Can't solve this error: Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERRORkeras using tensorflow as backend :Cannot interpret feed_dict key as Tensor: Can not convert a int into a TensorKeras Multi GPU example gives ResourceExhaustedErrorKeras loaded model is Not workingAn error ocurred while starting the kernel while usingKeras pretrained model is not downloadedProblems with Seq2Seq model using RNN layer and GRU cells in Kerastensorflow run any opmtimizer get exit code 139 interrupted by signal 11: SIGSEGVKeras Gpu: ConfigurationFailed to get convolution algorithm. This is probably because cuDNN failed to initialize
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Can't solve this error: Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
keras using tensorflow as backend :Cannot interpret feed_dict key as Tensor: Can not convert a int into a TensorKeras Multi GPU example gives ResourceExhaustedErrorKeras loaded model is Not workingAn error ocurred while starting the kernel while usingKeras pretrained model is not downloadedProblems with Seq2Seq model using RNN layer and GRU cells in Kerastensorflow run any opmtimizer get exit code 139 interrupted by signal 11: SIGSEGVKeras Gpu: ConfigurationFailed to get convolution algorithm. This is probably because cuDNN failed to initialize
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
0
I am trying to train a CNN with keras, tensorflow backend. It was working and out of the blue I got this error.
I tried rm -rf ~/.nv/ but it didn't work.
EDIT: I created another virtual environment and it is working.
Here is the full log:
Using TensorFlow backend.
2019-03-28 09:23:59.602808: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-28 09:23:59.686104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-28 09:23:59.686506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1060 with Max-Q Design major: 6 minor: 1 memoryClockRate(GHz): 1.3415
pciBusID: 0000:01:00.0
totalMemory: 5.94GiB freeMemory: 5.36GiB
2019-03-28 09:23:59.686525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2019-03-28 09:23:59.910495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-28 09:23:59.910530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2019-03-28 09:23:59.910536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2019-03-28 09:23:59.910694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5126 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 6.1)
Epoch 1/10
2019-03-28 09:24:24.618996: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-03-28 09:24:24.921106: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
File "train_models.py", line 63, in <module>
workers=6)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1418, in fit_generator
initial_epoch=initial_epoch)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training_generator.py", line 217, in fit_generator
class_weight=class_weight)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2715, in __call__
return self._call(inputs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1439, in __call__
run_metadata_ptr)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution = Conv2D[T=DT_FLOAT, _class=["loc:@training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter"], data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv2d_1/kernel/read)]]
[[node loss/mul/_113 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_853_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
tensorflow keras cudnn
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
add a comment |
0
I am trying to train a CNN with keras, tensorflow backend. It was working and out of the blue I got this error.
I tried rm -rf ~/.nv/ but it didn't work.
EDIT: I created another virtual environment and it is working.
Here is the full log:
Using TensorFlow backend.
2019-03-28 09:23:59.602808: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-28 09:23:59.686104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-28 09:23:59.686506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1060 with Max-Q Design major: 6 minor: 1 memoryClockRate(GHz): 1.3415
pciBusID: 0000:01:00.0
totalMemory: 5.94GiB freeMemory: 5.36GiB
2019-03-28 09:23:59.686525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2019-03-28 09:23:59.910495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-28 09:23:59.910530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2019-03-28 09:23:59.910536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2019-03-28 09:23:59.910694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5126 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 6.1)
Epoch 1/10
2019-03-28 09:24:24.618996: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-03-28 09:24:24.921106: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
File "train_models.py", line 63, in <module>
workers=6)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1418, in fit_generator
initial_epoch=initial_epoch)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training_generator.py", line 217, in fit_generator
class_weight=class_weight)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2715, in __call__
return self._call(inputs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1439, in __call__
run_metadata_ptr)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution = Conv2D[T=DT_FLOAT, _class=["loc:@training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter"], data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv2d_1/kernel/read)]]
[[node loss/mul/_113 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_853_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
tensorflow keras cudnn
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47
add a comment |
0
0
0
I am trying to train a CNN with keras, tensorflow backend. It was working and out of the blue I got this error.
