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Hi, I am using a Mac with M1 Pro. I want to use RandomCrop from tensorflow.keras.layers but while training I get the error below. If I understood correctly, it seems that RngReadAndSkip is not implemented for the GPU. InvalidArgumentError: Cannot assign a device for operation model/data_augmentation/random_crop/cond/model_data_augmentation_random_crop_cond_input_1/_6: Could not satisfy explicit device specification '' because the node {{colocation_node model/data_augmentation/random_crop/cond/model_data_augmentation_random_crop_cond_input_1/_6}} 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_=[] RngReadAndSkip: CPU Identity: GPU CPU Switch: GPU CPU _Arg: GPU CPU Colocation members, user-requested devices, and framework assigned devices, if any: model_data_augmentation_random_crop_cond_input_1 (_Arg) framework assigned device=/job:localhost/replica:0/task:0/device:GPU:0 model/data_augmentation/random_crop/cond/model_data_augmentation_random_crop_cond_input_1/_6 (Switch) Func/model/data_augmentation/random_crop/cond/then/_0/input/_47 (Identity) model/data_augmentation/random_crop/cond/then/_0/model/data_augmentation/random_crop/cond/stateful_uniform/RngReadAndSkip (RngReadAndSkip) Func/model/data_augmentation/random_crop/cond/else/_1/input/_52 (Identity) Python version: $ python --version --version Python 3.8.13 (default, Mar 28 2022, 06:13:39) [Clang 12.0.0 ] Libraries used: $ conda list | grep tensorflow tensorflow-addons 0.17.0 pypi_0 pypi tensorflow-deps 2.9.0 0 apple tensorflow-estimator 2.9.0 pypi_0 pypi tensorflow-macos 2.9.2 pypi_0 pypi tensorflow-metal 0.5.0 pypi_0 pypi Is there any workaround? Or anything I can do to help fixing this? Thanks