已合并
test(jit): add ScriptModule API alignment test cases [v2.10.0] #37635
TensorLake创建于 6月4日
test(jit): add ScriptModule API alignment test cases [v2.10.0] #37635
已合并
共 1 个文件变更+609-0
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| 1 | +""" | ||
| 2 | +Add validation cases for torch.jit.ScriptModule APIs on NPU: | ||
| 3 | +1. PyTorch community lacks sufficient direct API validations for | ||
| 4 | + ScriptModule instance methods, so this file is added. | ||
| 5 | +2. This file validates 19 torch.jit.ScriptModule APIs using | ||
| 6 | + torch.jit.script() as the canonical creation method: | ||
| 7 | + train, eval, zero_grad, float, double, to, type, | ||
| 8 | + state_dict, save, extra_repr, requires_grad_, to_empty, | ||
| 9 | + xpu, get_buffer, set_submodule, register_module, | ||
| 10 | + register_parameter, share_memory, set_extra_state | ||
| 11 | + (extendable). | ||
| 12 | +""" | ||
| 13 | + | ||
| 14 | +import io | ||
| 15 | +import os | ||
| 16 | +import re | ||
| 17 | +import tempfile | ||
| 18 | + | ||
| 19 | +import torch | ||
| 20 | +import torch.nn as nn | ||
| 21 | +from torch.testing._internal.common_utils import run_tests, TestCase | ||
| 22 | + | ||
| 23 | + | ||
| 24 | +device_type = acc.type if (acc := torch.accelerator.current_accelerator()) else "cpu" | ||
| 25 | + | ||
| 26 | + | ||
| 27 | +# --------------------------------------------------------------------------- | ||
| 28 | +# Module-level model builders (required by torch.jit.script() source access) | ||
| 29 | +# --------------------------------------------------------------------------- | ||
| 30 | + | ||
| 31 | +def _make_linear(): | ||
| 32 | + class M(nn.Module): | ||
| 33 | + def __init__(self): | ||
| 34 | + super().__init__() | ||
| 35 | + self.linear = nn.Linear(2, 2) | ||
| 36 | + | ||
| 37 | + def forward(self, x): | ||
| 38 | + return self.linear(x) | ||
| 39 | + | ||
| 40 | + return torch.jit.script(M().to(device_type)) | ||
| 41 | + | ||
| 42 | + | ||
| 43 | +def _make_with_buffer(): | ||
| 44 | + class M(nn.Module): | ||
| 45 | + def __init__(self): | ||
| 46 | + super().__init__() | ||
| 47 | + self.linear = nn.Linear(2, 2) | ||
| 48 | + self.register_buffer("buf", torch.ones(2, 2)) | ||
| 49 | + | ||
| 50 | + def forward(self, x): | ||
| 51 | + return self.linear(x) + self.buf | ||
| 52 | + | ||
| 53 | + return torch.jit.script(M().to(device_type)) | ||
| 54 | + | ||
| 55 | + | ||
| 56 | +def _make_nested(): | ||
| 57 | + class Sub(nn.Module): | ||
| 58 | + def __init__(self): | ||
| 59 | + super().__init__() | ||
| 60 | + self.linear = nn.Linear(2, 2) | ||
| 61 | + | ||
| 62 | + def forward(self, x): | ||
| 63 | + return self.linear(x) | ||
| 64 | + | ||
| 65 | + class Outer(nn.Module): | ||
| 66 | + def __init__(self): | ||
| 67 | + super().__init__() | ||
| 68 | + self.sub = Sub() | ||
| 69 | + | ||
| 70 | + def forward(self, x): | ||
| 71 | + return self.sub(x) | ||
| 72 | + | ||
| 73 | + return torch.jit.script(Outer().to(device_type)) | ||
| 74 | + | ||
| 75 | + | ||
| 76 | +def _make_cpu_linear(): | ||
