Generate name for each member of list arg

pytorch_pfn_extras/onnx/export_testcase.py

@@ -279,10 +279,23 @@ def export_testcase(
     os.makedirs(out_dir, exist_ok=True)
     if isinstance(args, torch.Tensor):
         args = args,
-    input_names = kwargs.pop(
-        'input_names',
-        ['input_{}'.format(i) for i in range(len(args))])
-    assert len(input_names) == len(args)
+
+    # We unroll list args and generate names for each tensor.
+    gen_input_names = []
+    unrolled_args = []
+
+    def append_input_name(prefix: str, arg: Any) -> None:
+        if isinstance(arg, list):
+            for i, a in enumerate(arg):
+                append_input_name(prefix + f"_{i}", a)
+        else:
+            gen_input_names.append(prefix)
+            unrolled_args.append(arg)
+    for i, arg in enumerate(args):
+        append_input_name(f"input_{i}", arg)
+
+    input_names = kwargs.pop('input_names', gen_input_names)
+    assert len(input_names) == len(unrolled_args)
     assert not isinstance(args, torch.Tensor)
 
     onnx_graph, outs = _export(
@@ -302,7 +315,7 @@ def export_testcase(
         if used_input.name not in initializer_names:
             used_input_index_list.append(input_names.index(used_input.name))
     input_names = [input_names[i] for i in used_input_index_list]
-    args = [args[i] for i in used_input_index_list]
+    unrolled_args = [unrolled_args[i] for i in used_input_index_list]
 
     output_path = os.path.join(out_dir, 'model.onnx')
     is_on_memory = True
@@ -341,7 +354,7 @@ def write_to_pb(f: str, tensor: torch.Tensor, name: Optional[str] = None) -> Non
     os.makedirs(data_set_path, exist_ok=True)
     for pb_name in glob.glob(os.path.join(data_set_path, "*.pb")):
         os.remove(pb_name)
-    for i, (arg, name) in enumerate(zip(args, input_names)):
+    for i, (arg, name) in enumerate(zip(unrolled_args, input_names)):
         f = os.path.join(data_set_path, 'input_{}.pb'.format(i))
         write_to_pb(f, arg, name)