File size: 16,155 Bytes
1ac9744 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 | from __future__ import annotations
import json
import threading
from pathlib import Path
from PIL import Image
from adam.config import ConfigManager
from adam.executor import ToolContext
from adam.oasis_dataset import validate_oasis_dataset
from adam.planner import Planner
from adam.registry import ToolRegistry, ToolSpec
from adam.tools import oasis_adapter
def _write_oasis_dataset(root: Path, *, frames: int = 4) -> Path:
dataset = root / "Minecraft Action Dataset"
frames_dir = dataset / "frames"
frames_dir.mkdir(parents=True)
rows = []
for index in range(frames):
filename = f"frame_{index:08d}.png"
Image.new("RGB", (256, 144), (index * 20, 50, 80)).save(frames_dir / filename)
rows.append({
"session_id": "session-a",
"frame_index": index,
"filename": filename,
"timestamp_seconds": index / 10,
"w": 1 if index == 1 else 0,
"a": 0,
"s": 0,
"d": 1 if index == 2 else 0,
"jump": 1 if index == 3 else 0,
"mouse_dx": 0.0,
"mouse_dy": 0.0,
"zoom": 0.0,
})
(dataset / "actions.jsonl").write_text(
"\n".join(json.dumps(row) for row in rows),
encoding="utf-8",
)
(dataset / "dataset_info.json").write_text(
json.dumps({"capture_fps": 10, "output_resolution": "256x144"}),
encoding="utf-8",
)
return dataset
def _write_registry(root: Path) -> None:
config = root / "config"
config.mkdir()
(config / "tools.json").write_text(json.dumps({"tools": []}), encoding="utf-8")
def _write_oasis_model(root: Path, name: str = "Smoke") -> Path:
model = root / "Oasis-Game-Trainer" / "output_action_flow_models" / name
(model / "unet").mkdir(parents=True)
(model / "unet" / "config.json").write_text("{}", encoding="utf-8")
(model / "action_flow_model_info.json").write_text(
json.dumps({"model_type": "action_conditioned_rectified_flow_video", "model_name": name}),
encoding="utf-8",
)
return model
def test_oasis_plugin_is_registered() -> None:
registry = ToolRegistry(Path.cwd())
tool = registry.get("oasis_trainer")
player = registry.get("oasis_player")
assert tool.model_trainers == ()
assert "resume_training" in tool.capabilities
assert registry.model_plugins.training_schema("oasis")["resolution"]["default"] == "256x144"
assert player.model_trainers == ("oasis",)
def test_oasis_dataset_validation_accepts_legacy_actions_jsonl(tmp_path: Path) -> None:
dataset = _write_oasis_dataset(tmp_path)
report = validate_oasis_dataset(str(dataset), frame_gap=1)
assert report.ok
assert report.valid_rows == 4
assert report.valid_transitions == 3
assert report.action_counts["w"] == 1
def test_oasis_dataset_validation_rejects_missing_labels(tmp_path: Path) -> None:
dataset = _write_oasis_dataset(tmp_path)
rows = (dataset / "actions.jsonl").read_text(encoding="utf-8").splitlines()
first = json.loads(rows[0])
del first["jump"]
rows[0] = json.dumps(first)
(dataset / "actions.jsonl").write_text("\n".join(rows), encoding="utf-8")
report = validate_oasis_dataset(str(dataset), frame_gap=1)
assert not report.ok
assert any("missing action label" in error for error in report.errors)
def test_oasis_dataset_validation_accepts_legacy_action_suffix_mismatch(tmp_path: Path) -> None:
dataset = _write_oasis_dataset(tmp_path, frames=3)
frames_dir = dataset / "frames"
(frames_dir / "frame_00000001.png").rename(frames_dir / "frame_00000001_CAM.png")
report = validate_oasis_dataset(str(dataset), frame_gap=1)
assert report.ok