| 77 | + class M(nn.Module): | ||
| 78 | + def __init__(self): | ||
| 79 | + super().__init__() | ||
| 80 | + self.linear = nn.Linear(2, 2) | ||
| 81 | + | ||
| 82 | + def forward(self, x): | ||
| 83 | + return self.linear(x) | ||
| 84 | + | ||
| 85 | + return torch.jit.script(M()) | ||
| 86 | + | ||
| 87 | + | ||
| 88 | +def _make_nested_with_buffer(): | ||
| 89 | + class Sub(nn.Module): | ||
| 90 | + def __init__(self): | ||
| 91 | + super().__init__() | ||
| 92 | + self.register_buffer("buf", torch.ones(2, 2)) | ||
| 93 | + | ||
| 94 | + def forward(self, x): | ||
| 95 | + return x + self.buf | ||
| 96 | + | ||
| 97 | + class Outer(nn.Module): | ||
| 98 | + def __init__(self): | ||
| 99 | + super().__init__() | ||
| 100 | + self.sub = Sub() | ||
| 101 | + | ||
| 102 | + def forward(self, x): | ||
| 103 | + return self.sub(x) | ||
| 104 | + | ||
| 105 | + return torch.jit.script(Outer().to(device_type)) | ||
| 106 | + | ||
| 107 | + | ||
| 108 | +# =================================================================== | ||
| 109 | +# Test Classes | ||
| 110 | +# =================================================================== | ||
| 111 | + | ||
| 112 | + | ||
| 113 | +class TestScriptModuleTrainEval(TestCase): | ||
| 114 | + | ||
| 115 | + def test_train_default_is_training(self): | ||
| 116 | + sm = _make_linear() | ||
| 117 | + self.assertTrue(sm.training) | ||
| 118 | + | ||
| 119 | + def test_train_set_true_explicit(self): | ||
| 120 | + sm = _make_linear() | ||
| 121 | + sm.train(True) | ||
| 122 | + self.assertTrue(sm.training) | ||
| 123 | + | ||
| 124 | + def test_train_set_false(self): | ||
| 125 | + sm = _make_linear() | ||
| 126 | + sm.train(False) | ||
| 127 | + self.assertFalse(sm.training) | ||
| 128 | + | ||
| 129 | + def test_eval_sets_training_false(self): | ||
| 130 | + sm = _make_linear() | ||
| 131 | + sm.eval() | ||
| 132 | + self.assertFalse(sm.training) | ||
| 133 | + | ||
| 134 | + def test_train_returns_self(self): | ||
| 135 | + sm = _make_linear() | ||
| 136 | + result = sm.train() | ||
| 137 | + self.assertIs(result, sm) | ||
| 138 | + | ||
| 139 | + def test_eval_returns_self(self): | ||
| 140 | + sm = _make_linear() | ||
| 141 | + result = sm.eval() | ||
| 142 | + self.assertIs(result, sm) | ||
| 143 | + | ||
| 144 | + def test_train_eval_roundtrip(self): | ||
| 145 | + sm = _make_linear() | ||
| 146 | + sm.train() | ||
| 147 | + self.assertTrue(sm.training) | ||
| 148 | + sm.eval() | ||
| 149 | + self.assertFalse(sm.training) | ||
| 150 | + sm.train(True) | ||
| 151 | + self.assertTrue(sm.training) | ||
| 152 | + | ||
| 153 | + def test_train_on_npu(self): | ||
| 154 | + sm = _make_linear() | ||
| 155 | + sm.train() | ||
| 156 | + self.assertTrue(sm.training) | ||
| 157 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 158 | + | ||
| 159 | + def test_eval_on_npu(self): | ||
| 160 | + sm = _make_linear() | ||
| 161 | + sm.eval() | ||
| 162 | + self.assertFalse(sm.training) | ||
| 163 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 164 | + | ||
| 165 | + def test_train_propagates_to_submodules(self): | ||
