Comments (4)
This package requires a newer version of tensorflow. It's currently set to use tf≥1.10
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Thansk for your answer , it is running now .
It takes a lot of the memory of gpu , but a low use of gpu-util.
Im using four gtx1080ti ,but when i enter the "make test" ,it tell me " OOM when allocating tensor with shape[512,64,31,125] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc"
Should I stop trainning and to test?
Look forward to your reply, thanks
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I've used the same device with no memory troubles in test. Odd.
You can reduce the batch size or run test on the CPU, since most of the computation (in test) happens there anyway. [That's why you'll have low GPU utilization.]
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I think I (belatedly) understand now that perhaps you're running the test while you're also doing training? If your trainer has claimed all of the GPUs, the tester won't have room to allocate memory, because tensorflow (by default) tries to allocate all the available memory.
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Related Issues (20)
- Training error HOT 9
- How to deal with single character input HOT 2
- Using Multiple GPU as a train_device HOT 3
- ctc_loss_calculator.cc Not a valid path HOT 3
- are there any pretrain model file HOT 3
- Input shapes: [72,357,1], [4] and with input tensors computed HOT 3
- It's possible to use a pre-trained model? HOT 1
- CuDnn 7.2.1 HOT 1
- get not good result, HOT 2
- FineTune ! HOT 3
- Model learns nothing about certain characters. HOT 1
- Fixed sequence length HOT 1
- Training Error when using my data HOT 1
- 0% GPU-Util when testing HOT 1
- Train on vertical patches HOT 1
- Question Regarding End Model HOT 3
- confidence on sess passing HOT 6
- How to convert .ckpt model to SavedModel .pb format for hosting with Tensorflow Model Serving? HOT 6
- How to batch inference? HOT 5
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