assert report.valid_rows == 3
assert any("missing legacy filename" in warning for warning in report.warnings)
def test_oasis_dataset_validation_skips_deleted_frames(tmp_path: Path) -> None:
dataset = _write_oasis_dataset(tmp_path, frames=5)
(dataset / "frames" / "frame_00000004.png").unlink()
report = validate_oasis_dataset(str(dataset), frame_gap=1)
assert report.ok
assert report.valid_rows == 4
assert report.valid_transitions == 3
assert any("skipping row" in warning for warning in report.warnings)
def test_oasis_training_request_creates_standard_plan(tmp_path: Path, monkeypatch) -> None:
_write_registry(tmp_path)
dataset = _write_oasis_dataset(tmp_path)
oasis_root = tmp_path / "Oasis-Game-Trainer"
oasis_root.mkdir()
(oasis_root / "roblox_action_flow_app.py").write_text("# oasis", encoding="utf-8")
config = ConfigManager(tmp_path)
config.settings["provider"] = "manual"
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
monkeypatch.chdir(tmp_path)
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan(
f"Create an Oasis model called Old Minecraft Beta, use the {dataset} dataset, "
"train it for 5 epochs at 256x144. "
'[ADAM_TRAINING_OPTIONS:{"resolution":"256x144","batch_size":2,"workers":0}]'
)
assert plan.requires_confirmation is True
assert [step.tool_id for step in plan.steps] == ["oasis_trainer"]
assert plan.steps[0].arguments["model_name"] == "Old Minecraft Beta"
assert Path(plan.steps[0].arguments["output_dir"]).parent.name == "output_action_flow_models"
assert plan.steps[0].arguments["resolution"] == "256x144"
def test_oasis_player_request_finds_registered_model(tmp_path: Path) -> None:
_write_registry(tmp_path)
oasis_root = tmp_path / "Oasis-Game-Trainer"
_write_oasis_model(tmp_path, "Beta World")
config = ConfigManager(tmp_path)
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan("Open Oasis Beta World with seed 42")
assert plan.requires_confirmation is False
assert [step.tool_id for step in plan.steps] == ["oasis_player"]
assert plan.steps[0].arguments["model_name"] == "Beta World"
assert plan.steps[0].arguments["seed"] == 42
def test_oasis_player_request_rejects_invalid_explicit_folder(tmp_path: Path) -> None:
_write_registry(tmp_path)
invalid = tmp_path / "not-a-model"
invalid.mkdir()
planner = Planner(tmp_path, ToolRegistry(tmp_path), ConfigManager(tmp_path))
plan = planner.plan(f"Launch Oasis from {invalid}")
assert plan.steps == []
assert "valid Oasis action model folder" in plan.summary
def test_oasis_fine_tune_accepts_existing_dataset_path(tmp_path: Path) -> None:
_write_registry(tmp_path)
bundle = tmp_path / "Roblox Dataset"
dataset = _write_oasis_dataset(bundle)
oasis_root = tmp_path / "Oasis-Game-Trainer"
_write_oasis_model(tmp_path, "Roblox Oasis V 2.3.6")
config = ConfigManager(tmp_path)
config.settings["provider"] = "manual"
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan(
"Fine-tune Roblox Oasis V 2.3.6 for 30 epochs with Oasis Action World Model. "
"[ADAM_FINE_TUNE:"
+ json.dumps({
"dataset_mode": "existing",
"dataset_name": str(bundle),
"epochs": 30,
"image_count": 500,
"model_name": "Roblox Oasis V 2.3.6",
"new_subject": "",
"trainer": "oasis",
"training_options": {"resolution": "256x144", "workers": 0},
})
+ "]"
)
assert plan.requires_confirmation is True
step = plan.steps[0]
assert step.tool_id == "oasis_trainer"
assert step.arguments["dataset_dir"] == str(dataset.resolve())