| 166 | + sm = _make_nested() | ||
| 167 | + sm.train() | ||
| 168 | + self.assertTrue(sm.sub.training) | ||
| 169 | + | ||
| 170 | + def test_eval_propagates_to_submodules(self): | ||
| 171 | + sm = _make_nested() | ||
| 172 | + sm.eval() | ||
| 173 | + self.assertFalse(sm.sub.training) | ||
| 174 | + | ||
| 175 | + | ||
| 176 | +class TestScriptModuleZeroGrad(TestCase): | ||
| 177 | + | ||
| 178 | + def test_zero_grad_no_error(self): | ||
| 179 | + sm = _make_linear() | ||
| 180 | + sm.zero_grad() | ||
| 181 | + | ||
| 182 | + def test_zero_grad_clears_grads(self): | ||
| 183 | + sm = _make_linear() | ||
| 184 | + x = torch.randn(2, 2, requires_grad=True).to(device_type) | ||
| 185 | + out = sm(x) | ||
| 186 | + out.sum().backward() | ||
| 187 | + self.assertIsNotNone(sm.linear.weight.grad) | ||
| 188 | + sm.zero_grad() | ||
| 189 | + self.assertIsNone(sm.linear.weight.grad) | ||
| 190 | + | ||
| 191 | + def test_zero_grad_set_to_none(self): | ||
| 192 | + sm = _make_linear() | ||
| 193 | + x = torch.randn(2, 2, requires_grad=True).to(device_type) | ||
| 194 | + out = sm(x) | ||
| 195 | + out.sum().backward() | ||
| 196 | + self.assertIsNotNone(sm.linear.weight.grad) | ||
| 197 | + sm.zero_grad(set_to_none=True) | ||
| 198 | + self.assertIsNone(sm.linear.weight.grad) | ||
| 199 | + | ||
| 200 | + def test_zero_grad_set_to_none_false(self): | ||
| 201 | + sm = _make_linear() | ||
| 202 | + x = torch.randn(2, 2, requires_grad=True).to(device_type) | ||
| 203 | + out = sm(x) | ||
| 204 | + out.sum().backward() | ||
| 205 | + old_grad = sm.linear.weight.grad | ||
| 206 | + self.assertIsNotNone(old_grad) | ||
| 207 | + sm.zero_grad(set_to_none=False) | ||
| 208 | + self.assertIsNotNone(sm.linear.weight.grad) | ||
| 209 | + self.assertEqual(sm.linear.weight.grad, | ||
| 210 | + torch.zeros_like(old_grad)) | ||
| 211 | + | ||
| 212 | + def test_zero_grad_backward_chain_on_npu(self): | ||
| 213 | + sm = _make_linear() | ||
| 214 | + x = torch.randn(2, 2, requires_grad=True).to(device_type) | ||
| 215 | + out = sm(x) | ||
| 216 | + out.sum().backward() | ||
| 217 | + self.assertIsNotNone(sm.linear.weight.grad) | ||
| 218 | + sm.zero_grad() | ||
| 219 | + self.assertIsNone(sm.linear.weight.grad) | ||
| 220 | + out2 = sm(x) | ||
| 221 | + out2.sum().backward() | ||
| 222 | + self.assertIsNotNone(sm.linear.weight.grad) | ||
| 223 | + | ||
| 224 | + | ||
| 225 | +class TestScriptModuleTo(TestCase): | ||
| 226 | + | ||
| 227 | + def test_to_dtype(self): | ||
| 228 | + sm = _make_linear() | ||
| 229 | + sm.to(torch.float64) | ||
| 230 | + self.assertIn(sm.linear.weight.dtype, | ||
| 231 | + (torch.float64, torch.float32)) | ||
| 232 | + | ||
| 233 | + def test_to_device(self): | ||
| 234 | + sm = _make_linear() | ||
| 235 | + sm.to(device_type) | ||
| 236 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 237 | + | ||
| 238 | + def test_to_returns_self(self): | ||
| 239 | + sm = _make_linear() | ||
| 240 | + result = sm.to(torch.float32) | ||
| 241 | + self.assertIsInstance(result, torch.jit.ScriptModule) | ||
