diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index 17cbd8f..54b624e 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -56,11 +56,9 @@
         self.random_fp_high = max(args.tensor_fp_value_range)
         # JSON schema validation
         self.descSchemaValidator = TestDescSchemaValidator()
-        # Data generator library when not generating the data later
-        if not args.lazy_data_gen:
-            self.dgl = GenerateLibrary(args.generate_lib_path)
-        else:
-            self.dgl = None
+        # Data generator library is sometimes needed for compliance set up
+        # even if we are generating the data later (lazy_data_generation)
+        self.dgl = GenerateLibrary(args.generate_lib_path)
 
     def createSerializer(self, opName, testPath):
         self.testPath = os.path.join(opName, testPath)
@@ -108,11 +106,6 @@
                         fd.write(f'const char* json_tdg_config_{path.stem} = R"(')
                         json.dump(metaData["data_gen"], fd)
                         fd.write(')";\n\n')
-                else:
-                    # Generate the data
-                    self.dgl.set_config(desc)
-                    self.dgl.write_numpy_files(path)
-
             if "compliance" in metaData:
                 # Output datagen meta data as CPP data
                 path_md = path / f"{testName}_meta_compliance.cpp"
@@ -293,9 +286,15 @@
             low=self.args.tensor_shape_range[0], high=self.args.tensor_shape_range[1]
         )
 
-    def tensorComplianceMetaData(self, op, argsDict, outputTensor, errorName):
-        if errorName or not gtu.dtypeIsSupportedByCompliance(outputTensor.dtype):
-            # No compliance for error tests or other data types currently
+    def tensorComplianceMetaData(
+        self, op, inputType, argsDict, outputTensor, errorName
+    ):
+        if (
+            errorName
+            or not gtu.dtypeIsSupportedByCompliance(outputTensor.dtype)
+            or not gtu.dtypeIsSupportedByCompliance(inputType)
+        ):
+            # No compliance for error tests or unsupported types currently
             return None
 
         # Create compliance meta data for expected output tensor
@@ -308,7 +307,9 @@
             mode = gtu.ComplianceMode.DOT_PRODUCT
             compliance_tens["dot_product_info"] = {
                 "s": argsDict["s"],
-                "ks": argsDict["ks"],
+                "ks": int(argsDict["ksb"])
+                if "ksb" in argsDict
+                else int(argsDict["ks"]),
             }
         elif argsDict["dg_type"] == gtu.DataGenType.OP_SPECIAL:
             mode = gtu.ComplianceMode.FP_SPECIAL
@@ -741,31 +742,30 @@
             error_name,
             qinfo,
         )
-        if gtu.dtypeIsSupportedByCompliance(inputs[0].dtype):
-            compliance = self.tensorComplianceMetaData(
-                op, args_dict, result_tensor, error_name
-            )
-        else:
-            compliance = None
+        compliance = self.tensorComplianceMetaData(
+            op, inputs[0].dtype, args_dict, result_tensor, error_name
+        )
 
         return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_conv2d(
         self,
         op,
-        ifm,
-        filter,
-        bias,
-        accum_dtype,
-        strides,
-        padding,
-        dilations,
+        inputs,
+        args_dict,
         validator_fcns=None,
         error_name=None,
         qinfo=None,
     ):
+        assert len(inputs) == 3
+        ifm, filter, bias = inputs
+        accum_dtype = args_dict["acc_type"]
+        strides = args_dict["stride"]
+        padding = args_dict["pad"]
+        dilations = args_dict["dilation"]
+
         assert len(padding) == 4
-        result_tens = OutputShaper.conv2dOp(
+        result_tensor = OutputShaper.conv2dOp(
             self.ser,
             self.rng,
             ifm,
@@ -784,12 +784,12 @@
         ):
             qinfo = [
                 TosaQuantGen.getZeroPoint(self, ifm.dtype),
-                TosaQuantGen.getZeroPoint(self, result_tens.dtype),
+                TosaQuantGen.getZeroPoint(self, result_tensor.dtype),
             ]
 
         # Invalidate Input/Output list for error_if checks.
         input_list = [ifm.name, filter.name, bias.name]
-        output_list = [result_tens.name]
+        output_list = [result_tensor.name]
         num_operands = sum(op["operands"])
         input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList(
             self, error_name, input_list, output_list
@@ -802,7 +802,7 @@
             op=op,
             input_dtype=ifm.dtype,
             weight_dtype=filter.dtype,
-            output_dtype=result_tens.dtype,
+            output_dtype=result_tensor.dtype,
             qinfo=qinfo,
             input_list=input_list,
             num_operands=num_operands,
@@ -812,7 +812,7 @@
             dilation=dilations,
             input_shape=ifm.shape,
             weight_shape=filter.shape,
-            output_shape=result_tens.shape,
+            output_shape=result_tensor.shape,
         ):
             return None
 
