Why Gemfury? Push, build, and install  RubyGems npm packages Python packages Maven artifacts PHP packages Go Modules Debian packages RPM packages NuGet packages

duality-group / torch python

Repository URL to install this package:

Version: 
1.12.1+cpu  ▾
Details    
torch / lib / libc10.so
Size: Mime: 
ELF>@Ȳ
@8
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ÿÿ·ÿÿN3c1013DebugInfoBaseEN3c1023MemoryReportingInfoBaseE../c10/core/CPUAllocator.cppC10 deleted  bytes, total alloc  bytes.C10 alloc %s
../c10/core/CopyBytes.cpp,  to ptr%dcpu../c10/core/Device.cppDeviceInvalid device string: ''stoiparse_type' in device string 'cudaipuxpumkldnnopenglopenclideephipvefpgaortxlalazyvulkanmpsmetahpuprivateuseoneCPUCUDAOPENGLOPENCLMKLDNNIDEEPHIPVEFPGAORTXLALAZYMPSVULKANmetalMETALXPUMETAHPUIPUPRIVATEUSEONEUnknown device: ../c10/core/DeviceType.cppDeviceTypeNameUNKNOWN_BACKEND_BITCPUBitHIPBitXLABitLazyBitXPUBitIPUBitMPSBitHPUBitVEBitPrivateUse1BitPrivateUse2BitPrivateUse3BitInvalidBitCUDABitUNKNOWN_TENSOR_TYPE_IDUndefinedLazyVulkanMetalQuantizedCPUQuantizedCUDAQuantizedXPUCustomRNGKeyIdMkldnnCPUSparseCPUSparseCUDASparseCsrCPUSparseCsrCUDASparseHIPSparseVESparseXPUNestedTensorNestedTensorCPUNestedTensorCUDAPythonPythonTLSSnapshotPrivateUse1PrivateUse2PrivateUse3NegativeConjugateMetaADInplaceOrViewAutogradAutogradCPUAutogradIPUAutogradXPUAutogradCUDAAutogradXLAAutogradLazyAutogradMPSAutogradHPUAutogradPrivateUse1AutogradPrivateUse2AutogradPrivateUse3AutogradOtherAutogradNestedTensorZeroTensorBackendSelectNamedFunctionalizeTracerAutocastAutocastCPUAutocastXPUBatchedVmapModeCompositeImplicitAutogradCompositeExplicitAutogradTESTING_ONLY_GenericWrapperTESTING_ONLY_GenericModeFuncTorchDynamicLayerBackModeFuncTorchGradWrapperFuncTorchVmapModeFuncTorchBatchedFakeDeferredInitDenseQuantizedSparseAutogradFunctionalityAutocastCUDA../c10/core/DispatchKey.cppparseDispatchKeygetRuntimeDispatchKeySetruntimeDispatchKeySetHasoperator++last_offset: num_runtime_entries: DispatchKeySet()DispatchKeySet() and backend bit ../c10/core/DispatchKeySet.hoperator*/dev/urandomUnable to open /dev/urandom../c10/core/GeneratorImpl.cppreadURandomLongdefault../c10/core/SafePyObject.cpp../c10/core/Scalar.cppoperator-stream  on device  devicesgetDeviceGuardImpl../c10/core/SymInt.cpptoSymbolicIntNodetoSymIntexpectIntArrayRefSymInt([]../c10/core/SymIntTable.cppgetNodevector::_M_realloc_insertTensorImpl../c10/core/TensorImpl.hlayout_impl../c10/core/TensorImpl.cpprelease_resourcesallocateOutOfLineStorageresizeOutOfLineStorageReshapeGetAutogradMetaFactoryset_requires_gradCannot access storage of throw_storage_access_errorShareDatais_contiguous_custom do not have is_contiguousTensors of type  do not have sizessizes_custom do not have numelnumel_custom do not have sym sizessym_sizes_custom do not have stridesstrides_custom do not have dimdim_customReserveSpaceExtenddevice_typetensor does not have a devicedeviceitemsizeShareExternalPointer../c10/core/Storage.htensor.createcaffe2_keep_on_shrinkstorage_initializedraw_mutable_datasafe_compute_numelset_storage_offset set_storage_offsetset_stride set_strideset_size set_sizeset_version_counterPreserveContiguousChannelsLastChannelsLast3dUnknown memory format ../c10/core/MemoryFormat.hoperator<< (default)TensorOptions(dtype=, device=, layout=StridedSparseCsrSparseCscSparseBsrSparseBscMkldnnUnknown layout../c10/core/Layout.h, requires_grad=, pinned_memory=(nullopt), memory_format=UndefinedTensorImpl but tensor has no dimensionsdimension specified as maybe_wrap_dim_slow], but got noop_detach_fnnoop_dispatch_fnnoop_is_contiguous_fn<unloaded interpreter>resizeSlowPath((ptrdiff_t)nbytes) >= 0data ( bytes. Error code ../c10/core/thread_pool.cppNo threads to run a taskvalidate_freerecord_freeAllocation plan is nullptr.set_planWithProfileAllocationsGuardWithProfilingAllocatorGuardfree, expected:, got:validate_allocation_planAllocation id:, but got:validate_allocationallocatevector::_M_default_append(basic_string::substr<unknown function>pythonpython3libpythonframe #<omitting python frames>
:  +  in )

SetPythonGILHooksWarning:  (function 