| 242 | + | ||
| 243 | + def test_to_device_and_dtype(self): | ||
| 244 | + sm = _make_linear() | ||
| 245 | + sm.to(device_type, torch.float64) | ||
| 246 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 247 | + self.assertIn(sm.linear.weight.dtype, | ||
| 248 | + (torch.float64, torch.float32)) | ||
| 249 | + | ||
| 250 | + def test_to_dtype_keyword(self): | ||
| 251 | + sm = _make_linear() | ||
| 252 | + sm.to(dtype=torch.float64) | ||
| 253 | + self.assertIn(sm.linear.weight.dtype, | ||
| 254 | + (torch.float64, torch.float32)) | ||
| 255 | + | ||
| 256 | + def test_to_string_device(self): | ||
| 257 | + sm = _make_linear() | ||
| 258 | + sm.to(str(torch.device(device_type))) | ||
| 259 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 260 | + | ||
| 261 | + def test_to_no_args_returns_self(self): | ||
| 262 | + sm = _make_linear() | ||
| 263 | + result = sm.to() | ||
| 264 | + self.assertIsInstance(result, torch.jit.ScriptModule) | ||
| 265 | + | ||
| 266 | + def test_to_propagates_to_submodules(self): | ||
| 267 | + sm = _make_nested() | ||
| 268 | + sm.to(dtype=torch.float64) | ||
| 269 | + self.assertIn(sm.sub.linear.weight.dtype, | ||
| 270 | + (torch.float64, torch.float32)) | ||
| 271 | + | ||
| 272 | + def test_to_npu_and_dtype(self): | ||
| 273 | + sm = _make_linear() | ||
| 274 | + sm.to(device_type, dtype=torch.float64) | ||
| 275 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 276 | + self.assertIn(sm.linear.weight.dtype, | ||
| 277 | + (torch.float64, torch.float32)) | ||
| 278 | + | ||
| 279 | + | ||
| 280 | +class TestScriptModuleFloatDouble(TestCase): | ||
| 281 | + | ||
| 282 | + def test_float_returns_self(self): | ||
| 283 | + sm = _make_linear() | ||
| 284 | + result = sm.float() | ||
| 285 | + self.assertIsInstance(result, torch.jit.ScriptModule) | ||
| 286 | + | ||
| 287 | + def test_float_converts_params(self): | ||
| 288 | + sm = _make_linear() | ||
| 289 | + sm.float() | ||
| 290 | + self.assertEqual(sm.linear.weight.dtype, torch.float32) | ||
| 291 | + | ||
| 292 | + def test_float_on_npu(self): | ||
| 293 | + sm = _make_linear() | ||
| 294 | + sm.float() | ||
| 295 | + self.assertEqual(sm.linear.weight.dtype, torch.float32) | ||
| 296 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 297 | + | ||
| 298 | + def test_float_propagates_to_submodules(self): | ||
| 299 | + sm = _make_nested() | ||
| 300 | + sm.float() | ||
| 301 | + self.assertEqual(sm.sub.linear.weight.dtype, torch.float32) | ||
| 302 | + | ||
| 303 | + def test_double_returns_self(self): | ||
| 304 | + sm = _make_linear() | ||
| 305 | + result = sm.double() | ||
| 306 | + self.assertIsInstance(result, torch.jit.ScriptModule) | ||
| 307 | + | ||
| 308 | + def test_double_converts_params(self): | ||
| 309 | + sm = _make_linear() | ||
| 310 | + sm.double() | ||
| 311 | + self.assertIn(sm.linear.weight.dtype, | ||
| 312 | + (torch.float64, torch.float32)) | ||
| 313 | + | ||
| 314 | + def test_double_on_npu_fallback_to_float32(self): | ||
| 315 | + sm = _make_linear() | ||
| 316 | + sm.double() | ||
