# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE

# CUDA Toolkit v13.1.1
_FALLBACK_EXPLANATIONS = {
    0: (
        "The API call returned with no errors. In the case of query calls, this"
        " also means that the operation being queried is complete (see"
        " ::cudaEventQuery() and ::cudaStreamQuery())."
    ),
    1: (
        "This indicates that one or more of the parameters passed to the API call"
        " is not within an acceptable range of values."
    ),
    2: (
        "The API call failed because it was unable to allocate enough memory or"
        " other resources to perform the requested operation."
    ),
    3: ("The API call failed because the CUDA driver and runtime could not be initialized."),
    4: (
        "This indicates that a CUDA Runtime API call cannot be executed because"
        " it is being called during process shut down, at a point in time after"
        " CUDA driver has been unloaded."
    ),
    5: (
        "This indicates profiler is not initialized for this run. This can"
        " happen when the application is running with external profiling tools"
        " like visual profiler."
    ),
    6: (
        "This error return is deprecated as of CUDA 5.0. It is no longer an error"
        " to attempt to enable/disable the profiling via ::cudaProfilerStart or"
        " ::cudaProfilerStop without initialization."
    ),
    7: (
        "This error return is deprecated as of CUDA 5.0. It is no longer an error"
        " to call cudaProfilerStart() when profiling is already enabled."
    ),
    8: (
        "This error return is deprecated as of CUDA 5.0. It is no longer an error"
        " to call cudaProfilerStop() when profiling is already disabled."
    ),
    9: (
        "This indicates that a kernel launch is requesting resources that can"
        " never be satisfied by the current device. Requesting more shared memory"
        " per block than the device supports will trigger this error, as will"
        " requesting too many threads or blocks. See ::cudaDeviceProp for more"
        " device limitations."
    ),
    12: (
        "This indicates that one or more of the pitch-related parameters passed"
        " to the API call is not within the acceptable range for pitch."
    ),
    13: ("This indicates that the symbol name/identifier passed to the API call is not a valid name or identifier."),
    16: (
        "This indicates that at least one host pointer passed to the API call is"
        " not a valid host pointer."
        " This error return is deprecated as of CUDA 10.1."
    ),
    17: (
        "This indicates that at least one device pointer passed to the API call is"
        " not a valid device pointer."
        " This error return is deprecated as of CUDA 10.1."
    ),
    18: ("This indicates that the texture passed to the API call is not a valid texture."),
    19: (
        "This indicates that the texture binding is not valid. This occurs if you"
        " call ::cudaGetTextureAlignmentOffset() with an unbound texture."
    ),
    20: (
        "This indicates that the channel descriptor passed to the API call is not"
        " valid. This occurs if the format is not one of the formats specified by"
        " ::cudaChannelFormatKind, or if one of the dimensions is invalid."
    ),
    21: (
        "This indicates that the direction of the memcpy passed to the API call is"
        " not one of the types specified by ::cudaMemcpyKind."
    ),
    22: (
        "This indicated that the user has taken the address of a constant variable,"
        " which was forbidden up until the CUDA 3.1 release."
        " This error return is deprecated as of CUDA 3.1. Variables in constant"
        " memory may now have their address taken by the runtime via"
        " ::cudaGetSymbolAddress()."
    ),
    23: (
        "This indicated that a texture fetch was not able to be performed."
        " This was previously used for device emulation of texture operations."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    24: (
        "This indicated that a texture was not bound for access."
        " This was previously used for device emulation of texture operations."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    25: (
        "This indicated that a synchronization operation had failed."
        " This was previously used for some device emulation functions."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    26: (
        "This indicates that a non-float texture was being accessed with linear"
        " filtering. This is not supported by CUDA."
    ),
    27: (
        "This indicates that an attempt was made to read an unsupported data type as a"
        " normalized float. This is not supported by CUDA."
    ),
    28: (
        "Mixing of device and device emulation code was not allowed."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    31: (
        "This indicates that the API call is not yet implemented. Production"
        " releases of CUDA will never return this error."
        " This error return is deprecated as of CUDA 4.1."
    ),
    32: (
        "This indicated that an emulated device pointer exceeded the 32-bit address"
        " range."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    34: (
        "This indicates that the CUDA driver that the application has loaded is a"
        " stub library. Applications that run with the stub rather than a real"
        " driver loaded will result in CUDA API returning this error."
