Coverage for cuda/core/experimental/_utils/runtime_cuda_error

2# SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE

4# To regenerate the dictionary below run:

5# ../../../../../toolshed/reformat_cuda_enums_as_py.py /usr/local/cuda/include/driver_types.h

6# Replace the dictionary below with the output.

7# Also update the CUDA Toolkit version number below.

9# ruff: noqa: E501

10# CUDA Toolkit v13.1.0

11RUNTIME_CUDA_ERROR_EXPLANATIONS = {

12 0: (

13 "The API call returned with no errors. In the case of query calls, this"

14 " also means that the operation being queried is complete (see"

15 " ::cudaEventQuery() and ::cudaStreamQuery())."

16 ),

17 1: (

18 "This indicates that one or more of the parameters passed to the API call"

19 " is not within an acceptable range of values."

20 ),

21 2: (

22 "The API call failed because it was unable to allocate enough memory or"

23 " other resources to perform the requested operation."

24 ),

25 3: ("The API call failed because the CUDA driver and runtime could not be initialized."),

26 4: (

27 "This indicates that a CUDA Runtime API call cannot be executed because"

28 " it is being called during process shut down, at a point in time after"

29 " CUDA driver has been unloaded."

30 ),

31 5: (

32 "This indicates profiler is not initialized for this run. This can"

33 " happen when the application is running with external profiling tools"

34 " like visual profiler."

35 ),

36 6: (

37 "This error return is deprecated as of CUDA 5.0. It is no longer an error"

38 " to attempt to enable/disable the profiling via ::cudaProfilerStart or"

39 " ::cudaProfilerStop without initialization."

40 ),

41 7: (

42 "This error return is deprecated as of CUDA 5.0. It is no longer an error"

43 " to call cudaProfilerStart() when profiling is already enabled."

44 ),

45 8: (

46 "This error return is deprecated as of CUDA 5.0. It is no longer an error"

47 " to call cudaProfilerStop() when profiling is already disabled."

48 ),

49 9: (

50 "This indicates that a kernel launch is requesting resources that can"

51 " never be satisfied by the current device. Requesting more shared memory"

52 " per block than the device supports will trigger this error, as will"

53 " requesting too many threads or blocks. See ::cudaDeviceProp for more"

54 " device limitations."

55 ),

56 12: (

57 "This indicates that one or more of the pitch-related parameters passed"

58 " to the API call is not within the acceptable range for pitch."

59 ),

60 13: ("This indicates that the symbol name/identifier passed to the API call is not a valid name or identifier."),

61 16: (

62 "This indicates that at least one host pointer passed to the API call is"

63 " not a valid host pointer."

64 " This error return is deprecated as of CUDA 10.1."

65 ),

66 17: (

67 "This indicates that at least one device pointer passed to the API call is"

68 " not a valid device pointer."

69 " This error return is deprecated as of CUDA 10.1."

70 ),

71 18: ("This indicates that the texture passed to the API call is not a valid texture."),

72 19: (

73 "This indicates that the texture binding is not valid. This occurs if you"

74 " call ::cudaGetTextureAlignmentOffset() with an unbound texture."

75 ),

76 20: (

77 "This indicates that the channel descriptor passed to the API call is not"

78 " valid. This occurs if the format is not one of the formats specified by"

79 " ::cudaChannelFormatKind, or if one of the dimensions is invalid."

80 ),

81 21: (

82 "This indicates that the direction of the memcpy passed to the API call is"

83 " not one of the types specified by ::cudaMemcpyKind."

84 ),

85 22: (

86 "This indicated that the user has taken the address of a constant variable,"

87 " which was forbidden up until the CUDA 3.1 release."

88 " This error return is deprecated as of CUDA 3.1. Variables in constant"

89 " memory may now have their address taken by the runtime via"

90 " ::cudaGetSymbolAddress()."

91 ),

92 23: (

93 "This indicated that a texture fetch was not able to be performed."

94 " This was previously used for device emulation of texture operations."

95 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

96 " removed with the CUDA 3.1 release."

97 ),

98 24: (

99 "This indicated that a texture was not bound for access."

100 " This was previously used for device emulation of texture operations."

101 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

102 " removed with the CUDA 3.1 release."