| 317 | + # NPU does not support float64; double() falls back to float32 | ||
| 318 | + self.assertEqual(sm.linear.weight.dtype, torch.float32) | ||
| 319 | + | ||
| 320 | + | ||
| 321 | +class TestScriptModuleType(TestCase): | ||
| 322 | + | ||
| 323 | + def test_type_float32(self): | ||
| 324 | + sm = _make_linear() | ||
| 325 | + sm.type(torch.float32) | ||
| 326 | + self.assertEqual(sm.linear.weight.dtype, torch.float32) | ||
| 327 | + | ||
| 328 | + def test_type_float64(self): | ||
| 329 | + sm = _make_linear() | ||
| 330 | + sm.type(torch.float64) | ||
| 331 | + self.assertIn(sm.linear.weight.dtype, | ||
| 332 | + (torch.float64, torch.float32)) | ||
| 333 | + | ||
| 334 | + def test_type_on_npu(self): | ||
| 335 | + sm = _make_linear() | ||
| 336 | + sm.type(torch.float64) | ||
| 337 | + self.assertEqual(sm.linear.weight.device.type, device_type) | ||
| 338 | + self.assertIn(sm.linear.weight.dtype, | ||
| 339 | + (torch.float64, torch.float32)) | ||
| 340 | + | ||
| 341 | + def test_type_int32_raises(self): | ||
| 342 | + sm = _make_linear() | ||
| 343 | + with self.assertRaisesRegex( | ||
| 344 | + RuntimeError, r"must be floating point"): | ||
| 345 | + sm.type(torch.int32) | ||
| 346 | + | ||
| 347 | + | ||
| 348 | +class TestScriptModuleStateDict(TestCase): | ||
| 349 | + | ||
| 350 | + def test_state_dict_contains_params(self): | ||
| 351 | + sm = _make_linear() | ||
| 352 | + sd = sm.state_dict() | ||
| 353 | + self.assertIn("linear.weight", sd) | ||
| 354 | + self.assertIn("linear.bias", sd) | ||
| 355 | + | ||
| 356 | + def test_state_dict_contains_buffers(self): | ||
| 357 | + sm = _make_with_buffer() | ||
| 358 | + sd = sm.state_dict() | ||
| 359 | + self.assertIn("buf", sd) | ||
| 360 | + | ||
| 361 | + def test_state_dict_values_match(self): | ||
| 362 | + sm = _make_linear() | ||
| 363 | + sd = sm.state_dict() | ||
| 364 | + self.assertEqual(sd["linear.weight"], sm.linear.weight) | ||
| 365 | + self.assertEqual(sd["linear.bias"], sm.linear.bias) | ||
| 366 | + | ||
| 367 | + def test_state_dict_on_npu(self): | ||
| 368 | + sm = _make_linear() | ||
| 369 | + sd = sm.state_dict() | ||
| 370 | + self.assertEqual(sd["linear.weight"].device.type, device_type) | ||
| 371 | + | ||
| 372 | + def test_state_dict_with_prefix(self): | ||
| 373 | + sm = _make_linear() | ||
| 374 | + sd = sm.state_dict(prefix="mymodel.") | ||
| 375 | + self.assertIn("mymodel.linear.weight", sd) | ||
| 376 | + self.assertIn("mymodel.linear.bias", sd) | ||
| 377 | + | ||
| 378 | + def test_state_dict_with_destination(self): | ||
| 379 | + sm = _make_linear() | ||
| 380 | + dest = {"existing": torch.tensor(0)} | ||
| 381 | + result = sm.state_dict(destination=dest, prefix="mod.") | ||
| 382 | + self.assertIs(result, dest) | ||
| 383 | + self.assertIn("existing", result) | ||
| 384 | + self.assertIn("mod.linear.weight", result) | ||
| 385 | + | ||
| 386 | + def test_state_dict_keep_vars(self): | ||
| 387 | + sm = _make_linear() | ||
| 388 | + sd = sm.state_dict(keep_vars=True) | ||
| 389 | + self.assertIsInstance(sd["linear.weight"], nn.Parameter) | ||
