Fixes more issues in dynamic shape benchmarking (#81)

hatlib/arg_value.py

@@ -27,6 +27,8 @@ class ArgValue:
             else:
                 # no value provided, allocate the pointer
                 self.allocate()
+        elif type(self.value) in [int, float]:
+            self.value = self.arg_info.numpy_dtype.type(self.value)
         self.dim_values = None
 
     def allocate(self):
@@ -169,7 +171,7 @@ def generate_arg_values(arguments: List[ArgInfo], dim_names_to_values = {}) -> L
                             dim_names_to_values[d] = ArgValue(dim_args[d], shape[-1])
                         else:
                             v = dim_names_to_values[d].value
-                            shape.append(v if type(v) == int else v[0])
+                            shape.append(v if isinstance(v, np.integer) or type(v) == int else v[0])
 
             # materialize an array input using the generated shape
             runtime_array_inputs = np.random.random(tuple(shape)).astype(arg.numpy_dtype)

hatlib/hat.py

@@ -87,7 +87,7 @@ def generate_arg_sets_for_func(
             shape_idx += 1
 
     else:
-        numerical_shapes = [p.shape if p.shape else [int(p.size)] for p in func.arguments]
+        numerical_shapes = [p.shape if p.shape else ([int(p.size)] if p.size else [1]) for p in func.arguments]
 
     shapes_to_sizes = [reduce(lambda x, y: x * y, shape, 1) for shape in numerical_shapes]
     set_size = reduce(lambda x, y: x + y, map(lambda size, p: size * p.element_num_bytes, shapes_to_sizes, parameters))