You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
(.venv) ub16c9@ub16c9-gpu:~/ub16_prj/QANet$ python config.py --mode train
Building model...
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/layers.py:52: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/model.py:134: calling softmax (from tensorflow.python.ops.nn_ops) with dim is deprecated and will be removed in a future version.
Instructions for updating:
dim is deprecated, use axis instead
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/model.py:174: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.
See tf.nn.softmax_cross_entropy_with_logits_v2.
Total number of trainable parameters: 788673
2018-12-29 11:14:48.345129: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-12-29 11:14:48.431530: 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
2018-12-29 11:14:48.431955: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6575
pciBusID: 0000:01:00.0
totalMemory: 10.92GiB freeMemory: 10.43GiB
2018-12-29 11:14:48.431971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2018-12-29 11:14:48.733045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-12-29 11:14:48.733079: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2018-12-29 11:14:48.733085: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2018-12-29 11:14:48.733318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10086 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-12-29 11:14:50.042331: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.174758: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.507489: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.691090: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.825623: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
55%|██████████████████████████████████████████████████████████████████████████████████████▏ | 32935/60000 [3:15:35<2:19:53, 3.22it/s] 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 53999/60000 [5:17:29<29:48, 3.36it/sException RuntimeError: RuntimeError('cannot join current thread',) in <object repr() failed> ignored██████████████████████████████████████████████████████████████████████| 328/328 [00:36<00:00, 9.07it/s]
(.venv) ub16c9@ub16c9-gpu:~/ub16_prj/QANet$
The text was updated successfully, but these errors were encountered:
(.venv) ub16c9@ub16c9-gpu:~/ub16_prj/QANet$ python config.py --mode train
Building model...
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/layers.py:52: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/model.py:134: calling softmax (from tensorflow.python.ops.nn_ops) with dim is deprecated and will be removed in a future version.
Instructions for updating:
dim is deprecated, use axis instead
WARNING:tensorflow:From /home/ub16c9/ub16_prj/QANet/model.py:174: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Future major versions of TensorFlow will allow gradients to flow
into the labels input on backprop by default.
See
tf.nn.softmax_cross_entropy_with_logits_v2
.Total number of trainable parameters: 788673
2018-12-29 11:14:48.345129: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-12-29 11:14:48.431530: 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
2018-12-29 11:14:48.431955: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6575
pciBusID: 0000:01:00.0
totalMemory: 10.92GiB freeMemory: 10.43GiB
2018-12-29 11:14:48.431971: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2018-12-29 11:14:48.733045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-12-29 11:14:48.733079: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2018-12-29 11:14:48.733085: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2018-12-29 11:14:48.733318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10086 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-12-29 11:14:50.042331: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.174758: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.507489: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.691090: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
2018-12-29 11:14:50.825623: W tensorflow/core/framework/allocator.cc:122] Allocation of 109906800 exceeds 10% of system memory.
55%|██████████████████████████████████████████████████████████████████████████████████████▏ | 32935/60000 [3:15:35<2:19:53, 3.22it/s] 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 53999/60000 [5:17:29<29:48, 3.36it/sException RuntimeError: RuntimeError('cannot join current thread',) in <object repr() failed> ignored██████████████████████████████████████████████████████████████████████| 328/328 [00:36<00:00, 9.07it/s]
(.venv) ub16c9@ub16c9-gpu:~/ub16_prj/QANet$
The text was updated successfully, but these errors were encountered: