Coverage for cuda/core/_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# CUDA Toolkit v13.1.0

10RUNTIME_CUDA_ERROR_EXPLANATIONS = { (empty)

11 0: (

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

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

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

15 ),

16 1: (

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

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

19 ),

20 2: (

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

22 " other resources to perform the requested operation."

23 ),

24 3: ("The API call failed because the CUDA driver and runtime could not be initialized."),

25 4: (

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

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

28 " CUDA driver has been unloaded."

29 ),

30 5: (

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

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

33 " like visual profiler."

34 ),

35 6: (

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

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

38 " ::cudaProfilerStop without initialization."

39 ),

40 7: (

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

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

43 ),

44 8: (

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

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

47 ),

48 9: (

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

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

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

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

53 " device limitations."

54 ),

55 12: (

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

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

58 ),

59 13: ("This indicates that the symbol name/identifier passed to the API call is not a valid name or identifier."),

60 16: (

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

62 " not a valid host pointer."

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

64 ),

65 17: (

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

67 " not a valid device pointer."

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

69 ),

70 18: ("This indicates that the texture passed to the API call is not a valid texture."),

71 19: (

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

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

74 ),

75 20: (

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

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

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

79 ),

80 21: (

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

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

83 ),

84 22: (

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

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

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

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

89 " ::cudaGetSymbolAddress()."

90 ),

91 23: (

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

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

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

95 " removed with the CUDA 3.1 release."

96 ),

97 24: (

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

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

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

101 " removed with the CUDA 3.1 release."

102 ),

103 25: (

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

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

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

107 " removed with the CUDA 3.1 release."

108 ),

109 26: (

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

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

112 ),

113 27: (

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

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

116 ),

117 28: (

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

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

120 " removed with the CUDA 3.1 release."

121 ),

122 31: (

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

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

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

126 ),

127 32: (

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

129 " range."

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

131 " removed with the CUDA 3.1 release."

132 ),

133 34: (

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

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

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

137 ),

138 35: (

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

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

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

142 ),

143 36: (

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

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

146 " to allow the API call to succeed."

147 ),

148 37: ("This indicates that the surface passed to the API call is not a valid surface."),

149 43: (

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

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

152 ),

153 44: (

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

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

156 ),

157 45: (

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

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

160 ),

161 46: (

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

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

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

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

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

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

168 ),

169 49: (

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

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

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

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

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

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

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

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

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

179 ),

180 52: (

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

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

183 ),

184 53: (

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

186 " used for device emulation of kernel launches."

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

188 " removed with the CUDA 3.1 release."

189 ),

190 65: (

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

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

193 " number of nested grid launches."

194 ),

195 66: (

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

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

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

199 " the Texture Object API's."

200 ),

201 67: (

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

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

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

205 " the Surface Object API's."

206 ),

207 68: (

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

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

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

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

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

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

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

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

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

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

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

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

220 ),

221 69: (

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

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

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

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

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

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

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

229 " cannot be used for user allocations."

230 ),

231 98: ("The requested device function does not exist or is not compiled for the proper device architecture."),

232 100: ("This indicates that no CUDA-capable devices were detected by the installed CUDA driver."),

233 101: (

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

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

236 " invalid for the specified device."

237 ),

238 102: "This indicates that the device doesn't have a valid Grid License.",

239 103: (

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

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

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

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

244 " or the driver could not be established."

245 ),

246 127: "This indicates an internal startup failure in the CUDA runtime.",

247 200: "This indicates that the device kernel image is invalid.",

248 201: (

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

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

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

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

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

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

255 ),

256 205: "This indicates that the buffer object could not be mapped.",

257 206: "This indicates that the buffer object could not be unmapped.",

258 207: ("This indicates that the specified array is currently mapped and thus cannot be destroyed."),

259 208: "This indicates that the resource is already mapped.",

260 209: (

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

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

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

264 " corresponding device configuration."

265 ),

266 210: "This indicates that a resource has already been acquired.",

267 211: "This indicates that a resource is not mapped.",

268 212: ("This indicates that a mapped resource is not available for access as an array."),

269 213: ("This indicates that a mapped resource is not available for access as a pointer."),

270 214: ("This indicates that an uncorrectable ECC error was detected during execution."),

271 215: ("This indicates that the ::cudaLimit passed to the API call is not supported by the active device."),

272 216: (

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

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

275 ),

276 217: ("This error indicates that P2P access is not supported across the given devices."),

277 218: (

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

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

280 ),

281 219: "This indicates an error with the OpenGL or DirectX context.",

282 220: ("This indicates that an uncorrectable NVLink error was detected during the execution."),

283 221: (

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

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

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

287 ),

288 222: (

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

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

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

292 ),

293 223: (

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

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

296 " a suitable binary for the current device."

297 ),

298 224: "This indicates that the provided execution affinity is not supported by the device.",

299 225: (

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

301 ),

302 226: (

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

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

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

306 " b. Certain classes of hardware errors"

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

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

309 " be terminated and relaunched."

