cuda nvcc生成ptx文件遇到的错误error: invalid redeclaration of type name "size_t"

最新推荐文章于 2024-09-10 16:21:17 发布
原创 最新推荐文章于 2024-09-10 16:21:17 发布 · 2.5k 阅读 · 1 ·
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博客给出解决问题的方法，使用vs的x64本机命令提示符可避免某错误，且经过亲测有效。
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解决方法：用vs的x64本机命令提示符可避免该错误，亲测有效！

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cuda编译出现vcruntime.h(184): error: invalid redeclaration of type name “size_t“
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【代码】cuda编译出现vcruntime.h(184): error: invalid redeclaration of type name “size_t“
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10-15 2211
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2025-06-30 09:26:27.075176: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleLoadData(&module, data)' failed with 'CUDA_ERROR_UNSUPPORTED_PTX_VERSION' 2025-06-30 09:26:27.075224: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleGetFunction(&function, module, kernel_name)' failed with 'CUDA_ERROR_INVALID_HANDLE' 如何解决这个报错
07-01
1.'cuModuleLoadData'failed withCUDA_ERROR_UNSUPPORTED_PTX_VERSION2.'cuModuleGetFunction'failed withCUDA_ERROR_INVALID_HANDLE根据引用[1]：任何未处理的CUDA驱动程序错误都会添加到该值中并通过运行时返回。...
2025-09-18 14:17:00.603094: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleLoadData(&module, data)' failed with 'CUDA_ERROR_INVALID_PTX' 2025-09-18 14:17:00.603148: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleGetFunction(&function, module, kernel_name)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-18 14:17:00.603193: W tensorflow/core/framework/op_kernel.cc:1827] INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-18 14:17:00.603235: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [2025-09-18 14:17:00,603][pinnstf2.utils.utils][ERROR] - Traceback (most recent call last): File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/common/variables.py", line 153, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/core.py", line 69, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/core.py", line 139, in convert_to_tensor return tf.cast(x, dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/tensorflow/python/framework/ops.py", line 5983, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: [2025-09-18 14:17:00,609][pinnstf2.utils.utils][INFO] - Output dir: /home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/examples/aneurysm3D/outputs/14-16-46 Error executing job with overrides: [] Traceback (most recent call last): File "/home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/train.py", line 139, in main metric_dict, _ = pinnstf2.train( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/utils/utils.py", line 84, in wrap raise ex File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/common/variables.py", line 153, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/core.py", line 69, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/keras/src/backend/tensorflow/core.py", line 139, in convert_to_tensor return tf.cast(x, dtype) File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.10/site-packages/tensorflow/python/framework/ops.py", line 5983, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
09-19
您遇到的错误 'CUDA_ERROR_INVALID_PTX' 和 'CUDA_ERROR_INVALID_HANDLE' 通常与 GPU 计算环境不兼容有关，尤其是在使用 TensorFlow 时。这些错误表明 CUDA 驱动程序或 PTX（并行线程执行）代码出现了问题。核心原因...
2025-09-20 18:11:55.609791: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleLoadData(&module, data)' failed with 'CUDA_ERROR_INVALID_PTX' 2025-09-20 18:11:55.609846: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleGetFunction(&function, module, kernel_name)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-20 18:11:55.609887: W tensorflow/core/framework/op_kernel.cc:1842] INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-20 18:11:55.609927: I tensorflow/core/framework/local_rendezvous.cc:407] Local rendezvous is aborting with status: INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [2025-09-20 18:11:55,610][pinnstf2.utils.utils][ERROR] - Traceback (most recent call last): File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( ^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() ^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/common/variables.py", line 173, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 73, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 152, in convert_to_tensor return tf.cast(x, dtype) ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/framework/ops.py", line 6027, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: [2025-09-20 18:11:55,614][pinnstf2.utils.utils][INFO] - Output dir: /home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/outputs/18-11-42 Error executing job with overrides: [] Traceback (most recent call last): File "/home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/train.py", line 139, in main metric_dict, _ = pinnstf2.train( ^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 84, in wrap raise ex File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( ^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() ^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/common/variables.py", line 173, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 73, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 152, in convert_to_tensor return tf.cast(x, dtype) ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/framework/ops.py", line 6027, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
最新发布
09-21
我们正在解决TensorFlow使用GPU时出现的两个错误：'CUDA_ERROR_INVALID_PTX'和'CUDA_ERROR_INVALID_HANDLE'。根据引用内容，这些错误可能与CUDA工具链的兼容性有关，特别是PTX（并行线程执行）代码的编译问题。以下...