    ),
    35: (
        "This indicates that the installed NVIDIA CUDA driver is older than the"
        " CUDA runtime library. This is not a supported configuration. Users should"
        " install an updated NVIDIA display driver to allow the application to run."
    ),
    36: (
        "This indicates that the API call requires a newer CUDA driver than the one"
        " currently installed. Users should install an updated NVIDIA CUDA driver"
        " to allow the API call to succeed."
    ),
    37: ("This indicates that the surface passed to the API call is not a valid surface."),
    43: (
        "This indicates that multiple global or constant variables (across separate"
        " CUDA source files in the application) share the same string name."
    ),
    44: (
        "This indicates that multiple textures (across separate CUDA source"
        " files in the application) share the same string name."
    ),
    45: (
        "This indicates that multiple surfaces (across separate CUDA source"
        " files in the application) share the same string name."
    ),
    46: (
        "This indicates that all CUDA devices are busy or unavailable at the current"
        " time. Devices are often busy/unavailable due to use of"
        " ::cudaComputeModeProhibited, ::cudaComputeModeExclusiveProcess, or when long"
        " running CUDA kernels have filled up the GPU and are blocking new work"
        " from starting. They can also be unavailable due to memory constraints"
        " on a device that already has active CUDA work being performed."
    ),
    49: (
        "This indicates that the current context is not compatible with this"
        " the CUDA Runtime. This can only occur if you are using CUDA"
        " Runtime/Driver interoperability and have created an existing Driver"
        " context using the driver API. The Driver context may be incompatible"
        " either because the Driver context was created using an older version"
        " of the API, because the Runtime API call expects a primary driver"
        " context and the Driver context is not primary, or because the Driver"
        ' context has been destroyed. Please see CUDART_DRIVER "Interactions'
        ' with the CUDA Driver API" for more information.'
    ),
    52: (
        "The device function being invoked (usually via ::cudaLaunchKernel()) was not"
        " previously configured via the ::cudaConfigureCall() function."
    ),
    53: (
        "This indicated that a previous kernel launch failed. This was previously"
        " used for device emulation of kernel launches."
        " This error return is deprecated as of CUDA 3.1. Device emulation mode was"
        " removed with the CUDA 3.1 release."
    ),
    65: (
        "This error indicates that a device runtime grid launch did not occur"
        " because the depth of the child grid would exceed the maximum supported"
        " number of nested grid launches."
    ),
    66: (
        "This error indicates that a grid launch did not occur because the kernel"
        " uses file-scoped textures which are unsupported by the device runtime."
        " Kernels launched via the device runtime only support textures created with"
        " the Texture Object API's."
    ),
    67: (
        "This error indicates that a grid launch did not occur because the kernel"
        " uses file-scoped surfaces which are unsupported by the device runtime."
        " Kernels launched via the device runtime only support surfaces created with"
        " the Surface Object API's."
    ),
    68: (
        "This error indicates that a call to ::cudaDeviceSynchronize made from"
        " the device runtime failed because the call was made at grid depth greater"
        " than than either the default (2 levels of grids) or user specified device"
        " limit ::cudaLimitDevRuntimeSyncDepth. To be able to synchronize on"
        " launched grids at a greater depth successfully, the maximum nested"
        " depth at which ::cudaDeviceSynchronize will be called must be specified"
        " with the ::cudaLimitDevRuntimeSyncDepth limit to the ::cudaDeviceSetLimit"
        " api before the host-side launch of a kernel using the device runtime."
        " Keep in mind that additional levels of sync depth require the runtime"
        " to reserve large amounts of device memory that cannot be used for"
        " user allocations. Note that ::cudaDeviceSynchronize made from device"
        " runtime is only supported on devices of compute capability < 9.0."
    ),
    69: (
        "This error indicates that a device runtime grid launch failed because"
        " the launch would exceed the limit ::cudaLimitDevRuntimePendingLaunchCount."
        " For this launch to proceed successfully, ::cudaDeviceSetLimit must be"
        " called to set the ::cudaLimitDevRuntimePendingLaunchCount to be higher"
        " than the upper bound of outstanding launches that can be issued to the"
        " device runtime. Keep in mind that raising the limit of pending device"
        " runtime launches will require the runtime to reserve device memory that"
        " cannot be used for user allocations."
    ),
    98: ("The requested device function does not exist or is not compiled for the proper device architecture."),
    100: ("This indicates that no CUDA-capable devices were detected by the installed CUDA driver."),
    101: (
        "This indicates that the device ordinal supplied by the user does not"
        " correspond to a valid CUDA device or that the action requested is"
        " invalid for the specified device."