| 390 | + self.assertTrue(sd["linear.weight"].requires_grad) | ||
| 391 | + | ||
| 392 | + | ||
| 393 | +class TestScriptModuleSave(TestCase): | ||
| 394 | + | ||
| 395 | + def test_save_and_load(self): | ||
| 396 | + sm = _make_linear() | ||
| 397 | + with tempfile.NamedTemporaryFile(suffix=".pt", delete=False) as f: | ||
| 398 | + path = f.name | ||
| 399 | + try: | ||
| 400 | + sm.save(path) | ||
| 401 | + loaded = torch.jit.load(path) | ||
| 402 | + x = torch.randn(2, 2).to(device_type) | ||
| 403 | + self.assertEqual(sm(x), loaded(x)) | ||
| 404 | + finally: | ||
| 405 | + if os.path.exists(path): | ||
| 406 | + os.remove(path) | ||
| 407 | + | ||
| 408 | + def test_save_preserves_output(self): | ||
| 409 | + sm = _make_linear() | ||
| 410 | + with tempfile.NamedTemporaryFile(suffix=".pt", delete=False) as f: | ||
| 411 | + path = f.name | ||
| 412 | + try: | ||
| 413 | + with torch.no_grad(): | ||
| 414 | + sm.linear.weight.fill_(1.0) | ||
| 415 | + sm.linear.bias.fill_(2.0) | ||
| 416 | + sm.save(path) | ||
| 417 | + loaded = torch.jit.load(path) | ||
| 418 | + self.assertEqual(loaded.linear.weight, torch.ones(2, 2)) | ||
| 419 | + self.assertEqual(loaded.linear.bias, torch.ones(2) * 2) | ||
| 420 | + finally: | ||
| 421 | + if os.path.exists(path): | ||
| 422 | + os.remove(path) | ||
| 423 | + | ||
| 424 | + def test_save_returns_none(self): | ||
| 425 | + sm = _make_linear() | ||
| 426 | + with tempfile.NamedTemporaryFile(suffix=".pt", delete=False) as f: | ||
| 427 | + path = f.name | ||
| 428 | + try: | ||
| 429 | + ret = sm.save(path) | ||
| 430 | + self.assertIsNone(ret) | ||
| 431 | + finally: | ||
| 432 | + if os.path.exists(path): | ||
| 433 | + os.remove(path) | ||
| 434 | + | ||
| 435 | + def test_save_on_npu(self): | ||
| 436 | + sm = _make_linear() | ||
| 437 | + with tempfile.NamedTemporaryFile(suffix=".pt", delete=False) as f: | ||
| 438 | + path = f.name | ||
| 439 | + try: | ||
| 440 | + sm.save(path) | ||
| 441 | + loaded = torch.jit.load(path) | ||
| 442 | + x = torch.randn(2, 2).to(device_type) | ||
| 443 | + self.assertEqual(sm(x), loaded(x)) | ||
| 444 | + finally: | ||
| 445 | + if os.path.exists(path): | ||
| 446 | + os.remove(path) | ||
| 447 | + | ||
| 448 | + def test_save_with_extra_files(self): | ||
| 449 | + sm = _make_linear() | ||
| 450 | + extra = {"meta.json": '{"version": 1}', "readme.txt": "hello"} | ||
| 451 | + with tempfile.NamedTemporaryFile(suffix=".pt", delete=False) as f: | ||
| 452 | + path = f.name | ||
| 453 | + try: | ||
| 454 | + sm.save(path, _extra_files=extra) | ||
| 455 | + self.assertTrue(os.path.exists(path)) | ||
| 456 | + self.assertGreater(os.path.getsize(path), 0) | ||
| 457 | + finally: | ||
| 458 | + if os.path.exists(path): | ||
| 459 | + os.remove(path) | ||
| 460 | + | ||
| 461 | + def test_save_to_buffer(self): | ||
| 462 | + sm = _make_linear() | ||
| 463 | + buf = sm.save_to_buffer() | ||
| 464 | + self.assertIsInstance(buf, bytes) | ||
| 465 | + loaded = torch.jit.load(io.BytesIO(buf)) | ||
| 466 | + x = torch.randn(2, 2).to(device_type) | ||
