattern.add_node(label="ADD", type="__add__")
-    relu6_node = pattern.add_node(label="RELU6", type="relu6")
-    truediv_node = pattern.add_node(label="DIV", type="__truediv__")
+    add_node = pattern.add_node(label="ADD", type=om.PTAddMetatype)
+    relu6_node = pattern.add_node(label="RELU6", type=om.PTRELU6Metatype)
+    truediv_node = pattern.add_node(label="DIV", type=om.PTDivMetatype)
 
     pattern.add_edge(input_pattern_node, add_node)
     pattern.add_edge(add_node, relu6_node)
diff --git a/nncf/torch/quantization/ignored_patterns.py b/nncf/torch/quantization/ignored_patterns.py
index b1e6c522ada..895849c244e 100644
--- a/nncf/torch/quantization/ignored_patterns.py
+++ b/nncf/torch/quantization/ignored_patterns.py
@@ -11,6 +11,7 @@
 from nncf.common.graph.patterns.patterns import GraphPattern
 from nncf.common.graph.patterns.patterns import IgnoredPatternNames
 from nncf.common.utils.registry import Registry
+from nncf.torch.graph import operator_metatypes as om
 from nncf.torch.graph.pattern_operations import ATOMIC_ACTIVATIONS_OPERATIONS
 from nncf.torch.graph.pattern_operations import LINEAR_OPERATIONS
 
@@ -19,11 +20,11 @@
 
 def _add_softmax_matmul(
     pattern: GraphPattern,
-    matmul_aliases,
-    reshape_squeeze_aliases,
-    gather_aliases,
-    transpose_aliases,
-    concat_aliases,
+    matmul_metatypes,
+    reshape_squeeze_metatypes,
+    gather_metatypes,
+    transpose_metatypes,
+    concat_metatypes,
 ) -> None:
     #       SOFTMAX  RESHAPE||TRANSPOSE||GATHER||SQUEEZE||CONCAT
     #           \              /
@@ -32,9 +33,9 @@ def _add_softmax_matmul(
     #              \        /
     #               \      /
     #                MATMUL
-    branch_matmul_nodes = reshape_squeeze_aliases + gather_aliases + transpose_aliases + concat_aliases
-    softmax = pattern.add_node(**{GraphPattern.LABEL_ATTR: "SOFTMAX", GraphPattern.METATYPE_ATTR: "softmax"})
-    matmul = pattern.add_node(**{GraphPattern.LABEL_ATTR: "MATMUL", GraphPattern.METATYPE_ATTR: matmul_aliases})
+    branch_matmul_nodes = reshape_squeeze_metatypes + gather_metatypes + transpose_metatypes + concat_metatypes
+    softmax = pattern.add_node(**{GraphPattern.LABEL_ATTR: "SOFTMAX", GraphPattern.METATYPE_ATTR: om.PTSoftmaxMetatype})
+    matmul = pattern.add_node(**{GraphPattern.LABEL_ATTR: "MATMUL", GraphPattern.METATYPE_ATTR: matmul_metatypes})
     matmul_branch_nodes = pattern.add_node(
         **{GraphPattern.LABEL_ATTR: "NON_PATTERN", GraphPattern.METATYPE_ATTR: branch_matmul_nodes}
     )
@@ -44,11 +45,11 @@ def _add_softmax_matmul(
 
