# Is, or will be, GPU accelerating supported on Mac device? **URL:** \ **Category:** 🤗Accelerate\ **Created:** [June 28, 2021, 6:08pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554 "2021-06-28T18:08:50Z")\ **Posts on this page:** 9\ **Page:** 1
**Author:** ![hawkiyc](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/hawkiyc/32/33085_2.png) [@hawkiyc](https://discuss.huggingface.co/u/hawkiyc)\ **Post date:** [June 28, 2021, 6:08pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/1 "2021-06-28T18:08:51Z")
Dear all Developers, Apple has just announced the [TensorFlow-Metal package](https://developer.apple.com/metal/tensorflow-plugin/) for GPU/NPU accelerating on Mac devices. Therefore, I am wondering that if it is feasible to solve NLP tasks with HuggingFace transformers through TensorFlow-macOS and TensorFlow-Metal. To figure it out, I installed TensorFlow-macOS, TensorFlow-Metal, and HuggingFace on my local device. Then, I ran the testing code to check everything installed correctly, and here was what I got. ![截圖 2021-06-29 00.53.46](https://us1.discourse-cdn.com/hellohellohello/original/2X/b/b5e47f2a84a1dd5073f4429f942331fdc1f2772c.jpeg) It seems everything works fine. But, I get the following error while I attempt to fine-tune a BERT model. ```auto InvalidArgumentError: Cannot assign a device for operation tf_bert_for_sequence_classification/bert/embeddings/Gather: Could not satisfy explicit device specification '' because the node {{colocation_node tf_bert_for_sequence_classification/bert/embeddings/Gather}} was colocated with a group of nodes that required incompatible device '/job:localhost/replica:0/task:0/device:GPU:0'. All available devices [/job:localhost/replica:0/task:0/device:CPU:0, /job:localhost/replica:0/task:0/device:GPU:0]. Colocation Debug Info: Colocation group had the following types and supported devices: Root Member(assigned_device_name_index_=2 requested_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' assigned_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' resource_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' supported_device_types_=[CPU] possible_devices_=[] RealDiv: GPU CPU Sqrt: GPU CPU UnsortedSegmentSum: CPU AssignVariableOp: GPU CPU AssignSubVariableOp: GPU CPU ReadVariableOp: GPU CPU StridedSlice: GPU CPU NoOp: GPU CPU Mul: GPU CPU Shape: GPU CPU _Arg: GPU CPU ResourceScatterAdd: GPU CPU Unique: CPU AddV2: GPU CPU ResourceGather: GPU CPU Const: GPU CPU ``` So, I checked that if TensorFlow detected GPU correctly, and here is what I had. ```auto tf.test.is_gpu_available() WARNING:tensorflow:From :1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.config.list_physical_devices('GPU')` instead. WARNING:tensorflow:From :1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.config.list_physical_devices('GPU')` instead. 2021-06-29 01:56:25.862829: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2021-06-29 01:56:25.862893: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: ) Out[2]: True ``` It looks like that HuggingFace is unable to detect the proper device. Is there any way to solve this issue, or would be solved in near future? I appreciate and looking forward to your kind assistance. Sincerely, hawkiyc ---
**Author:** ![Neel-Gupta](https://avatars.discourse-cdn.com/v4/letter/n/f1d935/32.png) [@Neel-Gupta](https://discuss.huggingface.co/u/Neel-Gupta)\ **Post date:** [June 28, 2021, 6:11pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/2 "2021-06-28T18:11:25Z")
> [@hawkiyc](#): > > `(/device:GPU:0 with 0 MB memory)` It doesn’t look like whatever device TF recongizes is actually usable - perhaps that may be the reason why HF can’t leverage it? if you can’t allocate tensors to GPU then there is little scope of executing ops there. ---
**Author:** ![hawkiyc](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/hawkiyc/32/33085_2.png) [@hawkiyc](https://discuss.huggingface.co/u/hawkiyc)\ **Post date:** [June 28, 2021, 6:26pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/3 "2021-06-28T18:26:25Z")
Dear Neel, I have tested neural network models with TensorFlow only, and everything works fine. So, I think TF indeed detects and uses my GPU. Sincerely, hawkiyc ---
**Author:** ![lewtun](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/lewtun/32/30995_2.png) [@lewtun](https://discuss.huggingface.co/u/lewtun)\ **Post date:** [June 28, 2021, 6:32pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/4 "2021-06-28T18:32:50Z")
cc @Rocketknight1 who might have some insights on running TF + HF on M1 chips ---
**Author:** ![Neel-Gupta](https://avatars.discourse-cdn.com/v4/letter/n/f1d935/32.png) [@Neel-Gupta](https://discuss.huggingface.co/u/Neel-Gupta)\ **Post date:** [June 28, 2021, 6:40pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/5 "2021-06-28T18:40:02Z")
> [@hawkiyc](#): > > I have tested neural network models with TensorFlow only, and everything works fine. So, I think TF indeed detects and uses my GPU. unfortunately, its not really a conclusive test. I admit I haven’t used an M1 device, but as long as the framework can use a device, I don’t see why Huggingface won’t be able to. Could you try doing a speed comparison for training models to ensure it’s not running on CPU? Another thing - in your image > Metal Device set to: AMD Radeo Pro 5500M Am I correct in assuming that you want to use an AMD GPU, not via the M1 processor? ---