  [enforce fail at :] . PYTORCH_API_USAGE_STDERRPYTORCH_API_USAGE ../c10/util/Logging.cppSetAPIUsageLoggerSetPyTorchDDPUsageLoggerTORCH_CPP_LOG_LEVEL0INFO1WARNING2ERROR3FATAL). Capping it to GLOG_FATAL. Exception raised from  (most recent call first):
caffe2_use_fatal_for_enforceminloglevelvlogtostderrcaffe2_log_level%lu at ../c10/util/StringUtil.cppReplaceAllExpected debug info of type _peek_pop without overflowfalseFalseFALSEtrueTrueTRUE--helpArguments:     . Ignoring this argument.C10 flag: illegal argument: (Usage message not set.)../c10/util/int128.cpp, lo=caffe2_cpu_numa_enabledwidth is not integerprecision is not integerinvalid type specifier<UNKNOWN>Failed to add  handler!Failed to remove /proc/self/taskSIGABRTSIGINTSIGILLSIGFPESIGBUSSIGSEGVnegative widthnumber is too biginvalid format stringargument not foundnegative precisioninvalid fill character '{'invalid fillmissing precision specifierstring pointer is nullINFNANinfnan0123456789ABCDEFmissing '}' in format stringunknown format specifier../c10/util/typeid.cpp_ThrowRuntimeTypeLogicError (please report this error)error_unsupported_typemetaPlease report this issue.../c10/util/typeid.haddTypeMetaDatanullptr (uninitialized)Type  does not allow assignment.0123456789basic_string::_M_createbasic_string::erasebasic_string::_M_replace_auxbasic_string::insertbasic_string::replacebasic_string::_M_replacebasic_string::assignbasic_string::appendbasic_string::copybasic_string::comparebasic_string::basic_stringstring::stringThere is not caching allocator registered for CPU, use the default allocator instead.Memory block of unknown size was allocated before the profiling started, profiler results will not include the deallocation event(bool, default false) If set, print out detailed memory usagecaffe2_report_cpu_memory_usageKey already registered with the same priority: Higher priority item already registered, skipping registration of Check failed: g_copy_bytes[0][from][to] == nullptr && g_copy_bytes[1][from][to] == nullptr Duplicate registration for device type pair No function found for copying from Device string must not be emptybasic_string::at: __n (which is %zu) >= this->size() (which is %zu)Expected one of cpu, cuda, ipu, xpu, mkldnn, opengl, opencl, ideep, hip, ve, ort, mps, xla, lazy, vulkan, meta, hpu, privateuseone device type at start of device string: Could not parse device index '. If you have recently updated the caffe2.proto file to add a new device type, did you forget to update the DeviceTypeName() function to reflect such recent changes?FuncTorchDynamicLayerFrontModecould not parse dispatch key: t != DispatchKey::Undefined INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":32, please report a bug to PyTorch. ../c10/core/DispatchKeySet.cppt != DispatchKey::Undefined INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":51, please report a bug to PyTorch. next_functionality_ <= iterator::end_iter_mask_val INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":128, please report a bug to PyTorch. next_backend_ <= num_backends INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":129, please report a bug to PyTorch. next_backend_ == 0 INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":201, please report a bug to PyTorch. offsets_and_masks[num_functionality_keys - 1].offset == (num_runtime_entries - 1) INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.cpp":236, please report a bug to PyTorch. initializeFunctionalityOffsetsAndMasksTried to map functionality key  to a runtime key, but ended up with . This can happen if the order of the backend dispatch keys in DispatchKey.h isn't consistent. Please double check that enum for inconsistencies.toBackendComponent(next_key) == static_cast<BackendComponent>(current_backendcomponent_idx_) INTERNAL ASSERT FAILED at "../c10/core/DispatchKeySet.h":565, please report a bug to PyTorch. Unable to read from /dev/urandominterpreter == pyinterpreter_ INTERNAL ASSERT FAILED at "../c10/core/SafePyObject.cpp":7, please report a bug to PyTorch. torch boolean negative, the `-` operator, is not supported.PyTorch is not linked with support for ../c10/core/impl/DeviceGuardImplInterface.hExpected is_symbolic() to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)SymbolicIntNode index overflow: Expected !sci.is_symbolic() to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)../c10/core/SymIntArrayRef.cppExpected index < nodes_.size() to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)layout_impl is only implemented for TensorImpl subclasses.pyobj_interpreter_ != nullptr INTERNAL ASSERT FAILED at "../c10/core/TensorImpl.cpp":328, please report a bug to PyTorch. pyobj_ != nullptr INTERNAL ASSERT FAILED at "../c10/core/TensorImpl.cpp":329, please report a bug to PyTorch. Could not allocate memory for Tensor SizesAndStrides!../c10/core/impl/SizesAndStrides.hRight now Reshape is only supported for contiguous Tensor.Expected d >= 0 to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)New size and old size are not equal. You cannot use Reshape, but should use Resize. The old caffe2 mixes Reshape and Resize but this behavior has been changed. If you find this error, most likely you will need to change corresponding code from Reshape to Resize.Support for autograd has not been loaded; have you linked against libtorch.so?Setting requires_grad=True on inference tensor outside InferenceMode is not allowed.Size mismatch - did you call reshape before sharing the data?Source tensor don't have a data type (did you call mutable_data<T> on the tensor?)Source tensor has no content and has size > 0cannot access PyObject for Tensor on interpreter Right now ReserveSpace is only supported for contiguous Tensor.Can't call ReserveSpace on shared storage.Expected sizes_and_strides_.size() >= 1u to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)`num` must be non-negative for ExtendRight now Extend is only supported for contiguous Tensor.device_type cannot be run on undefined Tensornon-POD types work only on CPUCannot report itemsize of Tensor that doesn't have initialized dtype (e.g., caffe2::Tensor x(CPU), prior to calling mutable_data<T>() on x)To share with a raw external pointer you need to pass in an initialized data_type(TypeMeta).UniqueStorageShareExternalPointer can only be called when use_count == 1UniqueStorageShareExternalPointerdata_type == ScalarType::Undefined || device_opt_.has_value() INTERNAL ASSERT FAILED at "../c10/core/TensorImpl.cpp":146, please report a bug to PyTorch. (bool, default true) If set, keeps memory when a tensor is shrinking its size.(int64_t, default 0x7fffffffffffffffLL) The maximum memory in bytes to keep on shrink, if the difference between tensor sizes is bigger than this then tensor will be reset.caffe2_max_keep_on_shrink_memoryis not allowed on a Tensor created from .data or .detach().
If your intent is to change the metadata of a Tensor (such as sizes / strides / storage / storage_offset)
without autograd tracking the change, remove the .data / .detach() call and wrap the change in a `with torch.no_grad():` block.
For example, change:
    x.data.set_(y)
to:
    with torch.no_grad():
        x.set_(y)cannot call storage_initialized on tensor that does not have storagestorage_offset_ == 0 INTERNAL ASSERT FAILED at "../c10/core/TensorImpl.h":1823, please report a bug to PyTorch. storage_offset_ == 0 INTERNAL ASSERT FAILED at "../c10/core/TensorImpl.h":1851, please report a bug to PyTorch. numel: integer multiplication overflowCannot set version_counter for inference tensorset_storage_offset() called on an undefined Tensor../c10/core/UndefinedTensorImpl.cpp../c10/core/WrapDimMinimal.cppshould never reach here as dim should be out-of-boundsfalse INTERNAL ASSERT FAILED at "../c10/core/WrapDimMinimal.cpp":31, please report a bug to PyTorch. Dimension out of range (expected to be in range of [attempted to detach (shallow_copy_and_detach) Tensor with nontrivial PyObject after corresponding interpreter died0 INTERNAL ASSERT FAILED at "../c10/core/impl/PyInterpreter.cpp":18, please report a bug to PyTorch. ../c10/core/impl/PyInterpreter.cppattempted to dispatch (__torch_dispatch__) an operator on Tensor with nontrivial PyObject after corresponding interpreter died0 INTERNAL ASSERT FAILED at "../c10/core/impl/PyInterpreter.cpp":28, please report a bug to PyTorch. attempted to is_contiguous Tensor with nontrivial PyObject after corresponding interpreter died0 INTERNAL ASSERT FAILED at "../c10/core/impl/PyInterpreter.cpp":34, please report a