 def _add_softmax_reshape_matmul(
     pattern: GraphPattern,
-    matmul_aliases,
-    reshape_squeeze_aliases,
-    gather_aliases,
-    transpose_aliases,
-    concat_aliases,
+    matmul_metatypes,
+    reshape_squeeze_metatypes,
+    gather_metatypes,
+    transpose_metatypes,
+    concat_metatypes,
 ) -> None:
     #       SOFTMAX
     #           \
@@ -62,12 +63,12 @@ def _add_softmax_reshape_matmul(
     #                     \         /
     #                      \       /
     #                        MATMUL
-    branch_matmul_nodes = reshape_squeeze_aliases + gather_aliases + transpose_aliases + concat_aliases
-    softmax = pattern.add_node(**{GraphPattern.LABEL_ATTR: "SOFTMAX", GraphPattern.METATYPE_ATTR: "softmax"})
+    branch_matmul_nodes = reshape_squeeze_metatypes + gather_metatypes + transpose_metatypes + concat_metatypes
+    softmax = pattern.add_node(**{GraphPattern.LABEL_ATTR: "SOFTMAX", GraphPattern.METATYPE_ATTR: om.PTSoftmaxMetatype})
     reshape = pattern.add_node(
-        **{GraphPattern.LABEL_ATTR: "RESHAPE", GraphPattern.METATYPE_ATTR: reshape_squeeze_aliases}
+        **{GraphPattern.LABEL_ATTR: "RESHAPE", GraphPattern.METATYPE_ATTR: reshape_squeeze_metatypes}
     )
-    matmul = pattern.add_node(**{GraphPattern.LABEL_ATTR: "MATMUL", GraphPattern.METATYPE_ATTR: matmul_aliases})
+    matmul = pattern.add_node(**{GraphPattern.LABEL_ATTR: "MATMUL", GraphPattern.METATYPE_ATTR: matmul_metatypes})
     matmul_branch_nodes = pattern.add_node(
         **{GraphPattern.LABEL_ATTR: "RESHAPE||TRANSPOSE||GATHER", GraphPattern.METATYPE_ATTR: branch_matmul_nodes}
     )
@@ -79,35 +80,28 @@ def _add_softmax_reshape_matmul(
 
 @PT_IGNORED_PATTERNS.register(IgnoredPatternNames.MULTIHEAD_ATTENTION_OUTPUT)
 def create_multihead_attention_output() -> GraphPattern:
-    matmul_aliases = ["linear", "addmm", "matmul", "bmm", "mm", "baddbmm", "__matmul__"]
-    reshape_squeeze_aliases = [
-        "reshape",
-        "view",
-        "flatten",
-        "unsqueeze",
-        "squeeze",
-        "unbind",
-    ]
-    gather_aliases = ["gather", "index_select", "where", "index_select", "__getitem__"]
-    transpose_aliases = ["transpose", "permute", "transpose_"]
-    concat_aliases = ["cat", "stack"]
+    matmul_metatypes = [om.PTLinearMetatype, om.PTAddmmMetatype, om.PTMatMulMetatype]
+    reshape_squeeze_metatypes = [om.PTReshapeMetatype, om.PTSqueezeMetatype, om.PTSplitMetatype]
+    gather_metatypes = [om.PTGatherMetatype]
+    transpose_metatypes = [om.PTTransposeMetatype]
+    concat_metatypes = [om.PTCatMetatype]
 
     pattern = GraphPattern()
     _add_softmax_matmul(
         pattern,
-        matmul_aliases=matmul_aliases,
-        reshape_squeeze_aliases=reshape_squeeze_aliases,
-        gather_aliases=gather_aliases,
-        transpose_aliases=transpose_aliases,
-        concat_aliases=concat_aliases,
+        matmul_metatypes=matmul_metatypes,
+        reshape_squeeze_metatypes=reshape_squeeze_metatypes,
+        gather_metatypes=gather_metatypes,
+        transpose_metatypes=transpose_metatypes,
+        concat_metatypes=concat_metatypes,
     )
     _add_softmax_reshape_matmul(
         pattern,
-        matmul_aliases=matmul_aliases,
-        reshape_squeeze_aliases=reshape_squeeze_aliases,
-        gather_aliases=gather_aliases,
-        transpose_aliases=transpose_aliases,
-        concat_aliases=concat_aliases,
+        matmul_metatypes=matmul_metatypes,
+        reshape_squeeze_metatypes=reshape_squeeze_metatypes,
+        gather_metatypes=gather_metatypes,
+        transpose_metatypes=transpose_metatypes,
+        concat_metatypes=concat_metatypes,
     )
     return pattern
 
@@ -117,16 +111,16 @@ def create_multihead_attention_output() -> GraphPattern:
 def create_se_block() -> GraphPattern:
     MEAN_OPERATIONS = {
         GraphPattern.LABEL_ATTR: "REDUCE_MEAN",
-        GraphPattern.METATYPE_ATTR: ["avg_pool2d", "adaptive_avg_pool2d", "avg_pool3d", "adaptive_avg_pool3d", "mean"],
+        GraphPattern.METATYPE_ATTR: [om.PTAvgPool2dMetatype, om.PTAvgPool3dMetatype, om.PTMeanMetatype],
         GraphPattern.PATTERN_NODE_TO_EXCLUDE: True,
     }
     SYGMOID_OPERATIONS = {
         GraphPattern.LABEL_ATTR: "SIGMOID",
-        GraphPattern.METATYPE_ATTR: ["sigmoid", "hardsigmoid"],
+        GraphPattern.METATYPE_ATTR: [om.PTSigmoidMetatype, om.PTHardSigmoidMetatype],
     }
     MUL_OPERATION = {
         GraphPattern.LABEL_ATTR: "MUL",
-        GraphPattern.METATYPE_ATTR: "__mul__",
+        GraphPattern.METATYPE_ATTR: om.PTMulMetatype,
         GraphPattern.PATTERN_NODE_TO_EXCLUDE: True,
     }
 
@@ -154,10 +148,10 @@ def get_se_block_with_bias_pattern() -> GraphPattern:
         any_node = pattern.add_node(label="NON_PATTERN_NODE", type=GraphPattern.NON_PATTERN_NODE_TYPE)
         reduce_mean_node = pattern.add_node(**MEAN_OPERATIONS)
         linear_node_1 = pattern.add_node(**LINEAR_OPERATIONS)
-        add_node_1 = pattern.add_node(label="ADD_BIAS", type=["__add__", "__sub__"])
+        add_node_1 = pattern.add_node(label="ADD_BIAS", type=[om.PTAddMetatype, om.PTSubMetatype])
         activation_node_1 = pattern.add_node(**ATOMIC_ACTIVATIONS_OPERATIONS)
         linear_node_2 = pattern.add_node(**LINEAR_OPERATIONS)
-        add_node_2 = pattern.add_node(label="ADD_BIAS", type=["__add__", "__sub__"])
+        add_node_2 = pattern.add_node(label="ADD_BIAS", type=[om.PTAddMetatype, om.PTSubMetatype])
         activation_node_2 = pattern.add_node(**SYGMOID_OPERATIONS)
         multiply_node = pattern.add_node(**MUL_OPERATION)
 
@@ -174,7 +168,7 @@ def get_se_block_with_bias_pattern() -> GraphPattern:
 
     RESHAPE_NODES = {
         GraphPattern.LABEL_ATTR: "RESHAPE",
-        GraphPattern.METATYPE_ATTR: ["reshape", "view", "flatten", "unsqueeze"],
+        GraphPattern.METATYPE_ATTR: om.PTReshapeMetatype,
     }
 
     def get_se_block_with_reshape() -> GraphPattern:
@@ -206,10 +200,10 @@ def get_se_block_with_bias_and_reshape() -> GraphPattern:
         reduce_mean_node = pattern.add_node(**MEAN_OPERATIONS)
         reshape_node_1 = pattern.add_node(**RESHAPE_NODES)
         linear_node_1 = pattern.add_node(**LINEAR_OPERATIONS)
-        add_node_1 = pattern.add_node(label="ADD_BIAS", type=["__add__", "__sub__"])
+        add_node_1 = pattern.add_node(label="ADD_BIAS", type=[om.PTAddMetatype, om.PTSubMetatype])
         activation_node_1 = pattern.add_node(**ATOMIC_ACTIVATIONS_OPERATIONS)
         linear_node_2 = pattern.add_node(**LINEAR_OPERATIONS)
-        add_node_2 = pattern.add_node(label="ADD_BIAS", type=["__add__", "__sub__"])
+        add_node_2 = pattern.add_node(label="ADD_BIAS", type=[om.PTAddMetatype, om.PTSubMetatype])
         activation_node_2 = pattern.add_node(**SYGMOID_OPERATIONS)
         reshape_node_2 = pattern.add_node(**RESHAPE_NODES)
         multiply_node = pattern.add_node(**MUL_OPERATION)
diff --git a/tests/common/quantization/mock_graphs.py b/tests/common/quantization/mock_graphs.py
index b8cb41ee142..ada50e90a21 100644
--- a/tests/common/quantization/mock_graphs.py
+++ b/tests/common/quantization/mock_graphs.py
@@ -21,6 +21,7 @@
 from nncf.common.graph.layer_attributes import BaseLayerAttributes
 from nncf.common.graph.layer_attributes import ConvolutionLayerAttributes
 from nncf.common.graph.layer_attributes import Dtype
+from nncf.common.graph.operator_metatypes import OperatorMetatype
 from nncf.common.graph.operator_metatypes import UnknownMetatype
 from nncf.common.insertion_point_graph import InsertionPointGraph
 from nncf.common.insertion_point_graph import PostHookInsertionPoint
@@ -188,16 +189,26 @@ def get_mock_nncf_node_attrs(op_name=None, scope_str=None, metatype=None, type_=
 