assert step.arguments["resume_from"] == str(
(oasis_root / "output_action_flow_models" / "Roblox Oasis V 2.3.6").resolve()
)
def test_oasis_fine_tune_normalizes_path_shaped_model_name(tmp_path: Path) -> None:
_write_registry(tmp_path)
dataset = _write_oasis_dataset(tmp_path)
oasis_root = tmp_path / "Oasis-Game-Trainer"
model = _write_oasis_model(tmp_path, "Roblox Oasis V 2.3.6")
(model / "action_flow_model_info.json").write_text(
json.dumps({
"model_type": "action_conditioned_rectified_flow_video",
"model_name": str(model),
}),
encoding="utf-8",
)
config = ConfigManager(tmp_path)
config.settings["provider"] = "manual"
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan(
f"Fine-tune {model} for 30 epochs with Oasis Action World Model. "
"[ADAM_FINE_TUNE:"
+ json.dumps({
"dataset_mode": "existing",
"dataset_name": str(dataset),
"epochs": 30,
"image_count": 500,
"model_name": str(model),
"new_subject": "",
"trainer": "oasis",
"training_options": {"resolution": "256x144", "workers": 0},
})
+ "]"
)
assert plan.requires_confirmation is True
assert plan.steps[0].arguments["model_name"] == "Roblox Oasis V 2.3.6"
def test_oasis_fine_tune_finds_model_when_payload_path_has_old_parent(tmp_path: Path) -> None:
_write_registry(tmp_path)
dataset = _write_oasis_dataset(tmp_path)
oasis_root = tmp_path / "FlowMatchImageGenerator" / "Oasis-Game-Trainer"
model = _write_oasis_model(tmp_path / "FlowMatchImageGenerator", "Roblox Oasis V 2.3.6")
old_parent_path = (
tmp_path
/ "FlowMatchImageGenerator"
/ "output_action_flow_models"
/ "Roblox Oasis V 2.3.6"
)
config = ConfigManager(tmp_path)
config.settings["provider"] = "manual"
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan(
f"Fine-tune {old_parent_path} for 30 epochs with Oasis Action World Model. "
"[ADAM_FINE_TUNE:"
+ json.dumps({
"dataset_mode": "existing",
"dataset_name": str(dataset),
"epochs": 30,
"image_count": 500,
"model_name": str(old_parent_path),
"new_subject": "",
"trainer": "oasis",
"training_options": {"resolution": "256x144", "workers": 0},
})
+ "]"
)
assert plan.requires_confirmation is True
assert plan.steps[0].arguments["resume_from"] == str(model.resolve())
assert plan.steps[0].arguments["model_name"] == "Roblox Oasis V 2.3.6"
def test_oasis_fine_tune_expands_dataset_bundle_to_safe_list(tmp_path: Path) -> None:
_write_registry(tmp_path)
bundle = tmp_path / "Roblox Dataset"
first = _write_oasis_dataset(bundle / "one")
second = _write_oasis_dataset(bundle / "two")
oasis_root = tmp_path / "Oasis-Game-Trainer"
_write_oasis_model(tmp_path, "Roblox Oasis V 2.3.6")
config = ConfigManager(tmp_path)
config.settings["provider"] = "manual"
config.settings["tool_folders"] = {"oasis_trainer": str(oasis_root)}
planner = Planner(tmp_path, ToolRegistry(tmp_path), config)
plan = planner.plan(
"Fine-tune Roblox Oasis V 2.3.6 for 30 epochs with Oasis Action World Model. "
"[ADAM_FINE_TUNE:"
+ json.dumps({
"dataset_mode": "existing",
"dataset_name": str(bundle),
"epochs": 30,
"image_count": 500,
"model_name": "Roblox Oasis V 2.3.6",
"new_subject": "",
"trainer": "oasis",
"training_options": {"resolution": "256x144", "workers": 0},
})
+ "]"
)
dataset_dir = plan.steps[0].arguments["dataset_dir"]
assert dataset_dir == [str(first.resolve()), str(second.resolve())]
def test_oasis_adapter_builds_worker_command_and_registers_model(tmp_path: Path, monkeypatch) -> None:
dataset = _write_oasis_dataset(tmp_path)
