I am trying to run the notebook Transformer model for language understanding https://www.tensorflow.org/text/tutorials/transformer from the TensorFlow website.
Although I get the message "Plugin optimizer for device_type GPU is enabled", the GPU is not used. The code uses no more than 30% of the GPU and is slower than for the case that I use only the CPU.
When I am running a code with CNNs, it uses 100% of the GPU.
I believe this is related to a previous post of mine https://developer.apple.com/forums/thread/709142 that had LSTMs. The transformer code does not have LSTMs though.
I am using MacBook Pro 14 (10 CPU cores, 16 GPU cores) and TensorFlow-macos 2.8 with TensorFlow-metal 0.5.0. I face the same problem for TensorFlow-macos 2.9.2 too.
My environment has:
tensorflow-macos 2.8.0
tensorflow-metal 0.5.0
tensorflow-text 2.8.1
tensorflow-datasets 4.6.0
tensorflow-deps 2.8.0
tensorflow-hub 0.12.0
tensorflow-metadata 1.8.0
Any idea why the GPU is not used for more than 30% although it is enabled?
Selecting any option will automatically load the page
Post
Replies
Boosts
Views
Activity
I am trying to run the notebook https://www.tensorflow.org/text/tutorials/text_classification_rnn from the TensorFlow website.
The code has LSTM and Bidirectional layers
When the GPU is enabled the time is 56 minutes/epoch.
When I am only using the CPU is 264 seconds/epoch.
I am using MacBook Pro 14 (10 CPU cores, 16 GPU cores) and TensorFlow-macos 2.8 with TensorFlow-metal 0.5.0. I face the same problem for TensorFlow-macos 2.9 too.
My environment has:
tensorflow-macos 2.8.0
tensorflow-metal 0.5.0
tensorflow-text 2.8.1
tensorflow-datasets 4.6.0
tensorflow-deps 2.8.0
tensorflow-hub 0.12.0
tensorflow-metadata 1.8.0
When I am using CNNs the GPU is fully enabled and 3-4 times faster than when only using the CPU.
Any idea where is the problem when using LSTMs and Bidirectional?