 
 def _add_nodes_with_layer_attrs(
-    nx_graph: nx.DiGraph, node_keys: List[str], layer_attrs: Dict[str, BaseLayerAttributes]
+    nx_graph: nx.DiGraph,
+    node_keys: List[str],
+    layer_attrs: Dict[str, BaseLayerAttributes],
+    metatypes: Dict[str, OperatorMetatype] = None,
 ) -> nx.DiGraph:
     for node_key in node_keys:
-        nx_graph.add_node(node_key, **get_mock_nncf_node_attrs(op_name=node_key))
+        metatype = None
+        if metatypes is not None and node_key in metatypes:
+            metatype = metatypes[node_key]
+        nx_graph.add_node(node_key, **get_mock_nncf_node_attrs(op_name=node_key, metatype=metatype))
+
         if node_key in layer_attrs:
             nx_graph.nodes[node_key][NNCFNode.LAYER_ATTRIBUTES] = layer_attrs[node_key]
+
     return nx_graph
 
 
-def get_mock_model_graph_with_mergeable_pattern() -> NNCFGraph:
+def get_mock_model_graph_with_mergeable_pattern(
+    conv2d_metatype=None, batchnorm_metatype=None, relu_metatype=None
+) -> NNCFGraph:
     mock_nx_graph = nx.DiGraph()
 
     #   (A)
@@ -225,7 +236,12 @@ def get_mock_model_graph_with_mergeable_pattern() -> NNCFGraph:
             padding_values=[0, 0, 0, 0],
         )
     }
-    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs)
+    metatypes = {
+        "conv2d": conv2d_metatype,
+        "batch_norm": batchnorm_metatype,
+        "relu": relu_metatype,
+    }
+    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs, metatypes)
 
     mock_nx_graph.add_edges_from(
         [
@@ -238,7 +254,9 @@ def get_mock_model_graph_with_mergeable_pattern() -> NNCFGraph:
     return get_nncf_graph_from_mock_nx_graph(mock_nx_graph)
 
 
-def get_mock_model_graph_with_no_mergeable_pattern() -> NNCFGraph:
+def get_mock_model_graph_with_no_mergeable_pattern(
+    conv2d_metatype=None, batchnorm_metatype=None, relu_metatype=None
+) -> NNCFGraph:
     mock_nx_graph = nx.DiGraph()
 
     #   (A)
@@ -270,7 +288,12 @@ def get_mock_model_graph_with_no_mergeable_pattern() -> NNCFGraph:
             padding_values=[0, 0, 0, 0],
         )
     }
-    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs)
+    metatypes = {
+        "conv2d": conv2d_metatype,
+        "batch_norm": batchnorm_metatype,
+        "relu": relu_metatype,
+    }
+    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs, metatypes)
 
     mock_nx_graph.add_edges_from(
         [
@@ -285,7 +308,9 @@ def get_mock_model_graph_with_no_mergeable_pattern() -> NNCFGraph:
     return get_nncf_graph_from_mock_nx_graph(mock_nx_graph)
 
 
-def get_mock_model_graph_with_broken_output_edge_pattern() -> NNCFGraph:
+def get_mock_model_graph_with_broken_output_edge_pattern(
+    conv2d_metatype=None, batchnorm_metatype=None, relu_metatype=None
+) -> NNCFGraph:
     mock_nx_graph = nx.DiGraph()
 