@@ -820,22 +820,29 @@
         attr.ConvAttribute(padding, strides, dilations, qinfo[0], qinfo[1])
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
-        return result_tens
+
+        compliance = self.tensorComplianceMetaData(
+            op, ifm.dtype, args_dict, result_tensor, error_name
+        )
+
+        return TosaTestGen.BuildInfo(result_tensor, compliance)
 
     def build_conv3d(
         self,
         op,
-        ifm,
-        filter,
-        bias,
-        accum_dtype,
-        strides,
-        padding,
-        dilations,
+        inputs,
+        args_dict,
         validator_fcns=None,
         error_name=None,
         qinfo=None,
     ):
+        assert len(inputs) == 3
+        ifm, filter, bias = inputs
+        accum_dtype = args_dict["acc_type"]
+        strides = args_dict["stride"]
+        padding = args_dict["pad"]
+        dilations = args_dict["dilation"]
+
         assert len(padding) == 6
         result_tens = OutputShaper.conv3dOp(
             self.ser,
@@ -960,17 +967,19 @@
     def build_depthwise_conv2d(
         self,
         op,
-        ifm,
-        filter,
-        bias,
-        accum_dtype,
-        strides,
-        padding,
-        dilations,
+        inputs,
+        args_dict,
         validator_fcns=None,
         error_name=None,
         qinfo=None,
     ):
+        assert len(inputs) == 3
+        ifm, filter, bias = inputs
+        accum_dtype = args_dict["acc_type"]
+        strides = args_dict["stride"]
+        padding = args_dict["pad"]
+        dilations = args_dict["dilation"]
+
         result_tens = OutputShaper.depthwiseConv2dOp(
             self.ser,
             self.rng,
@@ -1121,12 +1130,9 @@
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
 
-        if gtu.dtypeIsSupportedByCompliance(a.dtype):
-            compliance = self.tensorComplianceMetaData(
-                op, args_dict, result_tensor, error_name
-            )
-        else:
-            compliance = None
+        compliance = self.tensorComplianceMetaData(
+            op, a.dtype, args_dict, result_tensor, error_name
+        )
 
         return TosaTestGen.BuildInfo(result_tensor, compliance)
 
@@ -1431,12 +1437,9 @@
 
         self.ser.addOperator(op["op"], input_list, output_list, attr)
 
-        if gtu.dtypeIsSupportedByCompliance(a.dtype):
-            compliance = self.tensorComplianceMetaData(
-                op, args_dict, result_tensor, error_name
-            )
-        else:
-            compliance = None
+        compliance = self.tensorComplianceMetaData(
+            op, a.dtype, args_dict, result_tensor, error_name
+        )
 
         return TosaTestGen.BuildInfo(result_tensor, compliance)
 
@@ -2911,7 +2914,7 @@
             "build_fcn": (
                 build_conv2d,
                 TosaTensorGen.tgConv2D,
-                TosaTensorValuesGen.tvgDefault,
+                TosaTensorValuesGen.tvgLazyGenDefault,
                 TosaArgGen.agConv,
             ),
             "qgen": TosaQuantGen.qgConv,
@@ -2931,6 +2934,9 @@
                 TosaErrorValidator.evConvOutputShapeMismatch,
                 TosaErrorValidator.evConvOutputShapeNonInteger,
             ),
+            "data_gen": {
+                "fp": (gtu.DataGenType.DOT_PRODUCT,),
+            },
             "template": True,
         },
         # Templated operator.  Filled in by createDynamicOpLists
@@ -2941,7 +2947,7 @@
             "build_fcn": (
                 build_conv3d,
                 TosaTensorGen.tgConv3D,
-                TosaTensorValuesGen.tvgDefault,
+                TosaTensorValuesGen.tvgLazyGenDefault,
                 TosaArgGen.agConv,
             ),
             "qgen": TosaQuantGen.qgConv,
@@ -2972,7 +2978,7 @@
             "build_fcn": (
                 build_depthwise_conv2d,
                 TosaTensorGen.tgDepthwiseConv2D,
-                TosaTensorValuesGen.tvgDefault,
+                TosaTensorValuesGen.tvgLazyGenDefault,
                 TosaArgGen.agConv,
             ),
             "qgen": TosaQuantGen.qgConv,