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.
2026-05-26 05:59:52 +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 +1,155 @@
+#!/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.
+
+"""Compare the PI0.5 processor pipeline against the vendored OpenPI reference processors."""
+
+import os
+
+import pytest
+import torch
+
+pytest.importorskip("transformers")
+
+from lerobot.configs import FeatureType, PolicyFeature  # noqa: E402
+from lerobot.policies.pi05 import PI05Policy  # noqa: E402
+from lerobot.policies.pi05.configuration_pi05 import PI05Config  # noqa: E402
+from lerobot.policies.pi05.processor_pi05 import make_pi05_pre_post_processors  # noqa: E402
+from lerobot.utils.constants import ACTION, OBS_STATE  # noqa: E402
+from tests.policies.pi0_pi05.utils.openpi_parity import (  # noqa: E402
+    IMAGE_KEYS,
+    assert_processor_inputs_match_lerobot,
+    clone_batch,
+    make_openpi_observation_from_raw,
+    openpi_model_actions_from_raw,
+)
+
+pytestmark = pytest.mark.skipif(
+    os.environ.get("CI") == "true" or os.environ.get("GITHUB_ACTIONS") == "true",
+    reason="OpenPI processor parity uses the PaliGemma tokenizer; run manually outside CI.",
+)
+
+DUMMY_ACTION_DIM = 32
+DUMMY_STATE_DIM = 32
+DUMMY_ACTION_HORIZON = 50
+DUMMY_MAX_TOKEN_LEN = 200
+DEVICE = torch.device("cpu")
+
+DUMMY_DATASET_STATS = {
+    OBS_STATE: {
+        "mean": torch.zeros(DUMMY_STATE_DIM),
+        "std": torch.ones(DUMMY_STATE_DIM),
+        "q01": torch.zeros(DUMMY_STATE_DIM),
+        "q99": torch.ones(DUMMY_STATE_DIM),
+    },
+    ACTION: {
+        "mean": torch.zeros(DUMMY_ACTION_DIM),
+        "std": torch.ones(DUMMY_ACTION_DIM),
+        "q01": torch.zeros(DUMMY_ACTION_DIM),
+        "q99": torch.ones(DUMMY_ACTION_DIM),
+    },
+    "images": {
+        key: {
+            "mean": torch.zeros(3, 224, 224),
+            "std": torch.ones(3, 224, 224),
+            "q01": torch.zeros(3, 224, 224),
+            "q99": torch.ones(3, 224, 224),
+        }
+        for key in IMAGE_KEYS
+    },
+}
+
+
+class PI05PolicyInputAdapter(torch.nn.Module):
+    """Minimal adapter exposing PI0.5 policy image preparation without loading model weights."""
+
+    _preprocess_images = PI05Policy._preprocess_images
+
+    def __init__(self, config: PI05Config) -> None:
+        super().__init__()
+        self.config = config
+        self._device_anchor = torch.nn.Parameter(torch.empty((), device=config.device), requires_grad=False)
+
+
+def create_pi05_config() -> PI05Config:
+    config = PI05Config(device=str(DEVICE))
+    config.max_state_dim = DUMMY_STATE_DIM
+    config.max_action_dim = DUMMY_ACTION_DIM
+    config.chunk_size = DUMMY_ACTION_HORIZON
+    config.n_action_steps = DUMMY_ACTION_HORIZON
+    config.tokenizer_max_length = DUMMY_MAX_TOKEN_LEN
+    config.input_features = {
+        OBS_STATE: PolicyFeature(type=FeatureType.STATE, shape=(DUMMY_STATE_DIM,)),
+        **{
+            f"observation.images.{key}": PolicyFeature(type=FeatureType.VISUAL, shape=(3, 224, 224))
+            for key in IMAGE_KEYS
+        },
+    }
+    config.output_features = {
+        ACTION: PolicyFeature(type=FeatureType.ACTION, shape=(DUMMY_ACTION_DIM,)),
+    }
+    return config
+
+
+def create_dummy_data() -> dict:
+    batch_size = 2
+    prompt = "Pick up the red block and place it in the bin"
+    return {
+        OBS_STATE: torch.randn(batch_size, DUMMY_STATE_DIM, dtype=torch.float32, device=DEVICE),
+        ACTION: torch.randn(
+            batch_size, DUMMY_ACTION_HORIZON, DUMMY_ACTION_DIM, dtype=torch.float32, device=DEVICE
+        ),
+        **{
+            f"observation.images.{key}": torch.rand(
+                batch_size, 3, 224, 224, dtype=torch.float32, device=DEVICE
+            )
+            for key in IMAGE_KEYS
+        },
+        "task": [prompt for _ in range(batch_size)],
+    }
+
+
+def test_pi05_processor_inputs_match_openpi_reference():
+    torch.manual_seed(0)
+    config = create_pi05_config()
+    preprocessor, _ = make_pi05_pre_post_processors(config=config, dataset_stats=DUMMY_DATASET_STATS)
+
+    raw_batch = create_dummy_data()
+    lerobot_batch = preprocessor(clone_batch(raw_batch))
+    openpi_observation = make_openpi_observation_from_raw(
+        raw_batch,
+        action_dim=DUMMY_ACTION_DIM,
+        max_token_len=DUMMY_MAX_TOKEN_LEN,
+        dataset_stats=DUMMY_DATASET_STATS,
+        pi05=True,
+    )
+
+    assert_processor_inputs_match_lerobot(
+        PI05PolicyInputAdapter(config),
+        lerobot_batch,
+        openpi_observation,
+        compare_state=False,
+    )
+    torch.testing.assert_close(
+        lerobot_batch[ACTION],
+        openpi_model_actions_from_raw(
+            raw_batch,
+            action_dim=DUMMY_ACTION_DIM,
+            dataset_stats=DUMMY_DATASET_STATS,
+            pi05=True,
+        ),
+        rtol=0,
+        atol=0,
+    )