diff --git a/reference_model/src/ops/tensor_ops.cc b/reference_model/src/ops/tensor_ops.cc
index edc1793..f38f486 100644
--- a/reference_model/src/ops/tensor_ops.cc
+++ b/reference_model/src/ops/tensor_ops.cc
@@ -1958,12 +1958,6 @@
         return 1;
     }
 
-    if (attribute->output_shape().size() != 4)
-    {
-        printNodeValidationError("OpTransposeConv2d: illegal size for attribute output_shape");
-        return 1;
-    }
-
     for (int32_t i : attribute->stride())
     {
         if (i < 1)
@@ -1973,15 +1967,6 @@
         }
     }
 
-    for (int d = 0; d < 4; d++)
-    {
-        if (attribute->output_shape()[d] != this->output->getShape()[d])
-        {
-            printNodeValidationError("OpTransposeConv2d: illegal size for attribute output_shape");
-            return 1;
-        }
-    }
-
     int32_t IH = input->getShape()[1];
     int32_t IW = input->getShape()[2];
     int32_t OH = output->getShape()[1];
diff --git a/thirdparty/serialization_lib b/thirdparty/serialization_lib
index 57d7818..50256e1 160000
--- a/thirdparty/serialization_lib
+++ b/thirdparty/serialization_lib
@@ -1 +1 @@
-Subproject commit 57d781883142db8a45fe98ac1a1dfacc49cba78a
+Subproject commit 50256e168c3e759f03445bb872d0a43da1a6ba30
diff --git a/verif/generator/tosa_error_if.py b/verif/generator/tosa_error_if.py
index 53a3199..9fd13d2 100644
--- a/verif/generator/tosa_error_if.py
+++ b/verif/generator/tosa_error_if.py
@@ -2788,7 +2788,6 @@
 
         if opName.startswith("transpose_conv2d"):
             # transpose_conv2d
-            output_shape = args_dict["out_shape"]
             filter_shape = inputShapes[1]
             kernel_shape = filter_shape[1:-1]
 
@@ -2810,10 +2809,7 @@
                 padding[2],
                 padding[3],
             )
-            if output_shape[1] == h and output_shape[2] == w:
-                return False
-            # output shape does not match the expected shape
-            return True
+            return h < 1 or w < 1
 
         if "conv2d" in opName or "conv3d" in opName:
             # conv2d, conv3d, depthwise_conv2d
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index b85dd03..88dd17a 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -264,9 +264,9 @@
             mode = gtu.ComplianceMode.DOT_PRODUCT
             compliance_tens["dot_product_info"] = {
                 "s": argsDict["s"],
-                "ks": int(argsDict["ksb"])
-                if "ksb" in argsDict
-                else int(argsDict["ks"]),
+                "ks": (
+                    int(argsDict["ksb"]) if "ksb" in argsDict else int(argsDict["ks"])
+                ),
             }
         elif argsDict["dg_type"] == gtu.DataGenType.FP_SPECIAL:
             mode = gtu.ComplianceMode.FP_SPECIAL
@@ -1028,11 +1028,10 @@
         accum_dtype = args_dict["acc_type"]
         strides = args_dict["stride"]
         out_pad = args_dict["pad"]
-        output_shape = args_dict["out_shape"]
 
         assert len(out_pad) == 4
         result_tensor = OutputShaper.transposeConv2DOp(
-            self.ser, rng, ifm, output_shape, accum_dtype, error_name
+            self.ser, rng, ifm, filter, accum_dtype, strides, out_pad, error_name
         )
 
         # Ensure new output type has correct qinfo
@@ -1081,7 +1080,7 @@
 
         attr = ts.TosaSerializerAttribute()
         attr.TransposeConvAttribute(
-            out_pad, strides, output_shape, qinfo[0], qinfo[1], local_bound, accum_dtype
+            out_pad, strides, qinfo[0], qinfo[1], local_bound, accum_dtype
         )
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
@@ -5942,14 +5941,23 @@
         return ser.addOutput(val.shape, out_dtype)
 
     @staticmethod
-    def transposeConv2DOp(ser, rng, ifm, output_shape, accum_dtype, error_name=None):
+    def transposeConv2DOp(
+        ser, rng, ifm, filter, accum_dtype, strides, padding, error_name=None
+    ):
+
+        h = (ifm.shape[1] - 1) * strides[0] + padding[0] + padding[1] + filter.shape[1]
+
+        w = (ifm.shape[2] - 1) * strides[1] + padding[2] + padding[3] + filter.shape[2]
+
         if error_name == ErrorIf.ConvOutputShapeMismatch:
             choices = [1, 2, 3]
             change = rng.choice(choices)
             if change in [1, 3]:
-                output_shape[1] = output_shape[1] + rng.choice(choices)
+                h = h + rng.choice(choices)
             if change in [2, 3]:
-                output_shape[2] = output_shape[2] + rng.choice(choices)
+                w = w + rng.choice(choices)
+
+        ofm_shape = [ifm.shape[0], h, w, filter.shape[0]]
 
         if error_name == ErrorIf.WrongInputType:
             # Pick some potentially correct output dtype if input type is incorrect
@@ -5965,7 +5973,7 @@
             wrong_dtypes = list(gtu.usableDTypes(excludes=excludes))
             out_dtype = rng.choice(wrong_dtypes)
 
-        return ser.addOutput(output_shape, out_dtype)
+        return ser.addOutput(ofm_shape, out_dtype)
 
     @staticmethod
     def fft2dOp(serializer, rng, ifm1, ifm2, error_name=None):