**Author:** ![hawkiyc](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/hawkiyc/32/33085_2.png) [@hawkiyc](https://discuss.huggingface.co/u/hawkiyc)\ **Post date:** [June 28, 2021, 7:56pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/6 "2021-06-28T19:56:43Z")
Dear Neel, > [@Neel-Gupta](#): > > Metal Device set to: AMD Radeo Pro 5500M I am sorry that I forgot to mention that I am using MacBook Pro 16". And this machine is intel CPU & AMD gpu, not M1. I built a CNN model to test the device with the cifar10 dataset. Here is time-consuming for each epoch with AMD GPU, ```auto 112] Plugin optimizer for device_type GPU is enabled. 1667/1667 [==============================] - 49s 27ms/step - loss: 1.3462 - sparse_categorical_accuracy: 0.5124 Epoch 2/5 1667/1667 [==============================] - 47s 28ms/step - loss: 0.8867 - sparse_categorical_accuracy: 0.6872 Epoch 3/5 1667/1667 [==============================] - 50s 30ms/step - loss: 0.7183 - sparse_categorical_accuracy: 0.7503 Epoch 4/5 1667/1667 [==============================] - 56s 33ms/step - loss: 0.6007 - sparse_categorical_accuracy: 0.7901 Epoch 5/5 1667/1667 [==============================] - 53s 32ms/step - loss: 0.5020 - sparse_categorical_accuracy: 0.8227 Out[3]: ``` And here is for CPU, ```auto Epoch 1/5 1667/1667 [==============================] - 285s 170ms/step - loss: 1.3755 - sparse_categorical_accuracy: 0.5024 Epoch 2/5 1667/1667 [==============================] - 283s 170ms/step - loss: 0.9136 - sparse_categorical_accuracy: 0.6782 Epoch 3/5 23/1667 [..............................] - ETA: 4:38 - loss: 0.7261 - sparse_categorical_accuracy: 0.7333 --------------------------------------------------------------------------- KeyboardInterrupt Traceback (most recent call last) ``` Sincerely, ---
**Author:** ![Neel-Gupta](https://avatars.discourse-cdn.com/v4/letter/n/f1d935/32.png) [@Neel-Gupta](https://discuss.huggingface.co/u/Neel-Gupta)\ **Post date:** [June 28, 2021, 10:13pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/7 "2021-06-28T22:13:19Z")
ahh, so you are using `tensorflow-metal` to accelerate the training on AMD GPUs. Well, I am sure its not very different than the standard tensorflow we use, unfortunately, it doesn’t seem to be open source. I am not from Huggingface, so I can’t clarify but having a fork not being open source makes it quite difficult to work it; hence the lack of integration of HF+TF\_metal. It doesn’t make sense for them to invest in a framework used by so few. You would have to do customizations yourself and figure out how to do that - which I think is a pretty daunting task. Someone else might be able to explain better I suppose; I don’t know much about the Mac ecosystem unfortunately 🤗 ---
**Author:** ![hawkiyc](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/hawkiyc/32/33085_2.png) [@hawkiyc](https://discuss.huggingface.co/u/hawkiyc)\ **Post date:** [June 29, 2021, 11:27am UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/8 "2021-06-29T11:27:00Z")
Dear All, I have made another BERT model with TensorFlow-Hub only, and I got the same error as before. ```auto InvalidArgumentError: Cannot assign a device for operation AdamWeightDecay/AdamWeightDecay/update/Unique: Could not satisfy explicit device specification '/job:localhost/replica:0/task:0/device:GPU:0' because no supported kernel for GPU devices is available. Colocation Debug Info: Colocation group had the following types and supported devices: Root Member(assigned_device_name_index_=2 requested_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' assigned_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' resource_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' supported_device_types_=[CPU] possible_devices_=[] RealDiv: GPU CPU ResourceGather: GPU CPU AddV2: GPU CPU Sqrt: GPU CPU Unique: CPU ResourceScatterAdd: GPU CPU UnsortedSegmentSum: CPU AssignVariableOp: GPU CPU AssignSubVariableOp: GPU CPU ReadVariableOp: GPU CPU NoOp: GPU CPU Mul: GPU CPU Shape: GPU CPU Identity: GPU CPU StridedSlice: GPU CPU _Arg: GPU CPU Const: GPU CPU ``` So, this issue should from TensorFlow-Hub, not HuggingFace. I will report this issue to Apple Developer Forum. Anyway, thank you all good fellows. Sincerely, hawkiyc ---
**Author:** ![dominykas](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/dominykas/32/4244_2.png) [@dominykas](https://discuss.huggingface.co/u/dominykas)\ **Post date:** [March 15, 2022, 4:50pm UTC](https://discuss.huggingface.co/t/is-or-will-be-gpu-accelerating-supported-on-mac-device/7554/9 "2022-03-15T16:50:53Z")
Hi, hawkiyc. Any luck with fixing it or maybe got a response from Apple? 🙂