fix(pi0, pi05): stabilize torch.compile and expand test coverage (#3610)

* chore(gr00t): sync with #3606 for fixing gr00t config crash * fix(pi0&pi05): fix graph break caused by deepcopy of past_key_values in sample_actions * fix(pi0&pi05): fix frequent recompile caused by compute_layer_complete * feat(test): add compile test and benchamrk for pi0 and pi05 * feat(test): add comprehensive testing for pi0 and pi05. Including processor, forward, sample action, etc.
2026-05-28 06:59:44 +00:00 · 2026-05-22 16:29:34 +08:00
parent c0a2e9814d
commit b74a551d38
18 changed files with 2463 additions and 699 deletions
@@ -0,0 +1,101 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import pytest
+import torch
+
+pytest.importorskip("transformers")
+
+from lerobot.policies.pi05 import PI05Config  # noqa: E402
+from lerobot.policies.pi05.modeling_pi05 import PI05Pytorch  # noqa: E402
+from tests.policies.pi0_pi05.utils.torch_compile import (  # noqa: E402
+    assert_cache_stability,
+    assert_compiled_output_matches_eager,
+    assert_explain_has_no_graph_breaks,
+    benchmark_runtime,
+    make_compile_config,
+    reset_compile_state,
+)
+from tests.utils import require_cuda  # noqa: E402
+
+pytestmark = pytest.mark.skipif(
+    os.environ.get("CI") == "true" or os.environ.get("GITHUB_ACTIONS") == "true",
+    reason="torch.compile benchmark is too slow for CI; run manually on GPU nodes",
+)
+
+
+def _make_model(*, compile_model):
+    return PI05Pytorch(make_compile_config(PI05Config, compile_model=compile_model)).cuda().eval()
+
+
+def _make_dummy_inputs(config):
+    device = torch.device("cuda")
+    common = {
+        "images": [torch.randn(1, 3, *config.image_resolution, device=device)],
+        "img_masks": [torch.ones(1, dtype=torch.bool, device=device)],
+        "tokens": torch.randint(0, 1024, (1, 5), dtype=torch.long, device=device),
+        "masks": torch.ones(1, 5, dtype=torch.bool, device=device),
+    }
+    forward_kwargs = {
+        **common,
+        "actions": torch.randn(1, config.chunk_size, config.max_action_dim, device=device),
+        "noise": torch.randn(1, config.chunk_size, config.max_action_dim, device=device),
+        "time": torch.rand(1, device=device),
+    }
+    sample_kwargs = {
+        **common,
+        "noise": torch.randn(1, config.chunk_size, config.max_action_dim, device=device),
+        "num_steps": config.num_inference_steps,
+    }
+    return forward_kwargs, sample_kwargs
+
+
+@require_cuda
+def test_pi05_torch_compile_forward_and_sample_actions():
+    if not hasattr(torch, "compile"):
+        pytest.skip("torch.compile is not available")
+    if not torch._dynamo.is_dynamo_supported():
+        pytest.skip("torch._dynamo is not supported on this platform")
+
+    torch.manual_seed(0)
+    eager_model = _make_model(compile_model=False)
+    torch.manual_seed(0)
+    compiled_model = _make_model(compile_model=True)
+    forward_kwargs, sample_kwargs = _make_dummy_inputs(compiled_model.config)
+
+    try:
+        assert_compiled_output_matches_eager(eager_model, compiled_model, forward_kwargs, sample_kwargs)
+
+        assert_explain_has_no_graph_breaks(eager_model.forward, forward_kwargs, "pi05.forward")
+        assert_explain_has_no_graph_breaks(eager_model.sample_actions, sample_kwargs, "pi05.sample_actions")
+
+        assert_cache_stability(compiled_model.forward, forward_kwargs, "pi05.forward")
+        assert_cache_stability(compiled_model.sample_actions, sample_kwargs, "pi05.sample_actions")
+
+        benchmark_runtime(eager_model.forward, compiled_model.forward, forward_kwargs, "pi05.forward")
+        benchmark_runtime(
+            eager_model.sample_actions,
+            compiled_model.sample_actions,
+            sample_kwargs,
+            "pi05.sample_actions",
+        )
+    finally:
+        reset_compile_state()
+        del eager_model
+        del compiled_model
+        torch.cuda.empty_cache()