310 ),

311 300: "This indicates that the device kernel source is invalid.",

312 301: "This indicates that the file specified was not found.",

313 302: "This indicates that a link to a shared object failed to resolve.",

314 303: "This indicates that initialization of a shared object failed.",

315 304: "This error indicates that an OS call failed.",

316 400: (

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

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

319 " ::cudaEvent_t."

320 ),

321 401: (

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

323 " valid state to perform the requested operation."

324 ),

325 402: (

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

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

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

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

330 ),

331 500: (

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

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

334 " and surface names."

335 ),

336 600: (

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

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

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

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

341 ),

342 700: (

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

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

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

346 " and relaunched."

347 ),

348 701: (

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

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

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

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

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

354 ),

355 702: (

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

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

358 ' ::cudaDeviceAttr::cudaDevAttrKernelExecTimeout "cudaDevAttrKernelExecTimeout"'

359 " for more information."

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

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

362 " and relaunched."

363 ),

364 703: ("This error indicates a kernel launch that uses an incompatible texturing mode."),

365 704: (

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

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

368 " had peer addressing enabled."

369 ),

370 705: (

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

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

373 " ::cudaDeviceEnablePeerAccess()."

374 ),

375 708: (

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

377 " ::cudaSetDeviceFlags(), ::cudaD3D9SetDirect3DDevice(),"

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

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

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

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

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

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

384 " host thread."

385 ),

386 709: (

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

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

389 " has not yet been initialized."

390 ),

391 710: (

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

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

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

395 ),

396 711: (

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

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

399 " passed to ::cudaEnablePeerAccess()."

400 ),

401 712: ("This error indicates that the memory range passed to ::cudaHostRegister() has already been registered."),

402 713: (

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

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

405 ),

406 714: (

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

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

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

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

411 " and relaunched."

412 ),

413 715: (

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

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

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

417 " and relaunched."

418 ),

419 716: (

420 "The device encountered a load or store instruction"

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

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

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

424 " and relaunched."

425 ),

426 717: (

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

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

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

430 " belonging to an allowed address space."

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

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

433 " and relaunched."

434 ),

435 718: (

436 "The device encountered an invalid program counter."

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

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

439 " and relaunched."

440 ),

441 719: (

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

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

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

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

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

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

448 " and relaunched."

449 ),

450 720: (

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

452 " launched via either ::cudaLaunchCooperativeKernel"

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

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

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

456 ),

457 721: (

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

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

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

461 " process must be terminated and relaunched."

462 ),

463 800: "This error indicates the attempted operation is not permitted.",

464 801: ("This error indicates the attempted operation is not supported on the current system or device."),

465 802: (

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

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

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

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

470 " user guide."

471 ),

472 803: (

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

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

475 " for supported versions."

476 ),

477 804: (

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

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

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

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

482 " environment variable."

483 ),

484 805: "This error indicates that the MPS client failed to connect to the MPS control daemon or the MPS server.",

485 806: "This error indicates that the remote procedural call between the MPS server and the MPS client failed.",

486 807: (

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

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

489 ),

490 808: "This error indicates that the hardware resources required to create MPS client have been exhausted.",

491 809: "This error indicates the the hardware resources required to device connections have been exhausted.",

492 810: "This error indicates that the MPS client has been terminated by the server. To continue using CUDA, the process must be terminated and relaunched.",

493 811: "This error indicates, that the program is using CUDA Dynamic Parallelism, but the current configuration, like MPS, does not support it.",

494 812: "This error indicates, that the program contains an unsupported interaction between different versions of CUDA Dynamic Parallelism.",

495 900: "The operation is not permitted when the stream is capturing.",

496 901: ("The current capture sequence on the stream has been invalidated due to a previous error."),

497 902: ("The operation would have resulted in a merge of two independent capture sequences."),

498 903: "The capture was not initiated in this stream.",

499 904: ("The capture sequence contains a fork that was not joined to the primary stream."),

500 905: (

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

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

503 " cross the boundary."

504 ),

505 906: (

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

507 " a current capture sequence from cudaStreamLegacy."

508 ),

509 907: ("The operation is not permitted on an event which was last recorded in a capturing stream."),

510 908: (

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

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

513 " different thread."

514 ),

515 909: "This indicates that the wait operation has timed out.",

516 910: (

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

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

519 ),

520 911: (

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

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

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

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

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

526 " terminated and relaunched."

527 ),

528 912: ("This indicates that a kernel launch error has occurred due to cluster misconfiguration."),

529 913: ("Indiciates a function handle is not loaded when calling an API that requires a loaded function."),

530 914: ("This error indicates one or more resources passed in are not valid resource types for the operation."),

531 915: ("This error indicates one or more resources are insufficient or non-applicable for the operation."),

532 917: (

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

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

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

536 ),

537 999: "This indicates that an unknown internal error has occurred.",

538 10000: (

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

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

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

542 ),

543}

Coverage for cuda / core / _utils / runtime_cuda_error_explanations.py: 100.00%

1 statements