bug to PyTorch. Could not allocate memory to change Tensor SizesAndStrides!../c10/core/impl/SizesAndStrides.cppalloc_cpu() seems to have been called with negative number: ../c10/core/impl/alloc_cpu.cppDefaultCPUAllocator: not enough memory: you tried to allocate Check failed: !FLAGS_caffe2_cpu_allocator_do_zero_fill || !FLAGS_caffe2_cpu_allocator_do_junk_fill Cannot request both zero-fill and junk-fill at the same timeDefaultCPUAllocator: can't allocate memory: you tried to allocate (bool, default false) If set, do memory zerofilling when allocating on CPUcaffe2_cpu_allocator_do_zero_fill(bool, default false) If set, fill memory with deterministic junk when allocating on CPUcaffe2_cpu_allocator_do_junk_fillException in thread pool task: Exception in thread pool task: unknowncannot create std::deque larger than max_size()Allocation must have been recorded during validate_allocation.../c10/mobile/CPUProfilingAllocator.cppAllocation must have been recorded during record_allocation.Nesting profiling allocations is not supported.WithValidateAllocationPlanGuardNesting profiling allocators is not supported.Freeing allocation that is not accordingly to the plan.Lifetime of allocations do not match: allocation_id cannot create std::vector larger than max_size()ProfilingAllocator: Allocation plan invalid.formulate_greedy_allocation_planEnf offset of allocation being freed must match the one recorded.ProfilingAllocator: Invalid event type.ProfilingAllocator: Allocate event must have preceded deallocate event.Allocation request does not match plan:, Number of recorded allocations:, Recorded size of the requested allocation:Got allocation request that does not match with the plan.%s: __pos (which is %zu) > this->size() (which is %zu)TORCH_DISABLE_DEADLOCK_DETECTION!hooks || !python_gil_hooks INTERNAL ASSERT FAILED at "../c10/util/DeadlockDetection.cpp":27, please report a bug to PyTorch. ../c10/util/DeadlockDetection.cppExpected logger to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)`TORCH_CPP_LOG_LEVEL` environment variable cannot be parsed. Valid values are `INFO`, `WARNING`, `ERROR`, and `FATAL` or their numerical equivalents `0`, `1`, `2`, and `3`.InitCaffeLogging() has to be called after c10::ParseCommandLineFlags. Modify your program to make sure of this.The log level of Caffe2 has to be no larger than GLOG_FATAL((bool, default false) If set true, when CAFFE_ENFORCE is not met, abort instead of throwing an exception.(int, default 0) Equivalent to glog minloglevel(int, default 0) Equivalent to glog verbose(bool, default false) Equivalent to glog logtostderr(int, default c10::GLOG_WARNING) The minimum log level that caffe2 will output.SmallVector capacity unable to grow. Already at maximum size SmallVector unable to grow. Requested capacity () is larger than maximum value for size type (../c10/util/ThreadLocalDebugInfo.cppvalue cannot be converted to type C10 flag error: Cannot convert argument to bool: Note that if you are passing in a bool flag, you need to explicitly specify it, like --arg=True or --arg True. Otherwise, the next argument may be inadvertently used as the argument, causing the above error.Parsing commandline arguments for c10.C10 flag: commandline argument does not match --name=var or --name format: C10 flag: reached the last commandline argument, but I am expecting a value for C10 flag: unrecognized commandline argument: Division or mod by zero: dividend.hi=(bool, default false) Use NUMA whenever possible.../c10/util/signal_handler.cppCannot uninstall SIGHUP handler.Cannot uninstall SIGINT handler.Cannot install SIGHUP handler.Cannot install SIGINT handler.Failed to add SIGUSR2 handler!{}({}), PID: {}, Thread {}: 
