fix(processor): keep missing local state resolution local (#3715)

Co-authored-by: root <kinsonnee@gmail.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
This commit is contained in:
WOLIKIMCHENG
2026-07-27 21:53:31 +08:00
committed by GitHub
parent bbeacfe57d
commit acd42b4d85
2 changed files with 162 additions and 5 deletions
@@ -26,8 +26,17 @@ import tempfile
from pathlib import Path
import pytest
import torch
from safetensors.torch import save_file
from lerobot.processor.pipeline import DataProcessorPipeline, ProcessorMigrationError
from lerobot.configs import PipelineFeatureType, PolicyFeature
from lerobot.processor.pipeline import (
DataProcessorPipeline,
ProcessorMigrationError,
ProcessorStep,
ProcessorStepRegistry,
)
from lerobot.types import EnvTransition
# Simplified Config Loading Tests
@@ -98,6 +107,140 @@ def test_load_config_nonexistent_path_tries_hub():
DataProcessorPipeline._load_config("nonexistent/path", "processor.json", {})
def test_from_pretrained_local_directory_missing_state_does_not_call_hub(monkeypatch):
"""Local processor dirs must fail locally when a state file is missing."""
@ProcessorStepRegistry.register("local_missing_state_step")
class LocalMissingStateStep(ProcessorStep):
def __call__(self, transition: EnvTransition) -> EnvTransition:
return transition
def transform_features(
self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
return features
def load_state_dict(self, state: dict[str, torch.Tensor]) -> None:
pass
try:
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir)
config = {
"name": "LocalMissingStatePipeline",
"steps": [{"registry_name": "local_missing_state_step", "state_file": "missing.safetensors"}],
}
(tmp_path / "processor.json").write_text(json.dumps(config))
def fail_hub_download(*args, **kwargs):
pytest.fail("local missing processor state should not call hf_hub_download")
monkeypatch.setattr("lerobot.processor.pipeline.hf_hub_download", fail_hub_download)
with pytest.raises(FileNotFoundError, match="missing.safetensors.*local processor pipeline"):
DataProcessorPipeline.from_pretrained(tmp_path, config_filename="processor.json")
finally:
ProcessorStepRegistry.unregister("local_missing_state_step")
def test_from_pretrained_local_config_file_missing_state_does_not_call_hub(monkeypatch):
"""Local single-file processor configs must also keep missing state resolution local."""
@ProcessorStepRegistry.register("local_file_missing_state_step")
class LocalFileMissingStateStep(ProcessorStep):
def __call__(self, transition: EnvTransition) -> EnvTransition:
return transition
def transform_features(
self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
return features
def load_state_dict(self, state: dict[str, torch.Tensor]) -> None:
pass
try:
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir)
config_path = tmp_path / "processor.json"
config = {
"name": "LocalFileMissingStatePipeline",
"steps": [
{"registry_name": "local_file_missing_state_step", "state_file": "missing.safetensors"}
],
}
config_path.write_text(json.dumps(config))
def fail_hub_download(*args, **kwargs):
pytest.fail("local missing processor state should not call hf_hub_download")
monkeypatch.setattr("lerobot.processor.pipeline.hf_hub_download", fail_hub_download)
with pytest.raises(FileNotFoundError, match="missing.safetensors.*local processor pipeline"):
DataProcessorPipeline.from_pretrained(config_path, config_filename="ignored.json")
finally:
ProcessorStepRegistry.unregister("local_file_missing_state_step")
def test_from_pretrained_hub_source_missing_local_state_still_calls_hub(monkeypatch, tmp_path):
"""Hub sources still fall back to hf_hub_download for state files."""
@ProcessorStepRegistry.register("hub_state_step")
class HubStateStep(ProcessorStep):
def __init__(self):
self.value = torch.tensor(0)
def __call__(self, transition: EnvTransition) -> EnvTransition:
return transition
def transform_features(
self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
return features
def load_state_dict(self, state: dict[str, torch.Tensor]) -> None:
self.value = state["value"]
try:
state_path = tmp_path / "downloaded.safetensors"
save_file({"value": torch.tensor(7)}, state_path)
loaded_config = {
"name": "HubStatePipeline",
"steps": [{"registry_name": "hub_state_step", "state_file": "hub_state.safetensors"}],
}
calls = []
def fake_load_config(cls, model_id, config_filename, hub_download_kwargs):
return loaded_config, tmp_path / "hub_cache"
def fake_hub_download(**kwargs):
calls.append(kwargs)
return str(state_path)
monkeypatch.setattr(DataProcessorPipeline, "_load_config", classmethod(fake_load_config))
monkeypatch.setattr("lerobot.processor.pipeline.hf_hub_download", fake_hub_download)
pipeline = DataProcessorPipeline.from_pretrained("user/repo", config_filename="processor.json")
assert calls == [
{
"repo_id": "user/repo",
"filename": "hub_state.safetensors",
"repo_type": "model",
"force_download": False,
"resume_download": None,
"proxies": None,
"token": None,
"cache_dir": None,
"local_files_only": False,
"revision": None,
}
]
assert pipeline.steps[0].value.item() == 7
finally:
ProcessorStepRegistry.unregister("hub_state_step")
# Config Validation Tests