| 467 | + self.assertEqual(sm(x), loaded(x)) | ||
| 468 | + | ||
| 469 | + | ||
| 470 | +class TestScriptModuleExtraRepr(TestCase): | ||
| 471 | + | ||
| 472 | + def test_extra_repr_returns_str(self): | ||
| 473 | + sm = _make_linear() | ||
| 474 | + result = sm.extra_repr() | ||
| 475 | + self.assertIsInstance(result, str) | ||
| 476 | + | ||
| 477 | + def test_extra_repr_contains_original_name(self): | ||
| 478 | + sm = _make_linear() | ||
| 479 | + result = sm.extra_repr() | ||
| 480 | + match = re.search(r"original_name=(\S+)", result) | ||
| 481 | + if match: | ||
| 482 | + self.assertIsInstance(match.group(1), str) | ||
| 483 | + | ||
| 484 | + def test_extra_repr_on_npu(self): | ||
| 485 | + sm = _make_linear() | ||
| 486 | + result = sm.extra_repr() | ||
| 487 | + self.assertIsInstance(result, str) | ||
| 488 | + | ||
| 489 | + | ||
| 490 | +class TestScriptModuleShareMemory(TestCase): | ||
| 491 | + """share_memory behavior differs by device: | ||
| 492 | + CPU: works, makes storage shared. | ||
| 493 | + GPU/CUDA: no-op (per torch.Tensor.share_memory_ docstring). | ||
| 494 | + NPU: torch-npu intercepts with RuntimeError. | ||
| 495 | + Tests document actual NPU behavior and CPU baseline.""" | ||
| 496 | + | ||
| 497 | + def test_share_memory_cpu_returns_self(self): | ||
| 498 | + sm = _make_cpu_linear() | ||
| 499 | + result = sm.share_memory() | ||
| 500 | + self.assertIs(result, sm) | ||
| 501 | + | ||
| 502 | + def test_share_memory_cpu_makes_shared(self): | ||
| 503 | + sm = _make_cpu_linear() | ||
| 504 | + sm.share_memory() | ||
| 505 | + self.assertTrue(sm.linear.weight.untyped_storage().is_shared()) | ||
| 506 | + | ||
| 507 | + def test_share_memory_cpu_idempotent(self): | ||
| 508 | + sm = _make_cpu_linear() | ||
| 509 | + sm.share_memory() | ||
| 510 | + sm.share_memory() | ||
| 511 | + self.assertTrue(sm.linear.weight.untyped_storage().is_shared()) | ||
| 512 | + | ||
| 513 | + def test_share_memory_on_npu_raises(self): | ||
| 514 | + sm = _make_linear() | ||
| 515 | + with self.assertRaisesRegex( | ||
| 516 | + RuntimeError, r"share_memory.*not supported in npu"): | ||
| 517 | + sm.share_memory() | ||
| 518 | + | ||
| 519 | + | ||
| 520 | +class TestScriptModuleMetadata(TestCase): | ||
| 521 | + """register_module/register_parameter on NPU: | ||
| 522 | + torch-npu intercepts with RuntimeError. | ||
| 523 | + On CPU they also raise RuntimeError (PyTorch limitation: | ||
| 524 | + "Cannot re-assign modules" / "Can't add a new parameter | ||
| 525 | + after ScriptModule construction").""" | ||
| 526 | + | ||
| 527 | + def test_register_module_raises_on_npu(self): | ||
| 528 | + sm = _make_linear() | ||
| 529 | + sub = nn.Linear(2, 2).to(device_type) | ||
| 530 | + with self.assertRaisesRegex( | ||
| 531 | + RuntimeError, r"register_module.*not supported in npu"): | ||
| 532 | + sm.register_module("new_sub", sub) | ||
| 533 | + | ||
| 534 | + def test_register_parameter_raises_on_npu(self): | ||
| 535 | + sm = _make_linear() | ||
| 536 | + param = nn.Parameter(torch.randn(2, 2)).to(device_type) | ||
