时就是这种情况
我使用tensorflow，创建以下文件后，我得到下面的错误。我怀疑我提供了错误的输入类型，但我不知道如何将其更改为正确的表示。
dijkstra.py:
self.maze = tf.Variable(tf.zeros([64], dtype=tf.int32), name="grid")
print self.maze
if True :
self.grid_module = tf.load_op_library('d_grid_gpu.so')
with tf.Session('') as sess:
sess.run(tf.initialize_all_variables())
self.output = self.grid_module.grid_gpu(
self.maze
).eval()
d_grid_gpu。答:
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
using namespace tensorflow;
REGISTER_OP("GridGpu").Input("grid: int32").Output("prev: int32");
void run( int * in);
class DGridGpuOp : public OpKernel {
public:
explicit DGridGpuOp(OpKernelConstruction* context) : OpKernel(context) {
}
void Compute(OpKernelContext* context) override {
Tensor* prev_tensor = NULL;
Tensor grid_tensor = context->input(0);
auto grid = grid_tensor.flat<int32>();
OP_REQUIRES_OK(context, context->allocate_output(
0,
TensorShape({64}), &prev_tensor));
auto prev = prev_tensor->template flat<int32>();
run(grid.data());//
}
};
REGISTER_KERNEL_BUILDER(Name("GridGpu").Device(DEVICE_GPU), DGridGpuOp);
d_grid_gpu.cu。答:
#if GOOGLE_CUDA
#define EIGEN_USE_GPU
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include <stdio.h>
#define SIZE 10
__global__ void VectorAdd( int *in, int n)
{
int i = threadIdx.x;
if (i < n)
in[i] = in[i] + i;
}
void run( int * in){
VectorAdd<<< 1, SIZE >>>( in, SIZE);
/*
//these lines cause the segfault
//for (int i = 0; i < SIZE; i ++) {
// printf("%i, " , in[i]);
//}
*/
}
#endif
build script:
TF_INC=$(python -c 'import tensorflow as tf; print(tf.sysconfig.get_include())')
nvcc -std=c++11 -c -o d_grid_gpu.cu.o d_grid_gpu.cu.cc
-I $TF_INC -D GOOGLE_CUDA=1 -x cu -Xcompiler -fPIC --expt-relaxed-constexpr
g++ -std=c++11 -shared -o d_grid_gpu.so d_grid_gpu.cc
d_grid_gpu.cu.o -I $TF_INC -fPIC -lcudart -D_GLIBCXX_USE_CXX11_ABI=0 -L /usr/lib/x86_64-linux-gnu/
edit: I remove the old output.
我尝试了'add_one' op(从TF如何页面)，我想我得到了它的工作。这让我相信我的安装是OK的。这个例子可以编译。我想我只是不能正确注册，或者别的什么。欢迎任何帮助。
edit:我重新安装了tensorflow，现在错误有点不同
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally
simple dijkstra for tensorflow
<tensorflow.python.ops.variables.Variable object at 0x7fdec57c1b50>
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:925] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
I tensorflow/core/common_runtime/gpu/gpu_device.cc:951] Found device 0 with properties:
name: GeForce GTX 850M
major: 5 minor: 0 memoryClockRate (GHz) 0.9015
pciBusID 0000:0a:00.0
Total memory: 3.95GiB
Free memory: 3.64GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:972] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 850M, pci bus id: 0000:0a:00.0)
Traceback (most recent call last):
File "test_op.py", line 45, in <module>
d.eval()
File "/home/dave/workspace/awesome-tf/test_gpu/dijkstra.py", line 57, in eval
self.maze
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 559, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 3761, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 717, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 915, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 965, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 985, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors.FailedPreconditionError: Attempting to use uninitialized value grid
[[Node: grid/read = Identity[T=DT_INT32, _class=["loc:@grid"], _device="/job:localhost/replica:0/task:0/cpu:0"](grid)]]
Caused by op u'grid/read', defined at:
File "test_op.py", line 45, in <module>
d.eval()
File "/home/dave/workspace/awesome-tf/test_gpu/dijkstra.py", line 50, in eval
self.maze = tf.Variable(tf.zeros([64], dtype=tf.int32), name="grid")
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 215, in __init__
dtype=dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 327, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 1128, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 749, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2380, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1298, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value grid
[[Node: grid/read = Identity[T=DT_INT32, _class=["loc:@grid"], _device="/job:localhost/replica:0/task:0/cpu:0"](grid)]]
有时这是我的输出:
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally
simple dijkstra for tensorflow
<tensorflow.python.ops.variables.Variable object at 0x7fba5d0dafd0>
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:925] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
I tensorflow/core/common_runtime/gpu/gpu_device.cc:951] Found device 0 with properties:
name: GeForce GTX 850M
major: 5 minor: 0 memoryClockRate (GHz) 0.9015
pciBusID 0000:0a:00.0
Total memory: 3.95GiB
Free memory: 3.67GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:972] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 850M, pci bus id: 0000:0a:00.0)
Segmentation fault (core dumped)
当我使用initialize_all_variables()
您可能想使用tf.initialize_all_variables进行初始化，例如:
with tf.Session() as sess:
sess.run(tf.initialize_all_variables())