cuModuleLoadData(&module, data)' failed with 'CUDA_ERROR_INVALID_PTX' 2025-09-19 00:59:41.652223: W tensorflow/compiler/mlir/tools/kernel_gen/tf_gpu_runtime_wrappers.cc:40] 'cuModuleGetFunction(&function, module, kernel_name)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-19 00:59:41.652257: W tensorflow/core/framework/op_kernel.cc:1842] INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' 2025-09-19 00:59:41.652285: I tensorflow/core/framework/local_rendezvous.cc:407] Local rendezvous is aborting with status: INTERNAL: 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [2025-09-19 00:59:41,652][pinnstf2.utils.utils][ERROR] - Traceback (most recent call last): File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( ^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() ^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/common/variables.py", line 173, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 73, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 152, in convert_to_tensor return tf.cast(x, dtype) ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/framework/ops.py", line 6027, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: [2025-09-19 00:59:41,657][pinnstf2.utils.utils][INFO] - Output dir: /home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/outputs/00-59-28 Error executing job with overrides: [] Traceback (most recent call last): File "/home/jfq/pinns-tf2-main/pinns-tf2-main/examples/aneurysm3D/train.py", line 139, in main metric_dict, _ = pinnstf2.train( ^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 84, in wrap raise ex File "/root/pinns-tf2/pinnstf2/utils/utils.py", line 72, in wrap metric_dict, object_dict = task_func( ^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/train.py", line 122, in train model: PINNModule = hydra.utils.instantiate(cfg.model)( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/pinns-tf2/pinnstf2/models/pinn_module.py", line 56, in __init__ self.opt = optimizer() ^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/adam.py", line 62, in __init__ super().__init__( File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/optimizer.py", line 21, in __init__ super().__init__(*args, **kwargs) File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/optimizers/base_optimizer.py", line 158, in __init__ iterations = backend.Variable( ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/common/variables.py", line 173, in __init__ initializer = self._convert_to_tensor(initializer, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 73, in _convert_to_tensor return convert_to_tensor(value, dtype=dtype) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/keras/src/backend/tensorflow/core.py", line 152, in convert_to_tensor return tf.cast(x, dtype) ^^^^^^^^^^^^^^^^^ File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/util/traceback_utils.py", line 153, in error_handler raise e.with_traceback(filtered_tb) from None File "/home/jfq/anaconda3/envs/pinn/lib/python3.12/site-packages/tensorflow/python/framework/ops.py", line 6027, in raise_from_not_ok_status raise core._status_to_exception(e) from None # pylint: disable=protected-access ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ tensorflow.python.framework.errors_impl.InternalError: {{function_node __wrapped__Cast_device_/job:localhost/replica:0/task:0/device:GPU:0}} 'cuLaunchKernel(function, gridX, gridY, gridZ, blockX, blockY, blockZ, 0, reinterpret_cast<CUstream>(stream), params, nullptr)' failed with 'CUDA_ERROR_INVALID_HANDLE' [Op:Cast] name: Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
09-20
### 解决 Hydra/TensorFlow/Keras 的 CUDA 错误：`CUDA_ERROR_INVALID_PTX` 和 `CUDA_ERROR_INVALID_HANDLE` 以下解决方案针对两种常见 CUDA 错误： 1. `cuModuleLoadData(&module, data)` 失败并报错 `CUDA_ERROR_...
