diff --git a/verif/generator/tosa_arg_gen.py b/verif/generator/tosa_arg_gen.py
index 1f54851..454013a 100644
--- a/verif/generator/tosa_arg_gen.py
+++ b/verif/generator/tosa_arg_gen.py
@@ -767,8 +767,10 @@
         return TosaTensorValuesGen.TVGInfo(tens_ser_list, tens_data)
 
     @staticmethod
-    def tvgNegate(testGen, op, dtypeList, shapeList, testArgs, error_name=None):
+    def tvgNegate(testGen, opName, dtypeList, shapeList, argsDict, error_name=None):
         if dtypeList[0] == DType.INT32 and error_name is None:
+            # Integer test
+            op = testGen.TOSA_OP_LIST[opName]
             pCount, cCount = op["operands"]
             assert (
                 pCount == 1 and cCount == 0
@@ -780,14 +782,15 @@
             arr = np.int32(
                 testGen.rng.integers(low=min_val, high=(max_val + 1), size=shapeList[0])
             )
-            placeholders = []
-            placeholders.append(
+            tens_ser_list = []
+            tens_ser_list.append(
                 testGen.ser.addPlaceholder(shapeList[0], dtypeList[0], arr)
             )
-            return placeholders
+            return TosaTensorValuesGen.TVGInfo(tens_ser_list, None)
         else:
-            return TosaTensorValuesGen.tvgDefault(
-                testGen, op, dtypeList, shapeList, testArgs, error_name
+            # ERROR_IF or floating point test
+            return TosaTensorValuesGen.tvgLazyGenDefault(
+                testGen, opName, dtypeList, shapeList, argsDict, error_name
             )
 
     # Set the data range to half the largest value
diff --git a/verif/generator/tosa_error_if.py b/verif/generator/tosa_error_if.py
index ed1a941..86be347 100644
--- a/verif/generator/tosa_error_if.py
+++ b/verif/generator/tosa_error_if.py
@@ -343,6 +343,9 @@
         Returns:
             True if the result matches the expected result; otherwise False
         """
+        if validator_fcns is None:
+            # Nothing to do
+            return True
         overall_result = True
         for val_fcn in validator_fcns:
             val_result = val_fcn(True, **kwargs)
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index d1fe11d..35cd78f 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -352,28 +352,26 @@
             self.resultTensor = resultTensor
             self.complianceDict = complianceDict
 
-    def build_unary(self, op, a, validator_fcns=None, error_name=None, qinfo=None):
-        result_tens = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
+    def build_unary(
+        self, op, inputs, args_dict, validator_fcns=None, error_name=None, qinfo=None
+    ):
+        assert len(inputs) == 1
+        a = inputs[0]
+        result_tensor = OutputShaper.unaryOp(self.ser, self.rng, a, error_name)
 
-        # build_placeholder returns an int, ABS/other ops does not
-        if isinstance(op, int):
-            self.ser.addOperator(op, a.name, result_tens.name, None)
-            return result_tens
-        elif op["op"] == Op.IDENTITY:
-            self.ser.addOperator(op["op"], a.name, result_tens.name, None)
-            return result_tens
+        assert not isinstance(op, int)
 
         # Ensure new output type has correct qinfo
         if error_name == ErrorIf.WrongOutputType:
-            if result_tens.dtype not in [DType.INT8, DType.UINT8]:
+            if result_tensor.dtype not in [DType.INT8, DType.UINT8]:
                 qinfo = [
                     TosaQuantGen.getZeroPoint(self, a.dtype),
-                    TosaQuantGen.getZeroPoint(self, result_tens.dtype),
+                    TosaQuantGen.getZeroPoint(self, result_tensor.dtype),
                 ]
 
         # Invalidate Input/Output list for error if checks.
         input_list = [a.name]
-        output_list = [result_tens.name]
+        output_list = [result_tensor.name]
         pCount, cCount = op["operands"]
         num_operands = pCount + cCount
         input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList(
@@ -386,9 +384,9 @@
             error_name,
             op=op,
             input_dtype=a.dtype,
-            output_dtype=result_tens.dtype,
+            output_dtype=result_tensor.dtype,
             qinfo=qinfo,
-            result_tensors=[result_tens],
+            result_tensors=[result_tensor],
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
@@ -401,7 +399,15 @@
             attr.NegateAttribute(qinfo[0], qinfo[1])
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
-        return result_tens
+
+        if op["op"] in (Op.EXP, Op.LOG):
+            # TODO - add compliance support LOG and EXP
+            compliance = None
+        else:
+            compliance = self.tensorComplianceMetaData(
+                op, a.dtype, args_dict, result_tensor, error_name
+            )
+        return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_binary_broadcast(
         self, op, inputs, args_dict, validator_fcns, error_name=None, qinfo=None
@@ -3622,8 +3628,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FI32,
             "error_if_validators": (
@@ -3632,6 +3638,9 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
         },
         "bitwise_not": {
             "op": Op.BITWISE_NOT,
@@ -3639,8 +3648,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_INT,
             "error_if_validators": (
@@ -3656,8 +3665,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3666,6 +3675,10 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 0.5},
         },
         "clz": {
             "op": Op.CLZ,
@@ -3673,8 +3686,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": [DType.INT32],
             "error_if_validators": (
@@ -3690,8 +3703,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3707,8 +3720,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3717,6 +3730,10 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 0.5},
         },
         "log": {
             "op": Op.LOG,
@@ -3724,8 +3741,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3741,8 +3758,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_BOOL,
             "error_if_validators": (
@@ -3759,7 +3776,7 @@
                 build_unary,
                 TosaTensorGen.tgBasic,
                 TosaTensorValuesGen.tvgNegate,
-                None,
+                TosaArgGen.agNone,
             ),
             "qgen": TosaQuantGen.qgUnary,
             "types": TYPE_INT_FP,
@@ -3771,6 +3788,9 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
         },
         "reciprocal": {
             "op": Op.RECIPROCAL,
@@ -3778,8 +3798,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3788,6 +3808,10 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 1.0},
         },
         "rsqrt": {
             "op": Op.RSQRT,
@@ -3795,8 +3819,8 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FP,
             "error_if_validators": (
@@ -3805,6 +3829,10 @@
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
+            "compliance": {"ulp": 2},
         },
         # Elementwise Ternary operators
         "select": {
@@ -4220,10 +4248,13 @@
             "build_fcn": (
                 build_unary,
                 TosaTensorGen.tgBasic,
-                TosaTensorValuesGen.tvgDefault,
-                None,
+                TosaTensorValuesGen.tvgLazyGenDefault,
+                TosaArgGen.agNone,
             ),
             "types": TYPE_FIB,
+            "data_gen": {
+                "fp": (gtu.DataGenType.PSEUDO_RANDOM,),
+            },
         },
         # Scatter/Gather
         "gather": {