Comments (2)
mrlzla
commented on June 24, 2024
I ran demo.py on CPU mode and GPU mode and I figured out that this model was faster on CPU rather GPU. What did I do wrong?
I just changed line 21 in squeezeDet.py:
with tf.device('/gpu:{}'.format(gpu_id)):
with:
with tf.device('/cpu:0'):
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Timen
commented on June 24, 2024
Could you provide some more information, like the specs of your machine, which tensorflow version you are using and maybe any errors or abnormalities you are seeing between running cpu vs gpu.
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Related Issues (20)
- Gpu occupancy rate
- where is base_model_config.py?
- Will random initialization parameters have no precision? HOT 1
- Fine-tune SqueezeDet from sparse labels
- How to do hard negative mining HOT 1
- Publish frozen model? HOT 3
- Problem converting to TFLite HOT 3
- low GPU usage
- 8-bit weights
- Deploying squeezeDet on mobile HOT 3
- How to convert checkpoint of squeezedet to frozen graph for tflite conversion?! HOT 1
- Image resolution problem
- How to run demo.py using train.py checkpoint model HOT 1
- Train with different size and Inference with different size.
- Fine tuning with the model
- Train error and Eval error
- Using negative samples for training.
- print weights per layer during training
- Performance issue in src/eval.py (by P3) HOT 1
- The loss plateaus after 100 Epoch
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