I’m unsure whether I can use CUDA 10.0 on GTX860M, if not, this means I cannot use TF 2.0. Recently I encountered this error, which was not present while I use the CPU version of TF 2.0
2019-12-12 15:42:27.272181: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll
2019-12-12 15:44:02.738014: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2019-12-12 15:44:03.021713: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 860M major: 5 minor: 0 memoryClockRate(GHz): 1.0195
pciBusID: 0000:01:00.0
2019-12-12 15:44:03.022991: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-12-12 15:44:03.026364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-12 15:44:03.034081: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2019-12-12 15:44:03.046229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: GeForce GTX 860M major: 5 minor: 0 memoryClockRate(GHz): 1.0195
pciBusID: 0000:01:00.0
2019-12-12 15:44:03.047017: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-12-12 15:44:03.049190: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-12 15:44:08.408388: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-12 15:44:08.408802: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-12 15:44:08.409050: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-12 15:44:08.415573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1376 MB memory) -> physical GPU (device: 0, name: GeForce GTX 860M, pci bus id: 0000:01:00.0, compute capability: 5.0)
2019-12-12 15:44:15.865016: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at resource_variable_ops.cc:703 : Resource exhausted: OOM when allocating tensor with shape[39015,100,300] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu
I wonder why this allocation happened on CPU rather than GPU.