103 ),

104 25: (

105 "This indicated that a synchronization operation had failed."

106 " This was previously used for some device emulation functions."

107 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

108 " removed with the CUDA 3.1 release."

109 ),

110 26: (

111 "This indicates that a non-float texture was being accessed with linear"

112 " filtering. This is not supported by CUDA."

113 ),

114 27: (

115 "This indicates that an attempt was made to read an unsupported data type as a"

116 " normalized float. This is not supported by CUDA."

117 ),

118 28: (

119 "Mixing of device and device emulation code was not allowed."

120 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

121 " removed with the CUDA 3.1 release."

122 ),

123 31: (

124 "This indicates that the API call is not yet implemented. Production"

125 " releases of CUDA will never return this error."

126 " This error return is deprecated as of CUDA 4.1."

127 ),

128 32: (

129 "This indicated that an emulated device pointer exceeded the 32-bit address"

130 " range."

131 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

132 " removed with the CUDA 3.1 release."

133 ),

134 34: (

135 "This indicates that the CUDA driver that the application has loaded is a"

136 " stub library. Applications that run with the stub rather than a real"

137 " driver loaded will result in CUDA API returning this error."

138 ),

139 35: (

140 "This indicates that the installed NVIDIA CUDA driver is older than the"

141 " CUDA runtime library. This is not a supported configuration. Users should"

142 " install an updated NVIDIA display driver to allow the application to run."

143 ),

144 36: (

145 "This indicates that the API call requires a newer CUDA driver than the one"

146 " currently installed. Users should install an updated NVIDIA CUDA driver"

147 " to allow the API call to succeed."

148 ),

149 37: ("This indicates that the surface passed to the API call is not a valid surface."),

150 43: (

151 "This indicates that multiple global or constant variables (across separate"

152 " CUDA source files in the application) share the same string name."

153 ),

154 44: (

155 "This indicates that multiple textures (across separate CUDA source"

156 " files in the application) share the same string name."

157 ),

158 45: (

159 "This indicates that multiple surfaces (across separate CUDA source"

160 " files in the application) share the same string name."

161 ),

162 46: (

163 "This indicates that all CUDA devices are busy or unavailable at the current"

164 " time. Devices are often busy/unavailable due to use of"

165 " ::cudaComputeModeProhibited, ::cudaComputeModeExclusiveProcess, or when long"

166 " running CUDA kernels have filled up the GPU and are blocking new work"

167 " from starting. They can also be unavailable due to memory constraints"

168 " on a device that already has active CUDA work being performed."

169 ),

170 49: (

171 "This indicates that the current context is not compatible with this"

172 " the CUDA Runtime. This can only occur if you are using CUDA"

173 " Runtime/Driver interoperability and have created an existing Driver"

174 " context using the driver API. The Driver context may be incompatible"

175 " either because the Driver context was created using an older version"

176 " of the API, because the Runtime API call expects a primary driver"

177 " context and the Driver context is not primary, or because the Driver"

178 ' context has been destroyed. Please see CUDART_DRIVER "Interactions'

179 ' with the CUDA Driver API" for more information.'

180 ),

181 52: (

182 "The device function being invoked (usually via ::cudaLaunchKernel()) was not"

183 " previously configured via the ::cudaConfigureCall() function."

184 ),

185 53: (

186 "This indicated that a previous kernel launch failed. This was previously"

187 " used for device emulation of kernel launches."

188 " This error return is deprecated as of CUDA 3.1. Device emulation mode was"

189 " removed with the CUDA 3.1 release."

190 ),

191 65: (

192 "This error indicates that a device runtime grid launch did not occur"

193 " because the depth of the child grid would exceed the maximum supported"

194 " number of nested grid launches."

195 ),

196 66: (

197 "This error indicates that a grid launch did not occur because the kernel"

198 " uses file-scoped textures which are unsupported by the device runtime."

199 " Kernels launched via the device runtime only support textures created with"

200 " the Texture Object API's."

201 ),

202 67: (

203 "This error indicates that a grid launch did not occur because the kernel"

204 " uses file-scoped surfaces which are unsupported by the device runtime."

205 " Kernels launched via the device runtime only support surfaces created with"

206 " the Surface Object API's."