stm32结合TFLCD编程遇到的问题#256: invalid redeclaration of type name “_lcd_dev“
xiaoxiaokis的博客
07-05 1518
stm32结合TFLCD编程遇到的问题，当制作.c和.h时出现的报错
mdk报错invalid redeclaration of type name "s32"
mayahs的专栏
11-11 4185
将mdk固件库升级成V3.5.0，编译至XX.c时报错 \stm32f10x.h(487): error:  #256: invalid redeclaration of type name "s32" (declared at line 23 of "d:\Keil\ARM\INC\ST\STM32F10x\stm32f10x_type.h") 观察同名XX.h,其中有#include "s
关于STM32头文件包含出现No such file or directory和 invalid redeclaration of type name...的问题
fushiqianxun的专栏
08-30 2万+
用keil sdk编译STM32的程序时出现“.\inc\stm32f10x_conf.h(21): error:  #5: cannot open source input file "stm32f10x_type.h": No such file or directory”类似的问题，说明没有搜到此头文件，如果是用双引号 “  ” 包含的头文件，则问题肯定出在没有把此头文件放在工程文件夹内
stm32f10x.h(41): error: #256: invalid redeclaration of type name “GPIO_TypeDef“ (declared at line 4
weixin_53877801的博客
01-19 785
语法上没有什么问题的话。查看.h中是否包含声明。结构体如果是在.h中。加上以后就没有错误了。
keil报错：stm32f10x_type.h:error:256：invalid invalid redeclaration of type
Hzhena的专栏
04-16 6820
在使用ST官网的固件包新建工程文件后，编译报错“D:/Keil/ARM/INC/ST/STM32F10x/stm32f10x_type.h(23): error: #256: invalid redeclaration of type name "s32" (declared at line 470 of "Src/App/stm32f10x.h")”，在网上也看到了类似的问题，不过都没有明确
***stm32f10x_type.h(23): error: #256: invalid redeclaration of type name "s32" 原因+解决方案
@角色扮演#
12-29 1万+
Build target 'USART_Base' compiling main.c... D:\STM32开发板资料\STM32开发板资料\工具软件\MDK3.50\ARM\INC\ST\STM32F10x\stm32f10x_type.h(23): error:  #256: invalid redeclaration of type name "s32" (declared at lin
STM32调试小记
optimism_的博客
05-10 729
一.编译后报错： stm32f10x.h(24): error: #256: invalid redeclaration of type name "GPIO_TypeDef" (declared at line 24) }GPIO_TypeDef; stm32f10x.h(38): error: #256: invalid redeclaration of type name "RCC_TypeDef" (declared at line 38...
nvcc编译选项
yuzyong的博客
09-10 1522
gencode arch=compute_86,code=compute_86 : 生成sass指令，版本为sm_86 (若需要生成多个版本，这里可以指定多个)-gencode arch=compute_86,code=sm_86 : 生成ptx，版本为sm_86 (若需要生成多个版本，这里可以指定多个)官网地址：https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html。-o : 生成目标文件。
ninja: error: build.ninja:30: multiple rules generate dcn_v2_cuda.obj
07-05
在构建深度学习模型或相关库时，若遇到 `ninja: build stopped: subcommand failed` 错误，并提示多个规则生成了相同的输出文件（如 `dcn_v2_cuda.obj`），这通常意味着构建系统检测到两个或更多不同的编译步骤试图生成同一个目标文件。这种冲突会导致构建失败。 ### 原因分析 - **源文件重复编译**：不同编译配置或路径设置可能导致同一源文件被多次编译并尝试生成相同的目标文件。 - **构建脚本配置错误**：Ninja 构建文件（`build.ninja`）中可能存在不正确的规则定义，导致多个规则指向同一输出。 - **第三方库依赖问题**：例如 DCN（Deformable Convolution）等自定义 CUDA 操作可能与项目其他部分存在依赖冲突。 ### 解决方案 - **检查源码结构和 CMakeLists.txt 配置**：确保没有重复的源文件被添加进构建系统。对于使用 CMake 的项目，应检查 `CMakeLists.txt` 文件中是否多次包含了 `dcn_v2_cuda.cpp` 或 `.cu` 文件[^1]。 - **清理构建目录并重新生成 Ninja 文件**： ```bash rm -rf build/ mkdir build && cd build cmake .. ninja ``` 这样可以避免旧的构建残留影响新构建过程。 - **修改 CUDA 架构支持参数**：如果错误信息中包含类似 `nvcc fatal : Unsupported gpu architecture ‘compute_86’`，说明当前使用的 CUDA 工具链不支持该 GPU 架构（如 RTX 3090 对应 compute_86）。可以在构建命令中显式指定支持的架构，例如在调用 `cmake` 时添加： ```bash -DCMAKE_CUDA_ARCHITECTURES=75 ``` 或者在 `setup.py` 中调整 CUDA 编译参数以排除不支持的架构[^1]。 - **更新 PyTorch 和 CUDA 环境**：某些情况下，特定版本的 PyTorch 可能与自定义 CUDA 扩展存在兼容性问题。尝试升级 PyTorch 到最新稳定版，并确认 CUDA 版本与驱动程序匹配。 - **手动编辑 `build.ninja` 文件**：作为最后手段，可打开 `build.ninja` 查找所有涉及 `dcn_v2_cuda.obj` 的规则，并删除或注释掉重复的部分。但此方法不推荐，因为下次运行 CMake 会覆盖更改[^1]。 --- ###
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