oasis_root = tmp_path / "Oasis-Game-Trainer"
output = oasis_root / "output_action_flow_models" / "Smoke"
oasis_root.mkdir()
(oasis_root / "roblox_action_flow_app.py").write_text("# oasis", encoding="utf-8")
config = ConfigManager(tmp_path)
config.update({"tool_folders": {"oasis_trainer": str(oasis_root)}})
captured: dict[str, object] = {}
class FakeProcess:
pid = 123
returncode = 0
stdout = iter([
'ACTION_FLOW_EVENT:{"type":"start","transitions":3,"training":2,"validation":1,"device":"cpu"}\n',
'ACTION_FLOW_EVENT:{"type":"progress","epoch":1,"epochs":1,"update":1,"total_updates":1,"loss":0.5}\n',
'ACTION_FLOW_EVENT:{"type":"complete","output_dir":"x"}\n',
])
def poll(self):
return 0
def fake_popen(command, **kwargs):
captured["command"] = command
captured["cwd"] = kwargs.get("cwd")
(output / "unet").mkdir(parents=True)
(output / "unet" / "config.json").write_text("{}", encoding="utf-8")
(output / "action_flow_model_info.json").write_text(
json.dumps({"model_type": "action_conditioned_rectified_flow_video"}),
encoding="utf-8",
)
return FakeProcess()
monkeypatch.setattr(oasis_adapter.subprocess, "Popen", fake_popen)
context = ToolContext(
tmp_path,
"OASIS",
ToolSpec("oasis_trainer", "Oasis", "test", "Training", "train_oasis"),
threading.Event(),
threading.Event(),
lambda *_args, **_kwargs: None,
lambda *_args: None,
)
context.run_event.set()
result = oasis_adapter.train_oasis(
context,
dataset_dir=str(dataset),
model_name="Smoke",
epochs=1,
output_dir=str(output),
workers=0,
preview_enabled=False,
)
command = captured["command"]
assert "--train-worker" in command
assert "--dataset-dir" in command
assert str(dataset) in command
assert "--mixed-precision" in command
assert result["assets"][0]["trainer"] == "oasis"
def test_oasis_adapter_accepts_dataset_folder_list(tmp_path: Path, monkeypatch) -> None:
first = _write_oasis_dataset(tmp_path / "one")
second = _write_oasis_dataset(tmp_path / "two")
oasis_root = tmp_path / "Oasis-Game-Trainer"
output = oasis_root / "output_action_flow_models" / "Smoke"
oasis_root.mkdir()
(oasis_root / "roblox_action_flow_app.py").write_text("# oasis", encoding="utf-8")
ConfigManager(tmp_path).update({"tool_folders": {"oasis_trainer": str(oasis_root)}})
captured: dict[str, object] = {}
class FakeProcess:
pid = 123
returncode = 0
stdout = iter([
'ACTION_FLOW_EVENT:{"type":"complete","output_dir":"x"}\n',
])
def poll(self):
return 0
def fake_popen(command, **kwargs):
captured["command"] = command
(output / "unet").mkdir(parents=True)
(output / "unet" / "config.json").write_text("{}", encoding="utf-8")
(output / "action_flow_model_info.json").write_text(
json.dumps({"model_type": "action_conditioned_rectified_flow_video"}),
encoding="utf-8",
)
return FakeProcess()
monkeypatch.setattr(oasis_adapter.subprocess, "Popen", fake_popen)
context = ToolContext(
tmp_path,
"OASIS",
ToolSpec("oasis_trainer", "Oasis", "test", "Training", "train_oasis"),
threading.Event(),
threading.Event(),
lambda *_args, **_kwargs: None,
lambda *_args: None,
)
context.run_event.set()
result = oasis_adapter.train_oasis(
context,
dataset_dir=[str(first), str(second)],
model_name="Smoke",
epochs=1,
output_dir=str(output),
workers=0,
preview_enabled=False,
)
command = captured["command"]
dataset_arg = command[command.index("--dataset-dir") + 1]
assert dataset_arg == f"{first};{second}"
assert result["assets"][0]["dataset_path"] == f"{first};{second}"
|