add test for group_offloading with training.

tests/models/test_modeling_common.py

@@ -1581,6 +1581,30 @@ class ModelTesterMixin:
         self.assertTrue(torch.allclose(output_without_group_offloading, output_with_group_offloading3, atol=1e-5))
         self.assertTrue(torch.allclose(output_without_group_offloading, output_with_group_offloading4, atol=1e-5))
 
+    @parameterized.expand([False, True])
+    @require_torch_accelerator
+    def test_group_offloading_with_training(self, use_stream):
+        init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
+        model = self.model_class(**init_dict)
+        if not getattr(model, "_supports_group_offloading", True):
+            return
+
+        model.enable_group_offload(
+            torch_device, offload_type="block_level", num_blocks_per_group=1, use_stream=use_stream
+        )
+        model.train()
+
+        output = model(**inputs_dict)
+
+        if isinstance(output, dict):
+            output = output.to_tuple()[0]
+
+        input_tensor = inputs_dict[self.main_input_name]
+        noise = torch.randn((input_tensor.shape[0],) + self.output_shape).to(torch_device)
+        loss = torch.nn.functional.mse_loss(output, noise)
+
+        loss.backward()
+
     def test_auto_model(self, expected_max_diff=5e-5):
         if self.forward_requires_fresh_args:
             model = self.model_class(**self.init_dict)