 {}Failed to open /proc/self/taskcannot switch from manual to automatic argument indexingcannot switch from automatic to manual argument indexingformat specifier requires numeric argumentformat specifier requires signed argumentprecision not allowed for this argument typeinvalid format specifier for charunmatched '}' in format stringconstexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::unique_ptr<std::mutex>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::unique_ptr<std::atomic<bool> >; c10::string_view = c10::basic_string_view<char>]Unsupported TypeMeta in ATen: Maximum number of CAFFE_KNOWN_TYPE declarations has been exceeded. constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::basic_string<char>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = short unsigned int; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = char; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::vector<int>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::vector<long int>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = std::vector<long unsigned int>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = bool*; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = char*; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = int*; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = caffe2::detail::_guard_long_unique_dummy<long int>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = caffe2::detail::_guard_long_unique_dummy<std::vector<long int> >; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = float*; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::Half*; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = unsigned char; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = signed char; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = short int; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = int; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = long int; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::Half; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = float; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = double; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::complex<c10::Half>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::complex<float>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::complex<double>; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = bool; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::qint8; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::quint8; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::qint32; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::BFloat16; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::quint4x2; c10::string_view = c10::basic_string_view<char>]constexpr c10::string_view c10::util::detail::fully_qualified_type_name_impl() [with T = c10::quint2x4; c10::string_view = c10::basic_string_view<char>]basic_string::_M_construct null not validFSt10unique_ptrIN3c1013C10FlagParserESt14default_deleteIS1_EERKSsEN3c109AllocatorEN3c1019DefaultCPUAllocatorEN3c1025DefaultMobileCPUAllocatorILj64ELj16EEEPFSt10unique_ptrIN3c1013C10FlagParserESt14default_deleteIS1_EERKSsE<Œûÿ\Œûÿ|Œûÿ¤Œûÿ̌ûÿôŒûÿûÿDûÿlûÿ”ûÿ¼ûÿäûÿŽûÿ4Žûÿ\Žûÿ„Žûÿ¬ŽûÿԎûÿì‹ûÿŒûÿ¬”ûÿœ”ûÿŒ”ûÿü”ûÿ¼”ûÿ̔ûÿܔûÿì”ûÿ,•ûÿ<•ûÿL•ûÿ\•ûÿ•ûÿ•ûÿ¼—ûÿ´—ûÿ¬—ûÿ¤—ûÿœ—ûÿ”—ûÿŒ—ûÿ„—ûÿ|—ûÿt—ûÿl—ûÿd—ûÿ\—ûÿT—ûÿL—ûÿD—ûÿ<—ûÿ4—ûÿ,—ûÿ$—ûÿ—ûÿ—ûÿ—ûÿ—ûÿü–ûÿô–ûÿì–ûÿä–ûÿܖûÿԖûÿ̖ûÿĖûÿ¼–ûÿ´–ûÿ¬–ûÿ¤–ûÿœ–ûÿ”–ûÿŒ–ûÿ„–ûÿ|–ûÿT•ûÿT•ûÿėûÿt–ûÿl–ûÿd–ûÿ\–ûÿT–ûÿL–ûÿD–ûÿ<–ûÿ4–ûÿ,–ûÿ$–ûÿ–ûÿT•ûÿ–ûÿ–ûÿT•ûÿT•ûÿT•ûÿT•ûÿ–ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿü•ûÿô•ûÿì•ûÿT•ûÿT•ûÿT•ûÿä•ûÿT•ûÿܕûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿԕûÿ̕ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿT•ûÿĕûÿ¼•ûÿT•ûÿ´•ûÿ¬•ûÿ¤•ûÿœ•ûÿ”•ûÿT•ûÿŒ•ûÿ„•ûÿ|•ûÿt•ûÿl•ûÿd•ûÿ\•ûÿ8—ûÿȗûÿH—ûÿ8—ûÿX—ûÿh—ûÿؗûÿx—ûÿˆ—ûÿ8—ûÿ˜—ûÿ¨—ûÿ¸—ûÿ—ûÿ€_ÈB€?K?€ÿÿàC0Cð?ÿÿÿÿÿÿûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿð®ûÿ˜­ûÿ°­ûÿð®ûÿЭûÿð­ûÿ®ûÿ0®ûÿP®ûÿð®ûÿp®ûÿ®ûÿ°®ûÿЮûÿeN3c1020intrusive_ptr_targetEN3c1013GeneratorImplE€ÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿþnot enough space for format expansion (Please submit full bug report at https://gcc.gnu.org/bugsÝ(üÿp*üÿà)üÿÝ(üÿð)üÿ*üÿ€*üÿ *üÿ0*üÿÝ(üÿ@*üÿP*üÿ`*üÿ*üÿ€N3c105ErrorEN3c1019NotImplementedErrorEN3c1011StorageImplEN3c1021AutogradMetaInterfaceEN3c1015VariableVersion14VersionCounterEN3c1010TensorImplEÏ_üÿü^üÿ_üÿ<_üÿ\_üÿ¬^üÿÜ^üÿN3c1019UndefinedTensorImplEN3c1010IndexErrorEï¾íï¾íN3c1018TaskThreadPoolBaseEN3c1010ThreadPoolE*NSt6thread11_State_implINS_8_InvokerISt5tupleIJZN3c1010ThreadPoolC4EiiSt8functionIFvvEEEUlvE_EEEEEEN3c1019CPUCachingAllocatorE?:;/5<'06!*=3%(17"+>9.4& )2$

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