Unable to run TensorFlow using GPU. Code works in CPU.
Debian version 9.8
- 1 GPU Nvidia Tesla V100
- TensorFlow-GPU 1.12
- Nvidia Driver: NVIDIA-Linux-x86_64-390.46.run
- CUDA: cuda_9.0.176_384.81_linux-run
- CuDNN: cudnn-9.0-linux-x64-v7.4.1.5.tgz
- NCCL: nccl_2.3.7-1+cuda9.0_x86_64.txz
Update: Tested with CuDNN 7.1.4 and same problem
Patches
- cuda_9.0.176.1_linux-run
- cuda_9.0.176.2_linux-run
- cuda_9.0.176.3_linux-run
- cuda_9.0.176.4_linux-run
Error:
et convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv1/Conv2D (defined at mnist_distributed.py:119) = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:worker/replica:0/task:1/device:GPU:0"](adam_optimizer/gradients/conv1/Conv2D_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv1/Variable/read_S15)]]
[[{{node adam_optimizer/gradients/conv2/add_grad/tuple/control_dependency_1_S43}} = _Recv[client_terminated=false, recv_device="/job:ps/replica:0/task:0/device:GPU:0", send_device="/job:worker/replica:0/task:1/device:GPU:0", send_device_incarnation=-1302637405089825922, tensor_name="edge_273_adam_optimizer/gradients/conv2/add_grad/tuple/control_dependency_1", tensor_type=DT_FLOAT, _device="/job:ps/replica:0/task:0/device:GPU:0"]()]]
Caused by op 'conv1/Conv2D', defined at:
File "mnist_distributed.py", line 237, in <module>
tf.app.run()
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "mnist_distributed.py", line 196, in main
features, labels, keep_prob, global_step, train_step, accuracy, merged = create_model()
File "mnist_distributed.py", line 149, in create_model
y_conv, keep_prob = deepnn(x)
File "mnist_distributed.py", line 77, in deepnn
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
File "mnist_distributed.py", line 119, in conv2d
return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME')
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 957, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/hadoop/yarn/nm-local-dir/usercache/root/appcache/application_1550476352470_0004/container_1550476352470_0004_01_000004/venv/tf/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
UnknownError (see above for traceback): 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 conv1/Conv2D (defined at mnist_distributed.py:119) = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="SAME", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:worker/replica:0/task:1/device:GPU:0"](adam_optimizer/gradients/conv1/Conv2D_grad/Conv2DBackpropFilter-0-TransposeNHWCToNCHW-LayoutOptimizer, conv1/Variable/read_S15)]]
[[{{node adam_optimizer/gradients/conv2/add_grad/tuple/control_dependency_1_S43}} = _Recv[client_terminated=false, recv_device="/job:ps/replica:0/task:0/device:GPU:0", send_device="/job:worker/replica:0/task:1/device:GPU:0", send_device_incarnation=-1302637405089825922, tensor_name="edge_273_adam_optimizer/gradients/conv2/add_grad/tuple/control_dependency_1", tensor_type=DT_FLOAT, _device="/job:ps/replica:0/task:0/device:GPU:0"]()]]
Code here
Libraries:
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nccl2/lib:/usr/local/cuda/extras/CUPTI/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export CUDA_HOME=/usr/local/cuda
Versions
CUDA
cat /usr/local/cuda/version.txt
CUDA Version 9.0.176
CUDA Patch Version 9.0.176.1
CUDA Patch Version 9.0.176.2
CUDA Patch Version 9.0.176.3
CUDA Patch Version 9.0.176.4
CuDNN
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 4
#define CUDNN_PATCHLEVEL 1
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h"
Similar:
https://github.com/tensorflow/tensorflow/issues/24828
Which TensorFlow and CUDA version combinations are compatible?