207 ),

208 68: (

209 "This error indicates that a call to ::cudaDeviceSynchronize made from"

210 " the device runtime failed because the call was made at grid depth greater"

211 " than than either the default (2 levels of grids) or user specified device"

212 " limit ::cudaLimitDevRuntimeSyncDepth. To be able to synchronize on"

213 " launched grids at a greater depth successfully, the maximum nested"

214 " depth at which ::cudaDeviceSynchronize will be called must be specified"

215 " with the ::cudaLimitDevRuntimeSyncDepth limit to the ::cudaDeviceSetLimit"

216 " api before the host-side launch of a kernel using the device runtime."

217 " Keep in mind that additional levels of sync depth require the runtime"

218 " to reserve large amounts of device memory that cannot be used for"

219 " user allocations. Note that ::cudaDeviceSynchronize made from device"

220 " runtime is only supported on devices of compute capability < 9.0."

221 ),

222 69: (

223 "This error indicates that a device runtime grid launch failed because"

224 " the launch would exceed the limit ::cudaLimitDevRuntimePendingLaunchCount."

225 " For this launch to proceed successfully, ::cudaDeviceSetLimit must be"

226 " called to set the ::cudaLimitDevRuntimePendingLaunchCount to be higher"

227 " than the upper bound of outstanding launches that can be issued to the"

228 " device runtime. Keep in mind that raising the limit of pending device"

229 " runtime launches will require the runtime to reserve device memory that"

230 " cannot be used for user allocations."

231 ),

232 98: ("The requested device function does not exist or is not compiled for the proper device architecture."),

233 100: ("This indicates that no CUDA-capable devices were detected by the installed CUDA driver."),

234 101: (

235 "This indicates that the device ordinal supplied by the user does not"

236 " correspond to a valid CUDA device or that the action requested is"

237 " invalid for the specified device."

238 ),

239 102: "This indicates that the device doesn't have a valid Grid License.",

240 103: (

241 "By default, the CUDA runtime may perform a minimal set of self-tests,"

242 " as well as CUDA driver tests, to establish the validity of both."

243 " Introduced in CUDA 11.2, this error return indicates that at least one"

244 " of these tests has failed and the validity of either the runtime"

245 " or the driver could not be established."

246 ),

247 127: "This indicates an internal startup failure in the CUDA runtime.",

248 200: "This indicates that the device kernel image is invalid.",

249 201: (

250 "This most frequently indicates that there is no context bound to the"

251 " current thread. This can also be returned if the context passed to an"

252 " API call is not a valid handle (such as a context that has had"

253 " ::cuCtxDestroy() invoked on it). This can also be returned if a user"

254 " mixes different API versions (i.e. 3010 context with 3020 API calls)."

255 " See ::cuCtxGetApiVersion() for more details."

256 ),

257 205: "This indicates that the buffer object could not be mapped.",

258 206: "This indicates that the buffer object could not be unmapped.",

259 207: ("This indicates that the specified array is currently mapped and thus cannot be destroyed."),

260 208: "This indicates that the resource is already mapped.",

261 209: (

262 "This indicates that there is no kernel image available that is suitable"

263 " for the device. This can occur when a user specifies code generation"

264 " options for a particular CUDA source file that do not include the"

265 " corresponding device configuration."

266 ),

267 210: "This indicates that a resource has already been acquired.",

268 211: "This indicates that a resource is not mapped.",

269 212: ("This indicates that a mapped resource is not available for access as an array."),

270 213: ("This indicates that a mapped resource is not available for access as a pointer."),

271 214: ("This indicates that an uncorrectable ECC error was detected during execution."),

272 215: ("This indicates that the ::cudaLimit passed to the API call is not supported by the active device."),

273 216: (

274 "This indicates that a call tried to access an exclusive-thread device that"

275 " is already in use by a different thread."

276 ),

277 217: ("This error indicates that P2P access is not supported across the given devices."),

278 218: (

279 "A PTX compilation failed. The runtime may fall back to compiling PTX if"

280 " an application does not contain a suitable binary for the current device."

281 ),

282 219: "This indicates an error with the OpenGL or DirectX context.",

283 220: ("This indicates that an uncorrectable NVLink error was detected during the execution."),

284 221: (

285 "This indicates that the PTX JIT compiler library was not found. The JIT Compiler"

286 " library is used for PTX compilation. The runtime may fall back to compiling PTX"

287 " if an application does not contain a suitable binary for the current device."