     #   (A)
@@ -314,7 +339,12 @@ def get_mock_model_graph_with_broken_output_edge_pattern() -> NNCFGraph:
             padding_values=[0, 0, 0, 0],
         )
     }
-    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs)
+    metatypes = {
+        "conv2d": conv2d_metatype,
+        "batch_norm": batchnorm_metatype,
+        "relu": relu_metatype,
+    }
+    mock_nx_graph = _add_nodes_with_layer_attrs(mock_nx_graph, node_keys, layer_attrs, metatypes)
 
     mock_nx_graph.add_edges_from(
         [
diff --git a/tests/torch/data/reference_graphs/quantized/synthetic_model/MHA_single_input.dot b/tests/torch/data/reference_graphs/quantized/synthetic_model/MHA_single_input.dot
index 578b6e795d7..5f55464d859 100644
--- a/tests/torch/data/reference_graphs/quantized/synthetic_model/MHA_single_input.dot
+++ b/tests/torch/data/reference_graphs/quantized/synthetic_model/MHA_single_input.dot
@@ -2,8 +2,8 @@ strict digraph  {
 "0 /nncf_model_input_0" [id=0, type=nncf_model_input];
 "1 SymmetricQuantizer/symmetric_quantize_0" [id=1, type=symmetric_quantize];
 "2 MHA_single_input/MultiheadAttention[mha]/linear_0" [id=2, type=linear];
-"3 MHA_single_input/MultiheadAttention[mha]/unflatten_0" [id=3, type=unflatten];
-"4 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0" [id=4, type=symmetric_quantize];
+"3 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0" [id=3, type=symmetric_quantize];
+"4 MHA_single_input/MultiheadAttention[mha]/unflatten_0" [id=4, type=unflatten];
 "5 MHA_single_input/MultiheadAttention[mha]/unsqueeze_0" [id=5, type=unsqueeze];
 "6 MHA_single_input/MultiheadAttention[mha]/transpose_0" [id=6, type=transpose];
 "7 MHA_single_input/MultiheadAttention[mha]/squeeze_0" [id=7, type=squeeze];
@@ -36,9 +36,9 @@ strict digraph  {
 "34 /nncf_model_output_1" [id=34, type=nncf_model_output];
 "0 /nncf_model_input_0" -> "1 SymmetricQuantizer/symmetric_quantize_0";
 "1 SymmetricQuantizer/symmetric_quantize_0" -> "2 MHA_single_input/MultiheadAttention[mha]/linear_0";
-"2 MHA_single_input/MultiheadAttention[mha]/linear_0" -> "3 MHA_single_input/MultiheadAttention[mha]/unflatten_0";
-"3 MHA_single_input/MultiheadAttention[mha]/unflatten_0" -> "4 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0";
-"4 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0" -> "5 MHA_single_input/MultiheadAttention[mha]/unsqueeze_0";
+"2 MHA_single_input/MultiheadAttention[mha]/linear_0" -> "3 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0";
+"3 MHA_single_input/MultiheadAttention[mha]/SymmetricQuantizer/symmetric_quantize_0" -> "4 MHA_single_input/MultiheadAttention[mha]/unflatten_0";
+"4 MHA_single_input/MultiheadAttention[mha]/unflatten_0" -> "5 MHA_single_input/MultiheadAttention[mha]/unsqueeze_0";
 "5 MHA_single_input/MultiheadAttention[mha]/unsqueeze_0" -> "6 MHA_single_input/MultiheadAttention[mha]/transpose_0";
 "6 MHA_single_input/MultiheadAttention[mha]/transpose_0" -> "7 MHA_single_input/MultiheadAttention[mha]/squeeze_0";
 "7 MHA_single_input/MultiheadAttention[mha]/squeeze_0" -> "8 MHA_single_input/MultiheadAttention[mha]/contiguous_0";
diff --git a/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__multi_input_branch.dot b/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__multi_input_branch.dot
index 3b5e80a9758..765baeccf24 100644
--- a/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__multi_input_branch.dot
+++ b/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__multi_input_branch.dot
@@ -1,25 +1,25 @@
 strict digraph  {
 "0 /nncf_model_input_0" [id=0, type=nncf_model_input];
-"1 ShiftScaleParametrized/clone_0" [id=1, type=clone];
-"2 ShiftScaleParametrized/sub__0" [id=2, type=sub_];
-"3 ShiftScaleParametrized/div__0" [id=3, type=div_];
-"4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" [id=4, type=symmetric_quantize];
-"5 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" [id=5, type=symmetric_quantize];
-"6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" [id=6, type=conv2d];
-"7 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_1" [id=7, type=symmetric_quantize];
-"8 ShiftScaleParametrized/NNCFConv2d[conv]/SymmetricQuantizer/symmetric_quantize_0" [id=8, type=symmetric_quantize];
+"1 SymmetricQuantizer/symmetric_quantize_0" [id=1, type=symmetric_quantize];
+"2 ShiftScaleParametrized/clone_0" [id=2, type=clone];
+"3 ShiftScaleParametrized/sub__0" [id=3, type=sub_];
+"4 ShiftScaleParametrized/div__0" [id=4, type=div_];
+"5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" [id=5, type=symmetric_quantize];
+"6 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" [id=6, type=symmetric_quantize];
+"7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" [id=7, type=conv2d];
+"8 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_1" [id=8, type=symmetric_quantize];
 "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1" [id=9, type=conv2d];
 "10 /nncf_model_output_0" [id=10, type=nncf_model_output];
 "11 /nncf_model_output_1" [id=11, type=nncf_model_output];
-"0 /nncf_model_input_0" -> "1 ShiftScaleParametrized/clone_0";
-"0 /nncf_model_input_0" -> "8 ShiftScaleParametrized/NNCFConv2d[conv]/SymmetricQuantizer/symmetric_quantize_0";
-"1 ShiftScaleParametrized/clone_0" -> "2 ShiftScaleParametrized/sub__0";