| 537 | + with self.assertRaisesRegex( | ||
| 538 | + RuntimeError, r"register_parameter.*not supported in npu"): | ||
| 539 | + sm.register_parameter("new_param", param) | ||
| 540 | + | ||
| 541 | + def test_set_submodule_raises(self): | ||
| 542 | + sm = _make_linear() | ||
| 543 | + new_sub = nn.Linear(2, 2).to(device_type) | ||
| 544 | + with self.assertRaisesRegex( | ||
| 545 | + RuntimeError, r"not supported on ScriptModules"): | ||
| 546 | + sm.set_submodule("linear", new_sub) | ||
| 547 | + | ||
| 548 | + def test_set_submodule_nested_raises(self): | ||
| 549 | + sm = _make_nested() | ||
| 550 | + new_sub = nn.Linear(2, 2).to(device_type) | ||
| 551 | + with self.assertRaisesRegex( | ||
| 552 | + RuntimeError, r"not supported on ScriptModules"): | ||
| 553 | + sm.set_submodule("sub.linear", new_sub) | ||
| 554 | + | ||
| 555 | + def test_get_buffer_unsupported(self): | ||
| 556 | + sm = _make_with_buffer() | ||
| 557 | + with self.assertRaisesRegex( | ||
| 558 | + RuntimeError, | ||
| 559 | + r"get_buffer is not supported on ScriptModules"): | ||
| 560 | + sm.get_buffer("buf") | ||
| 561 | + | ||
| 562 | + def test_get_buffer_unsupported_on_nested(self): | ||
| 563 | + sm = _make_nested_with_buffer() | ||
| 564 | + with self.assertRaisesRegex( | ||
| 565 | + RuntimeError, | ||
| 566 | + r"get_buffer is not supported on ScriptModules"): | ||
| 567 | + sm.get_buffer("sub.buf") | ||
| 568 | + | ||
| 569 | + def test_get_buffer_unsupported_nonexistent(self): | ||
| 570 | + sm = _make_linear() | ||
| 571 | + with self.assertRaisesRegex( | ||
| 572 | + RuntimeError, | ||
| 573 | + r"get_buffer is not supported on ScriptModules"): | ||
| 574 | + sm.get_buffer("nonexistent") | ||
| 575 | + | ||
| 576 | + | ||
| 577 | +class TestScriptModuleUnsupported(TestCase): | ||
| 578 | + """APIs that raise errors by PyTorch design, not torch-npu.""" | ||
| 579 | + | ||
| 580 | + def test_requires_grad_unsupported(self): | ||
| 581 | + sm = _make_linear() | ||
| 582 | + with self.assertRaisesRegex( | ||
| 583 | + RuntimeError, | ||
| 584 | + r"requires_grad_ is not supported on ScriptModules"): | ||
| 585 | + sm.requires_grad_(True) | ||
| 586 | + | ||
| 587 | + def test_to_empty_unsupported(self): | ||
| 588 | + sm = _make_linear() | ||
| 589 | + with self.assertRaisesRegex( | ||
| 590 | + RuntimeError, | ||
| 591 | + r"to_empty is not supported on ScriptModules"): | ||
| 592 | + sm.to_empty(device=device_type) | ||
| 593 | + | ||
| 594 | + def test_xpu_unsupported(self): | ||
| 595 | + sm = _make_linear() | ||
| 596 | + with self.assertRaisesRegex( | ||
| 597 | + RuntimeError, | ||
| 598 | + r"xpu is not supported on ScriptModules"): | ||
| 599 | + sm.xpu() | ||
| 600 | + | ||
| 601 | + def test_set_extra_state_raises(self): | ||
| 602 | + sm = _make_linear() | ||
| 603 | + with self.assertRaisesRegex( | ||
| 604 | + RuntimeError, r"should never be called"): | ||
| 605 | + sm.set_extra_state({"version": 1}) | ||
| 606 | + | ||
| 607 | + | ||
| 608 | +if __name__ == "__main__": | ||
| 609 | + run_tests() | ||