288 ),

289 222: (

290 "This indicates that the provided PTX was compiled with an unsupported toolchain."

291 " The most common reason for this, is the PTX was generated by a compiler newer"

292 " than what is supported by the CUDA driver and PTX JIT compiler."

293 ),

294 223: (

295 "This indicates that the JIT compilation was disabled. The JIT compilation compiles"

296 " PTX. The runtime may fall back to compiling PTX if an application does not contain"

297 " a suitable binary for the current device."

298 ),

299 224: "This indicates that the provided execution affinity is not supported by the device.",

300 225: (

301 "This indicates that the code to be compiled by the PTX JIT contains unsupported call to cudaDeviceSynchronize."

302 ),

303 226: (

304 "This indicates that an exception occurred on the device that is now"

305 " contained by the GPU's error containment capability. Common causes are -"

306 " a. Certain types of invalid accesses of peer GPU memory over nvlink"

307 " b. Certain classes of hardware errors"

308 " This leaves the process in an inconsistent state and any further CUDA"

309 " work will return the same error. To continue using CUDA, the process must"

310 " be terminated and relaunched."

311 ),

312 300: "This indicates that the device kernel source is invalid.",

313 301: "This indicates that the file specified was not found.",

314 302: "This indicates that a link to a shared object failed to resolve.",

315 303: "This indicates that initialization of a shared object failed.",

316 304: "This error indicates that an OS call failed.",

317 400: (

318 "This indicates that a resource handle passed to the API call was not"

319 " valid. Resource handles are opaque types like ::cudaStream_t and"

320 " ::cudaEvent_t."

321 ),

322 401: (

323 "This indicates that a resource required by the API call is not in a"

324 " valid state to perform the requested operation."

325 ),

326 402: (

327 "This indicates an attempt was made to introspect an object in a way that"

328 " would discard semantically important information. This is either due to"

329 " the object using funtionality newer than the API version used to"

330 " introspect it or omission of optional return arguments."

331 ),

332 500: (

333 "This indicates that a named symbol was not found. Examples of symbols"

334 " are global/constant variable names, driver function names, texture names,"

335 " and surface names."

336 ),

337 600: (

338 "This indicates that asynchronous operations issued previously have not"

339 " completed yet. This result is not actually an error, but must be indicated"

340 " differently than ::cudaSuccess (which indicates completion). Calls that"

341 " may return this value include ::cudaEventQuery() and ::cudaStreamQuery()."

342 ),

343 700: (

344 "The device encountered a load or store instruction on an invalid memory address."

345 " This leaves the process in an inconsistent state and any further CUDA work"

346 " will return the same error. To continue using CUDA, the process must be terminated"

347 " and relaunched."

348 ),

349 701: (

350 "This indicates that a launch did not occur because it did not have"

351 " appropriate resources. Although this error is similar to"

352 " ::cudaErrorInvalidConfiguration, this error usually indicates that the"

353 " user has attempted to pass too many arguments to the device kernel, or the"

354 " kernel launch specifies too many threads for the kernel's register count."

355 ),

356 702: (

357 "This indicates that the device kernel took too long to execute. This can"

358 " only occur if timeouts are enabled - see the device attribute"

359 ' ::cudaDeviceAttr::cudaDevAttrKernelExecTimeout "cudaDevAttrKernelExecTimeout"'

360 " for more information."

361 " This leaves the process in an inconsistent state and any further CUDA work"

362 " will return the same error. To continue using CUDA, the process must be terminated"

363 " and relaunched."

364 ),

365 703: ("This error indicates a kernel launch that uses an incompatible texturing mode."),

366 704: (

367 "This error indicates that a call to ::cudaDeviceEnablePeerAccess() is"

368 " trying to re-enable peer addressing on from a context which has already"

369 " had peer addressing enabled."

370 ),

371 705: (

372 "This error indicates that ::cudaDeviceDisablePeerAccess() is trying to"

373 " disable peer addressing which has not been enabled yet via"

374 " ::cudaDeviceEnablePeerAccess()."