-"2 ShiftScaleParametrized/sub__0" -> "3 ShiftScaleParametrized/div__0";
-"3 ShiftScaleParametrized/div__0" -> "4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0";
-"4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" -> "6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
-"5 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" -> "6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
-"6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" -> "10 /nncf_model_output_0";
-"7 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_1" -> "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1";
-"8 ShiftScaleParametrized/NNCFConv2d[conv]/SymmetricQuantizer/symmetric_quantize_0" -> "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1";
+"0 /nncf_model_input_0" -> "1 SymmetricQuantizer/symmetric_quantize_0";
+"1 SymmetricQuantizer/symmetric_quantize_0" -> "2 ShiftScaleParametrized/clone_0";
+"1 SymmetricQuantizer/symmetric_quantize_0" -> "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1";
+"2 ShiftScaleParametrized/clone_0" -> "3 ShiftScaleParametrized/sub__0";
+"3 ShiftScaleParametrized/sub__0" -> "4 ShiftScaleParametrized/div__0";
+"4 ShiftScaleParametrized/div__0" -> "5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0";
+"5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" -> "7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
+"6 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" -> "7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
+"7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" -> "10 /nncf_model_output_0";
+"8 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_1" -> "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1";
 "9 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_1" -> "11 /nncf_model_output_1";
 }
diff --git a/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__single_input_branch.dot b/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__single_input_branch.dot
index 9eab740c541..793bfa2f7da 100644
--- a/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__single_input_branch.dot
+++ b/tests/torch/data/reference_graphs/quantized/synthetic_model/ShiftScale__normalize__single_input_branch.dot
@@ -1,17 +1,19 @@
 strict digraph  {
 "0 /nncf_model_input_0" [id=0, type=nncf_model_input];
-"1 ShiftScaleParametrized/clone_0" [id=1, type=clone];
-"2 ShiftScaleParametrized/sub__0" [id=2, type=sub_];
-"3 ShiftScaleParametrized/div__0" [id=3, type=div_];
-"4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" [id=4, type=symmetric_quantize];
-"5 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" [id=5, type=symmetric_quantize];
-"6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" [id=6, type=conv2d];
-"7 /nncf_model_output_0" [id=7, type=nncf_model_output];
-"0 /nncf_model_input_0" -> "1 ShiftScaleParametrized/clone_0";
-"1 ShiftScaleParametrized/clone_0" -> "2 ShiftScaleParametrized/sub__0";
-"2 ShiftScaleParametrized/sub__0" -> "3 ShiftScaleParametrized/div__0";
-"3 ShiftScaleParametrized/div__0" -> "4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0";
-"4 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" -> "6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
-"5 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" -> "6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
-"6 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" -> "7 /nncf_model_output_0";
+"1 SymmetricQuantizer/symmetric_quantize_0" [id=1, type=symmetric_quantize];
+"2 ShiftScaleParametrized/clone_0" [id=2, type=clone];
+"3 ShiftScaleParametrized/sub__0" [id=3, type=sub_];
+"4 ShiftScaleParametrized/div__0" [id=4, type=div_];
+"5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" [id=5, type=symmetric_quantize];
+"6 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" [id=6, type=symmetric_quantize];
+"7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" [id=7, type=conv2d];
+"8 /nncf_model_output_0" [id=8, type=nncf_model_output];
+"0 /nncf_model_input_0" -> "1 SymmetricQuantizer/symmetric_quantize_0";
+"1 SymmetricQuantizer/symmetric_quantize_0" -> "2 ShiftScaleParametrized/clone_0";
+"2 ShiftScaleParametrized/clone_0" -> "3 ShiftScaleParametrized/sub__0";
+"3 ShiftScaleParametrized/sub__0" -> "4 ShiftScaleParametrized/div__0";
+"4 ShiftScaleParametrized/div__0" -> "5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0";
+"5 ShiftScaleParametrized/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[ShiftScaleParametrized/div__0|OUTPUT]/symmetric_quantize_0" -> "7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
+"6 ShiftScaleParametrized/NNCFConv2d[conv]/ModuleDict[pre_ops]/UpdateWeight[0]/SymmetricQuantizer[op]/symmetric_quantize_0" -> "7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0";
+"7 ShiftScaleParametrized/NNCFConv2d[conv]/conv2d_0" -> "8 /nncf_model_output_0";
 }
diff --git a/tests/torch/test_model_transformer.py b/tests/torch/test_model_transformer.py
index d4fe6ca2f72..3eabe1f7e99 100644
--- a/tests/torch/test_model_transformer.py
+++ b/tests/torch/test_model_transformer.py
@@ -12,6 +12,7 @@
 from collections import Counter
 from copy import deepcopy
 from dataclasses import dataclass
+from functools import partial
 from pathlib import Path
 from typing import List
 