    ),
    102: "This indicates that the device doesn't have a valid Grid License.",
    103: (
        "By default, the CUDA runtime may perform a minimal set of self-tests,"
        " as well as CUDA driver tests, to establish the validity of both."
        " Introduced in CUDA 11.2, this error return indicates that at least one"
        " of these tests has failed and the validity of either the runtime"
        " or the driver could not be established."
    ),
    127: "This indicates an internal startup failure in the CUDA runtime.",
    200: "This indicates that the device kernel image is invalid.",
    201: (
        "This most frequently indicates that there is no context bound to the"
        " current thread. This can also be returned if the context passed to an"
        " API call is not a valid handle (such as a context that has had"
        " ::cuCtxDestroy() invoked on it). This can also be returned if a user"
        " mixes different API versions (i.e. 3010 context with 3020 API calls)."
        " See ::cuCtxGetApiVersion() for more details."
    ),
    205: "This indicates that the buffer object could not be mapped.",
    206: "This indicates that the buffer object could not be unmapped.",
    207: ("This indicates that the specified array is currently mapped and thus cannot be destroyed."),
    208: "This indicates that the resource is already mapped.",
    209: (
        "This indicates that there is no kernel image available that is suitable"
        " for the device. This can occur when a user specifies code generation"
        " options for a particular CUDA source file that do not include the"
        " corresponding device configuration."
    ),
    210: "This indicates that a resource has already been acquired.",
    211: "This indicates that a resource is not mapped.",
    212: ("This indicates that a mapped resource is not available for access as an array."),
    213: ("This indicates that a mapped resource is not available for access as a pointer."),
    214: ("This indicates that an uncorrectable ECC error was detected during execution."),
    215: ("This indicates that the ::cudaLimit passed to the API call is not supported by the active device."),
    216: (
        "This indicates that a call tried to access an exclusive-thread device that"
        " is already in use by a different thread."
    ),
    217: ("This error indicates that P2P access is not supported across the given devices."),
    218: (
        "A PTX compilation failed. The runtime may fall back to compiling PTX if"
        " an application does not contain a suitable binary for the current device."
    ),
    219: "This indicates an error with the OpenGL or DirectX context.",
    220: ("This indicates that an uncorrectable NVLink error was detected during the execution."),
    221: (
        "This indicates that the PTX JIT compiler library was not found. The JIT Compiler"
        " library is used for PTX compilation. The runtime may fall back to compiling PTX"
        " if an application does not contain a suitable binary for the current device."
    ),
    222: (
        "This indicates that the provided PTX was compiled with an unsupported toolchain."
        " The most common reason for this, is the PTX was generated by a compiler newer"
        " than what is supported by the CUDA driver and PTX JIT compiler."
    ),
    223: (
        "This indicates that the JIT compilation was disabled. The JIT compilation compiles"
        " PTX. The runtime may fall back to compiling PTX if an application does not contain"
        " a suitable binary for the current device."
    ),
    224: "This indicates that the provided execution affinity is not supported by the device.",
    225: (
        "This indicates that the code to be compiled by the PTX JIT contains unsupported call to cudaDeviceSynchronize."
    ),
    226: (
        "This indicates that an exception occurred on the device that is now"
        " contained by the GPU's error containment capability. Common causes are -"
        " a. Certain types of invalid accesses of peer GPU memory over nvlink"
        " b. Certain classes of hardware errors"
        " This leaves the process in an inconsistent state and any further CUDA"
        " work will return the same error. To continue using CUDA, the process must"
        " be terminated and relaunched."
    ),
    300: "This indicates that the device kernel source is invalid.",
    301: "This indicates that the file specified was not found.",
    302: "This indicates that a link to a shared object failed to resolve.",
    303: "This indicates that initialization of a shared object failed.",
    304: "This error indicates that an OS call failed.",
    400: (
        "This indicates that a resource handle passed to the API call was not"
        " valid. Resource handles are opaque types like ::cudaStream_t and"
        " ::cudaEvent_t."
    ),
    401: (
        "This indicates that a resource required by the API call is not in a"
        " valid state to perform the requested operation."
    ),
    402: (
        "This indicates an attempt was made to introspect an object in a way that"
        " would discard semantically important information. This is either due to"
        " the object using funtionality newer than the API version used to"
        " introspect it or omission of optional return arguments."