375 ),

376 708: (

377 "This indicates that the user has called ::cudaSetValidDevices(),"

378 " ::cudaSetDeviceFlags(), ::cudaD3D9SetDirect3DDevice(),"

379 " ::cudaD3D10SetDirect3DDevice, ::cudaD3D11SetDirect3DDevice(), or"

380 " ::cudaVDPAUSetVDPAUDevice() after initializing the CUDA runtime by"

381 " calling non-device management operations (allocating memory and"

382 " launching kernels are examples of non-device management operations)."

383 " This error can also be returned if using runtime/driver"

384 " interoperability and there is an existing ::CUcontext active on the"

385 " host thread."

386 ),

387 709: (

388 "This error indicates that the context current to the calling thread"

389 " has been destroyed using ::cuCtxDestroy, or is a primary context which"

390 " has not yet been initialized."

391 ),

392 710: (

393 "An assert triggered in device code during kernel execution. The device"

394 " cannot be used again. All existing allocations are invalid. To continue"

395 " using CUDA, the process must be terminated and relaunched."

396 ),

397 711: (

398 "This error indicates that the hardware resources required to enable"

399 " peer access have been exhausted for one or more of the devices"

400 " passed to ::cudaEnablePeerAccess()."

401 ),

402 712: ("This error indicates that the memory range passed to ::cudaHostRegister() has already been registered."),

403 713: (

404 "This error indicates that the pointer passed to ::cudaHostUnregister()"

405 " does not correspond to any currently registered memory region."

406 ),

407 714: (

408 "Device encountered an error in the call stack during kernel execution,"

409 " possibly due to stack corruption or exceeding the stack size limit."

410 " This leaves the process in an inconsistent state and any further CUDA work"

411 " will return the same error. To continue using CUDA, the process must be terminated"

412 " and relaunched."

413 ),

414 715: (

415 "The device encountered an illegal instruction during kernel execution"

416 " This leaves the process in an inconsistent state and any further CUDA work"

417 " will return the same error. To continue using CUDA, the process must be terminated"

418 " and relaunched."

419 ),

420 716: (

421 "The device encountered a load or store instruction"

422 " on a memory address which is not aligned."

423 " This leaves the process in an inconsistent state and any further CUDA work"

424 " will return the same error. To continue using CUDA, the process must be terminated"

425 " and relaunched."

426 ),

427 717: (

428 "While executing a kernel, the device encountered an instruction"

429 " which can only operate on memory locations in certain address spaces"

430 " (global, shared, or local), but was supplied a memory address not"

431 " belonging to an allowed address space."

432 " This leaves the process in an inconsistent state and any further CUDA work"

433 " will return the same error. To continue using CUDA, the process must be terminated"

434 " and relaunched."

435 ),

436 718: (

437 "The device encountered an invalid program counter."

438 " This leaves the process in an inconsistent state and any further CUDA work"

439 " will return the same error. To continue using CUDA, the process must be terminated"

440 " and relaunched."

441 ),

442 719: (

443 "An exception occurred on the device while executing a kernel. Common"

444 " causes include dereferencing an invalid device pointer and accessing"

445 " out of bounds shared memory. Less common cases can be system specific - more"

446 " information about these cases can be found in the system specific user guide."

447 " This leaves the process in an inconsistent state and any further CUDA work"

448 " will return the same error. To continue using CUDA, the process must be terminated"

449 " and relaunched."

450 ),

451 720: (

452 "This error indicates that the number of blocks launched per grid for a kernel that was"

453 " launched via either ::cudaLaunchCooperativeKernel"

454 " exceeds the maximum number of blocks as allowed by ::cudaOccupancyMaxActiveBlocksPerMultiprocessor"

455 " or ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags times the number of multiprocessors"

456 " as specified by the device attribute ::cudaDevAttrMultiProcessorCount."

457 ),

458 721: (

459 "An exception occurred on the device while exiting a kernel using tensor memory: the"

460 " tensor memory was not completely deallocated. This leaves the process in an inconsistent"

461 " state and any further CUDA work will return the same error. To continue using CUDA, the"

462 " process must be terminated and relaunched."

463 ),

464 800: "This error indicates the attempted operation is not permitted.",

465 801: ("This error indicates the attempted operation is not supported on the current system or device."),

466 802: (

467 "This error indicates that the system is not yet ready to start any CUDA"

468 " work. To continue using CUDA, verify the system configuration is in a"

469 " valid state and all required driver daemons are actively running."

