Dear All, I am a Data Scientist and waiting for GPU accelerating for years, and I am thrilled while Apple announced it will come at MacOS 12. linkText And so, I updated my OS to Monterey Beta and tried to install TensorFlow-Metal a few days ago. However, all installing instruction commands not work at all. After that, I looked into pypi.org and found out there are whl files for TensorFlow-macos and TensorFlow-metal. So, I tried to pip install both whl files. Yet, noting work again. Here is the screenshot for installing. I would very much appreciate if you can help me to solve this issue. Sincerely,

Dear All, There were years waiting for GPU acceleration for Mac users, and the frameworks were finally released this year. After some testing, I found out that the NLP task isn’t supported in the previous versions and made a report in 'FB9220496'. Then I was informed that this issue would be fixed in the next versions. So, I updated my frameworks immediately when the latest versions were released. However, I am very disappointed and frustrated because the latest frameworks cannot work at all. IDE Kernel always crashes when I am trying to train any model. Nevertheless, I attached the copy of my env in the .yaml file, so you should be able to reproduce this issue very easily. Here is the link of the .yaml file https://www.icloud.com/iclouddrive/0Yhr444NAqu6oD8qxOfKriY-A#env%5Fmac%5Ftf Besides that, please also note that I only update TesnorFlow-macos and TensorFlow-metal. And this env was fine except for NLP tasks before I update the frameworks. Could you please kindly look into this issue and solve it, thank you very much. BTW, the IDE which I use is spyder 5.1.5. Though IDE should not be the reason for crashes. I appreciate your time and looking forward to your prompt reply. Sincerely, Gavin

Dear All Developers, After macOS 12 Beta 3, there is a malfunction while adding a new tab or open a website in the new tab on Safari. The new tab is indeed created but not showed on top, and you have to click another tab for showing which one you just created. It isn't a big bug, but very annoying. Have anyone face this bug too? For more information, I have upload clips about this issue in the following google drive links, please find more detail in them. https://drive.google.com/file/d/1snH74s5H4aLf5ISzfXYmz9IRGfR-u_2G/view?usp=sharing https://drive.google.com/file/d/1jd_LMVh6ZENrrbZSEZiJahKOuNYi3979/view?usp=sharing Sincerely, hawkiyc

Dear All Developers, I have reported an issue about the HuggingFace package on 683992. In the beginning, I thought the problem is from HuggingFace. However, I found out it seems results from TensorFlow-Hub after some further tests. Here is the thing, I made a fine-tuning BERT model with TF and TF-Hub only. And I got the same error as before. Here is the detail about the error. 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, obviously, there is something wrong with the TF part and I don't think there is a quick solution. As transformers and related models are so powerful in the NLP area, it is a great shame that if we cannot solving NLP tasks with GPU accelerating. I will raise this issue on Feedback Assistant App too, and please comment here if you would also like Apple to solve this issue. Sincerely, hawkiyc

Dear All Developers, It is so great that we finally have TF-macOS and TF-Metal for GPU/NPU accelerating. After some tests, it looks like everything works well. So, I am wondering that if it is possible to solve NLP tasks with HuggingFace via TF-Metal for GPU accelerating. To figure it out, I installed all packages we need and ran the testing code. What I got is showing here. So far so good, right? However, it pops out an error while I attempt to fine-tune a BERT model. 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 It looks like that GPU is not assigned correctly, therefore, I checked if GPU is detected by TensorFlow. And here is the GPU info. from TensorFlow. WARNING:tensorflow:From <ipython-input-2-17bb7203622b>: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 <ipython-input-2-17bb7203622b>: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: <undefined>) Out[2]: True Obviously, the problem resulted from HuggingFace. I do know that it is not Apple's responsibility to packages other than TF-macOS and TF-Metal, I am just curious that if anyone has a solution about it here. Sincerely, hawkiyc