@@ -21,6 +22,7 @@
 import torch.nn.functional as F
 from torch import nn
 
+import nncf.torch.graph.operator_metatypes as om
 from nncf.common.graph.definitions import MODEL_INPUT_OP_NAME
 from nncf.common.graph.definitions import MODEL_OUTPUT_OP_NAME
 from nncf.common.graph.patterns.manager import PatternsManager
@@ -367,9 +369,33 @@ def test_priority(self, target_type, trace_parameters, priority_type):
 
 
 MERGE_PATTERN_TEST_CASES = (
-    [get_mock_model_graph_with_mergeable_pattern, "basic_pattern"],
-    [get_mock_model_graph_with_no_mergeable_pattern, "no_pattern"],
-    [get_mock_model_graph_with_broken_output_edge_pattern, "broken_output_edges_pattern"],
+    [
+        partial(
+            get_mock_model_graph_with_mergeable_pattern,
+            conv2d_metatype=om.PTConv2dMetatype,
+            batchnorm_metatype=om.PTBatchNormMetatype,
+            relu_metatype=om.PTRELUMetatype,
+        ),
+        "basic_pattern",
+    ],
+    [
+        partial(
+            get_mock_model_graph_with_no_mergeable_pattern,
+            conv2d_metatype=om.PTConv2dMetatype,
+            batchnorm_metatype=om.PTBatchNormMetatype,
+            relu_metatype=om.PTRELUMetatype,
+        ),
+        "no_pattern",
+    ],
+    [
+        partial(
+            get_mock_model_graph_with_broken_output_edge_pattern,
+            conv2d_metatype=om.PTConv2dMetatype,
+            batchnorm_metatype=om.PTBatchNormMetatype,
+            relu_metatype=om.PTRELUMetatype,
+        ),
+        "broken_output_edges_pattern",
+    ],
 )