    ),
    500: (
        "This indicates that a named symbol was not found. Examples of symbols"
        " are global/constant variable names, driver function names, texture names,"
        " and surface names."
    ),
    600: (
        "This indicates that asynchronous operations issued previously have not"
        " completed yet. This result is not actually an error, but must be indicated"
        " differently than ::cudaSuccess (which indicates completion). Calls that"
        " may return this value include ::cudaEventQuery() and ::cudaStreamQuery()."
    ),
    700: (
        "The device encountered a load or store instruction on an invalid memory address."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    701: (
        "This indicates that a launch did not occur because it did not have"
        " appropriate resources. Although this error is similar to"
        " ::cudaErrorInvalidConfiguration, this error usually indicates that the"
        " user has attempted to pass too many arguments to the device kernel, or the"
        " kernel launch specifies too many threads for the kernel's register count."
    ),
    702: (
        "This indicates that the device kernel took too long to execute. This can"
        " only occur if timeouts are enabled - see the device attribute"
        ' ::cudaDeviceAttr::cudaDevAttrKernelExecTimeout "cudaDevAttrKernelExecTimeout"'
        " for more information."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    703: ("This error indicates a kernel launch that uses an incompatible texturing mode."),
    704: (
        "This error indicates that a call to ::cudaDeviceEnablePeerAccess() is"
        " trying to re-enable peer addressing on from a context which has already"
        " had peer addressing enabled."
    ),
    705: (
        "This error indicates that ::cudaDeviceDisablePeerAccess() is trying to"
        " disable peer addressing which has not been enabled yet via"
        " ::cudaDeviceEnablePeerAccess()."
    ),
    708: (
        "This indicates that the user has called ::cudaSetValidDevices(),"
        " ::cudaSetDeviceFlags(), ::cudaD3D9SetDirect3DDevice(),"
        " ::cudaD3D10SetDirect3DDevice, ::cudaD3D11SetDirect3DDevice(), or"
        " ::cudaVDPAUSetVDPAUDevice() after initializing the CUDA runtime by"
        " calling non-device management operations (allocating memory and"
        " launching kernels are examples of non-device management operations)."
        " This error can also be returned if using runtime/driver"
        " interoperability and there is an existing ::CUcontext active on the"
        " host thread."
    ),
    709: (
        "This error indicates that the context current to the calling thread"
        " has been destroyed using ::cuCtxDestroy, or is a primary context which"
        " has not yet been initialized."
    ),
    710: (
        "An assert triggered in device code during kernel execution. The device"
        " cannot be used again. All existing allocations are invalid. To continue"
        " using CUDA, the process must be terminated and relaunched."
    ),
    711: (
        "This error indicates that the hardware resources required to enable"
        " peer access have been exhausted for one or more of the devices"
        " passed to ::cudaEnablePeerAccess()."
    ),
    712: ("This error indicates that the memory range passed to ::cudaHostRegister() has already been registered."),
    713: (
        "This error indicates that the pointer passed to ::cudaHostUnregister()"
        " does not correspond to any currently registered memory region."
    ),
    714: (
        "Device encountered an error in the call stack during kernel execution,"
        " possibly due to stack corruption or exceeding the stack size limit."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    715: (
        "The device encountered an illegal instruction during kernel execution"
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    716: (
        "The device encountered a load or store instruction"
        " on a memory address which is not aligned."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    717: (
        "While executing a kernel, the device encountered an instruction"
        " which can only operate on memory locations in certain address spaces"
        " (global, shared, or local), but was supplied a memory address not"
        " belonging to an allowed address space."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    718: (
        "The device encountered an invalid program counter."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    719: (
        "An exception occurred on the device while executing a kernel. Common"
        " causes include dereferencing an invalid device pointer and accessing"
        " out of bounds shared memory. Less common cases can be system specific - more"
        " information about these cases can be found in the system specific user guide."
        " This leaves the process in an inconsistent state and any further CUDA work"
        " will return the same error. To continue using CUDA, the process must be terminated"
        " and relaunched."
    ),
    720: (
        "This error indicates that the number of blocks launched per grid for a kernel that was"
        " launched via either ::cudaLaunchCooperativeKernel"
        " exceeds the maximum number of blocks as allowed by ::cudaOccupancyMaxActiveBlocksPerMultiprocessor"
        " or ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags times the number of multiprocessors"
        " as specified by the device attribute ::cudaDevAttrMultiProcessorCount."