I tried rm -rf ~/.nv/ but it didn't work.
EDIT: I created another virtual environment and it is working.
Here is the full log:
Using TensorFlow backend.
2019-03-28 09:23:59.602808: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-28 09:23:59.686104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-28 09:23:59.686506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1060 with Max-Q Design major: 6 minor: 1 memoryClockRate(GHz): 1.3415
pciBusID: 0000:01:00.0
totalMemory: 5.94GiB freeMemory: 5.36GiB
2019-03-28 09:23:59.686525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2019-03-28 09:23:59.910495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-28 09:23:59.910530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2019-03-28 09:23:59.910536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2019-03-28 09:23:59.910694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5126 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 6.1)
Epoch 1/10
2019-03-28 09:24:24.618996: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-03-28 09:24:24.921106: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
File "train_models.py", line 63, in <module>
workers=6)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1418, in fit_generator
initial_epoch=initial_epoch)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training_generator.py", line 217, in fit_generator
class_weight=class_weight)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2715, in __call__
return self._call(inputs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1439, in __call__
run_metadata_ptr)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution = Conv2D[T=DT_FLOAT, _class=["loc:@training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter"], data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv2d_1/kernel/read)]]
[[node loss/mul/_113 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_853_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
tensorflow keras cudnn
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
I am trying to train a CNN with keras, tensorflow backend. It was working and out of the blue I got this error.
I tried rm -rf ~/.nv/ but it didn't work.
EDIT: I created another virtual environment and it is working.
Here is the full log:
Using TensorFlow backend.
2019-03-28 09:23:59.602808: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-28 09:23:59.686104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-03-28 09:23:59.686506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1060 with Max-Q Design major: 6 minor: 1 memoryClockRate(GHz): 1.3415
pciBusID: 0000:01:00.0
totalMemory: 5.94GiB freeMemory: 5.36GiB
2019-03-28 09:23:59.686525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2019-03-28 09:23:59.910495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-28 09:23:59.910530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2019-03-28 09:23:59.910536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2019-03-28 09:23:59.910694: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5126 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 with Max-Q Design, pci bus id: 0000:01:00.0, compute capability: 6.1)
Epoch 1/10
2019-03-28 09:24:24.618996: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-03-28 09:24:24.921106: E tensorflow/stream_executor/cuda/cuda_dnn.cc:373] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
File "train_models.py", line 63, in <module>
workers=6)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1418, in fit_generator
initial_epoch=initial_epoch)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training_generator.py", line 217, in fit_generator
class_weight=class_weight)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/engine/training.py", line 1217, in train_on_batch
outputs = self.train_function(ins)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2715, in __call__
return self._call(inputs)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1439, in __call__
run_metadata_ptr)
File "/home/fadwa/.virtualenvs/dl_tf_Py3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution = Conv2D[T=DT_FLOAT, _class=["loc:@training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter"], data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](training/Adam/gradients/conv2d_1/convolution_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv2d_1/kernel/read)]]
[[node loss/mul/_113 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_853_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
tensorflow keras cudnn
tensorflow keras cudnn
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
edited Mar 28 at 7:56
Misaki
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
asked Mar 28 at 5:27
MisakiMisaki
6641 gold badge13 silver badges30 bronze badges
6641 gold badge13 silver badges30 bronze badges
Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47
add a comment |
Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47
Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47
add a comment |
0
active
oldest
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Please list yout cuda, cuDNN, tensorflow, python version. This is probably because some version is not incompatible.
– qinlong
Mar 28 at 12:55
But it was working perfectly on the same environment!.
– Misaki
Apr 3 at 9:28
Maybe you should check the environment variable setting.
– qinlong
Apr 3 at 11:47