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Why my wall time is very long? CPU times: 4min Wall time: 11min.? [on hold]
The 2019 Stack Overflow Developer Survey Results Are InWhy does my loss value start at approximately -10,000 and my accuracy not improve?Strange behavior in current Keras setting (tensorflow-1.7.0 Keras-2.1.5) when using CPUWhy Tensorflow does NOT quit when CUDA_ERROR_OUT_OF_MEMORYMoving from macbook (without GPU) to linux system with Titan V, only getting a 4x speedup, what am I doing wrong?what is the one hot encoding for cancer data classificationUnderstanding why my binary classification is approaching 50% accuracy using TensorFlow and KerasHow to use a NN architecture that is too big for GPU?Training model in Keras(TF backend) with GPUBetter training time using GTX 1050 than GTX TITAN X? (4GB vs. 12GB). I have very bad wall time using TITAN x?
$begingroup$
I am using a GPU: TITAN X for my project and Mask-Rcnn. Epoch 1/1
I don't know why I got a very long time in Wall time? What is wrong?
200/200 [==============================] - 461s 2s/step - loss: 1.7415 - rpn_class_loss: 0.0592 - rpn_bbox_loss: 0.4563 - mrcnn_class_loss: 0.2490 - mrcnn_bbox_loss: 0.5253 - mrcnn_mask_loss: 0.4517 - val_loss: 1.9419 - val_rpn_class_loss: 0.0657 - val_rpn_bbox_loss: 0.6273 - val_mrcnn_class_loss: 0.2827 - val_mrcnn_bbox_loss: 0.5468 - val_mrcnn_mask_loss: 0.4194
CPU times: user 4min 34s, sys: 7.73 s, total: 4min 42s
Wall time: 10min 32s
deep-learning tensorflow gpu nvidia
edited 9 hours ago
Ethan
703525
asked 9 hours ago
BadumBadum
487
$endgroup$
put on hold as too broad by Toros91, Stephen Rauch♦ 3 hours ago
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
add a comment |
$begingroup$
I am using a GPU: TITAN X for my project and Mask-Rcnn. Epoch 1/1
I don't know why I got a very long time in Wall time? What is wrong?
200/200 [==============================] - 461s 2s/step - loss: 1.7415 - rpn_class_loss: 0.0592 - rpn_bbox_loss: 0.4563 - mrcnn_class_loss: 0.2490 - mrcnn_bbox_loss: 0.5253 - mrcnn_mask_loss: 0.4517 - val_loss: 1.9419 - val_rpn_class_loss: 0.0657 - val_rpn_bbox_loss: 0.6273 - val_mrcnn_class_loss: 0.2827 - val_mrcnn_bbox_loss: 0.5468 - val_mrcnn_mask_loss: 0.4194
CPU times: user 4min 34s, sys: 7.73 s, total: 4min 42s
Wall time: 10min 32s
deep-learning tensorflow gpu nvidia
edited 9 hours ago
Ethan
703525
asked 9 hours ago
BadumBadum
487
$endgroup$
put on hold as too broad by Toros91, Stephen Rauch♦ 3 hours ago
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
1
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago
add a comment |
$begingroup$
I am using a GPU: TITAN X for my project and Mask-Rcnn. Epoch 1/1
I don't know why I got a very long time in Wall time? What is wrong?
200/200 [==============================] - 461s 2s/step - loss: 1.7415 - rpn_class_loss: 0.0592 - rpn_bbox_loss: 0.4563 - mrcnn_class_loss: 0.2490 - mrcnn_bbox_loss: 0.5253 - mrcnn_mask_loss: 0.4517 - val_loss: 1.9419 - val_rpn_class_loss: 0.0657 - val_rpn_bbox_loss: 0.6273 - val_mrcnn_class_loss: 0.2827 - val_mrcnn_bbox_loss: 0.5468 - val_mrcnn_mask_loss: 0.4194
CPU times: user 4min 34s, sys: 7.73 s, total: 4min 42s
Wall time: 10min 32s
deep-learning tensorflow gpu nvidia
edited 9 hours ago
Ethan
703525
asked 9 hours ago
BadumBadum
487
$endgroup$
I am using a GPU: TITAN X for my project and Mask-Rcnn. Epoch 1/1
I don't know why I got a very long time in Wall time? What is wrong?
200/200 [==============================] - 461s 2s/step - loss: 1.7415 - rpn_class_loss: 0.0592 - rpn_bbox_loss: 0.4563 - mrcnn_class_loss: 0.2490 - mrcnn_bbox_loss: 0.5253 - mrcnn_mask_loss: 0.4517 - val_loss: 1.9419 - val_rpn_class_loss: 0.0657 - val_rpn_bbox_loss: 0.6273 - val_mrcnn_class_loss: 0.2827 - val_mrcnn_bbox_loss: 0.5468 - val_mrcnn_mask_loss: 0.4194
CPU times: user 4min 34s, sys: 7.73 s, total: 4min 42s
Wall time: 10min 32s
deep-learning tensorflow gpu nvidia
deep-learning tensorflow gpu nvidia
edited 9 hours ago
Ethan
703525
asked 9 hours ago
BadumBadum
487
edited 9 hours ago
Ethan
703525
asked 9 hours ago
BadumBadum
487
edited 9 hours ago
Ethan
703525
edited 9 hours ago
Ethan
703525
edited 9 hours ago
Ethan
703525
703525
asked 9 hours ago
BadumBadum
487
asked 9 hours ago
BadumBadum
487
asked 9 hours ago
BadumBadum
487
487
put on hold as too broad by Toros91, Stephen Rauch♦ 3 hours ago
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
put on hold as too broad by Toros91, Stephen Rauch♦ 3 hours ago
Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
1
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago
add a comment |
$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
1
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago
$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
1
1
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago
add a comment |
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$begingroup$
Possible duplicate of Why my tensorflow is very slow?
$endgroup$
– Simon Larsson
8 hours ago
1
$begingroup$
Wall time is always going to be larger than CPU time since Wall Time = CPU(Which is actually User-cpu time) + Other Processes Time, if that time is that much bigger you can try to dedicate threads to your process or increase its priority. Also this is not the proper place to ask this question as its emphasis is not in data science but computer science
$endgroup$
– Pedro Henrique Monforte
4 hours ago