470 " More information about this error can be found in the system specific"

471 " user guide."

472 ),

473 803: (

474 "This error indicates that there is a mismatch between the versions of"

475 " the display driver and the CUDA driver. Refer to the compatibility documentation"

476 " for supported versions."

477 ),

478 804: (

479 "This error indicates that the system was upgraded to run with forward compatibility"

480 " but the visible hardware detected by CUDA does not support this configuration."

481 " Refer to the compatibility documentation for the supported hardware matrix or ensure"

482 " that only supported hardware is visible during initialization via the CUDA_VISIBLE_DEVICES"

483 " environment variable."

484 ),

485 805: "This error indicates that the MPS client failed to connect to the MPS control daemon or the MPS server.",

486 806: "This error indicates that the remote procedural call between the MPS server and the MPS client failed.",

487 807: (

488 "This error indicates that the MPS server is not ready to accept new MPS client requests."

489 " This error can be returned when the MPS server is in the process of recovering from a fatal failure."

490 ),

491 808: "This error indicates that the hardware resources required to create MPS client have been exhausted.",

492 809: "This error indicates the the hardware resources required to device connections have been exhausted.",

493 810: "This error indicates that the MPS client has been terminated by the server. To continue using CUDA, the process must be terminated and relaunched.",

494 811: "This error indicates, that the program is using CUDA Dynamic Parallelism, but the current configuration, like MPS, does not support it.",

495 812: "This error indicates, that the program contains an unsupported interaction between different versions of CUDA Dynamic Parallelism.",

496 900: "The operation is not permitted when the stream is capturing.",

497 901: ("The current capture sequence on the stream has been invalidated due to a previous error."),

498 902: ("The operation would have resulted in a merge of two independent capture sequences."),

499 903: "The capture was not initiated in this stream.",

500 904: ("The capture sequence contains a fork that was not joined to the primary stream."),

501 905: (

502 "A dependency would have been created which crosses the capture sequence"

503 " boundary. Only implicit in-stream ordering dependencies are allowed to"

504 " cross the boundary."

505 ),

506 906: (

507 "The operation would have resulted in a disallowed implicit dependency on"

508 " a current capture sequence from cudaStreamLegacy."

509 ),

510 907: ("The operation is not permitted on an event which was last recorded in a capturing stream."),

511 908: (

512 "A stream capture sequence not initiated with the ::cudaStreamCaptureModeRelaxed"

513 " argument to ::cudaStreamBeginCapture was passed to ::cudaStreamEndCapture in a"

514 " different thread."

515 ),

516 909: "This indicates that the wait operation has timed out.",

517 910: (

518 "This error indicates that the graph update was not performed because it included"

519 " changes which violated constraints specific to instantiated graph update."

520 ),

521 911: (

522 "This indicates that an async error has occurred in a device outside of CUDA."

523 " If CUDA was waiting for an external device's signal before consuming shared data,"

524 " the external device signaled an error indicating that the data is not valid for"

525 " consumption. This leaves the process in an inconsistent state and any further CUDA"

526 " work will return the same error. To continue using CUDA, the process must be"

527 " terminated and relaunched."

528 ),

529 912: ("This indicates that a kernel launch error has occurred due to cluster misconfiguration."),

530 913: ("Indiciates a function handle is not loaded when calling an API that requires a loaded function."),

531 914: ("This error indicates one or more resources passed in are not valid resource types for the operation."),

532 915: ("This error indicates one or more resources are insufficient or non-applicable for the operation."),

533 917: (

534 "This error indicates that the requested operation is not permitted because the"

535 " stream is in a detached state. This can occur if the green context associated"

536 " with the stream has been destroyed, limiting the stream's operational capabilities."

537 ),

538 999: "This indicates that an unknown internal error has occurred.",

539 10000: (

540 "Any unhandled CUDA driver error is added to this value and returned via"

541 " the runtime. Production releases of CUDA should not return such errors."

542 " This error return is deprecated as of CUDA 4.1."

543 ),

544}

Coverage for cuda / core / experimental / _utils / runtime_cuda_error_explanations.py: 100%

1 statements