    ),
    721: (
        "An exception occurred on the device while exiting a kernel using tensor memory: the"
        " tensor memory was not completely deallocated. This leaves the process in an inconsistent"
        " state and any further CUDA work will return the same error. To continue using CUDA, the"
        " process must be terminated and relaunched."
    ),
    800: "This error indicates the attempted operation is not permitted.",
    801: ("This error indicates the attempted operation is not supported on the current system or device."),
    802: (
        "This error indicates that the system is not yet ready to start any CUDA"
        " work.  To continue using CUDA, verify the system configuration is in a"
        " valid state and all required driver daemons are actively running."
        " More information about this error can be found in the system specific"
        " user guide."
    ),
    803: (
        "This error indicates that there is a mismatch between the versions of"
        " the display driver and the CUDA driver. Refer to the compatibility documentation"
        " for supported versions."
    ),
    804: (
        "This error indicates that the system was upgraded to run with forward compatibility"
        " but the visible hardware detected by CUDA does not support this configuration."
        " Refer to the compatibility documentation for the supported hardware matrix or ensure"
        " that only supported hardware is visible during initialization via the CUDA_VISIBLE_DEVICES"
        " environment variable."
    ),
    805: "This error indicates that the MPS client failed to connect to the MPS control daemon or the MPS server.",
    806: "This error indicates that the remote procedural call between the MPS server and the MPS client failed.",
    807: (
        "This error indicates that the MPS server is not ready to accept new MPS client requests."
        " This error can be returned when the MPS server is in the process of recovering from a fatal failure."
    ),
    808: "This error indicates that the hardware resources required to create MPS client have been exhausted.",
    809: "This error indicates the the hardware resources required to device connections have been exhausted.",
    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.",
    811: "This error indicates, that the program is using CUDA Dynamic Parallelism, but the current configuration, like MPS, does not support it.",
    812: "This error indicates, that the program contains an unsupported interaction between different versions of CUDA Dynamic Parallelism.",
    900: "The operation is not permitted when the stream is capturing.",
    901: ("The current capture sequence on the stream has been invalidated due to a previous error."),
    902: ("The operation would have resulted in a merge of two independent capture sequences."),
    903: "The capture was not initiated in this stream.",
    904: ("The capture sequence contains a fork that was not joined to the primary stream."),
    905: (
        "A dependency would have been created which crosses the capture sequence"
        " boundary. Only implicit in-stream ordering dependencies are allowed to"
        " cross the boundary."
    ),
    906: (
        "The operation would have resulted in a disallowed implicit dependency on"
        " a current capture sequence from cudaStreamLegacy."
    ),
    907: ("The operation is not permitted on an event which was last recorded in a capturing stream."),
    908: (
        "A stream capture sequence not initiated with the ::cudaStreamCaptureModeRelaxed"
        " argument to ::cudaStreamBeginCapture was passed to ::cudaStreamEndCapture in a"
        " different thread."
    ),
    909: "This indicates that the wait operation has timed out.",
    910: (
        "This error indicates that the graph update was not performed because it included"
        " changes which violated constraints specific to instantiated graph update."
    ),
    911: (
        "This indicates that an async error has occurred in a device outside of CUDA."
        " If CUDA was waiting for an external device's signal before consuming shared data,"
        " the external device signaled an error indicating that the data is not valid for"
        " consumption. This leaves the process in an inconsistent state and any further CUDA"
        " work will return the same error. To continue using CUDA, the process must be"
        " terminated and relaunched."
    ),
    912: ("This indicates that a kernel launch error has occurred due to cluster misconfiguration."),
    913: ("Indiciates a function handle is not loaded when calling an API that requires a loaded function."),
    914: ("This error indicates one or more resources passed in are not valid resource types for the operation."),
    915: ("This error indicates one or more resources are insufficient or non-applicable for the operation."),
    917: (
        "This error indicates that the requested operation is not permitted because the"
        " stream is in a detached state. This can occur if the green context associated"
        " with the stream has been destroyed, limiting the stream's operational capabilities."
    ),
    999: "This indicates that an unknown internal error has occurred.",
    10000: (
        "Any unhandled CUDA driver error is added to this value and returned via"
        " the runtime. Production releases of CUDA should not return such errors."
        " This error return is deprecated as of CUDA 4.1."
    ),
}
