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mldl@mldlUB1604:~/ub16_prj/RWMN$ python train.py
2018-01-16 22:21:50.274948: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274975: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274983: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274989: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274995: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.351769: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-01-16 22:21:50.352033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: GeForce GTX 950M
major: 5 minor: 0 memoryClockRate (GHz) 1.124
pciBusID 0000:01:00.0
Total memory: 3.95GiB
Free memory: 2.76GiB
2018-01-16 22:21:50.352051: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2018-01-16 22:21:50.352057: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y
2018-01-16 22:21:50.352064: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:01:00.0)
Variables: name (type shape) [size]
Total size of variables: 0
Total bytes of variables: 0
memory_write/query_w:0
memory_write/query_b:0
Exception in thread Thread-7:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
File "/home/mldl/ub16_prj/RWMN/custom_input_ops.py", line 80, in thread_main
for mini_batch in self.iterator():
File "/home/mldl/ub16_prj/RWMN/custom_input_ops.py", line 50, in iterator
movie_index = np.random.choice(self.num_movie, 1)
File "mtrand.pyx", line 1104, in mtrand.RandomState.choice (numpy/random/mtrand/mtrand.c:17062)
ValueError: a must be greater than 0
The text was updated successfully, but these errors were encountered:
mldl@mldlUB1604:~/ub16_prj/RWMN$ python train.py
2018-01-16 22:21:50.274948: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274975: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274983: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274989: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.274995: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2018-01-16 22:21:50.351769: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-01-16 22:21:50.352033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:887] Found device 0 with properties:
name: GeForce GTX 950M
major: 5 minor: 0 memoryClockRate (GHz) 1.124
pciBusID 0000:01:00.0
Total memory: 3.95GiB
Free memory: 2.76GiB
2018-01-16 22:21:50.352051: I tensorflow/core/common_runtime/gpu/gpu_device.cc:908] DMA: 0
2018-01-16 22:21:50.352057: I tensorflow/core/common_runtime/gpu/gpu_device.cc:918] 0: Y
2018-01-16 22:21:50.352064: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:01:00.0)
Variables: name (type shape) [size]
Total size of variables: 0
Total bytes of variables: 0
memory_write/query_w:0
memory_write/query_b:0
Exception in thread Thread-7:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
File "/home/mldl/ub16_prj/RWMN/custom_input_ops.py", line 80, in thread_main
for mini_batch in self.iterator():
File "/home/mldl/ub16_prj/RWMN/custom_input_ops.py", line 50, in iterator
movie_index = np.random.choice(self.num_movie, 1)
File "mtrand.pyx", line 1104, in mtrand.RandomState.choice (numpy/random/mtrand/mtrand.c:17062)
ValueError: a must be greater than 0
The text was updated successfully, but these errors were encountered: