It doesn't matter if I install miniforge or mamba, directly or through brew, when I try to fit the sample model from https://developer.apple.com/metal/tensorflow-plugin/, even with a simple sequential model, I always get this error. Is there any workaround on this? I'll appreciate any help, thanks! 2022-12-10 11:18:19.941623: W tensorflow/tsl/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz 2022-12-10 11:18:20.427283: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:114] Plugin optimizer for device_type GPU is enabled. 2022-12-10 11:18:21.222950: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 2022-12-10 11:18:21.223003: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 2022-12-10 11:18:21.363366: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 2022-12-10 11:18:21.364757: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 2022-12-10 11:18:21.388739: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 2022-12-10 11:18:21.388757: W tensorflow/core/framework/op_kernel.cc:1830] OP_REQUIRES failed at xla_ops.cc:418 : NOT_FOUND: could not find registered platform with id: 0x28edf1f90 NotFoundError Traceback (most recent call last) Cell In[25], line 2 1 model = create_model() ----> 2 history = model.fit(Xf_train, yf_train, epochs=3, batch_size=64); File /opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/utils/traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs) 67 filtered_tb = _process_traceback_frames(e.traceback) 68 # To get the full stack trace, call: 69 # tf.debugging.disable_traceback_filtering() ---> 70 raise e.with_traceback(filtered_tb) from None 71 finally: 72 del filtered_tb File /opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/tensorflow/python/eager/execute.py:52, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name) 50 try: 51 ctx.ensure_initialized() ---> 52 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name, 53 inputs, attrs, num_outputs) 54 except core._NotOkStatusException as e: 55 if name is not None: NotFoundError: Graph execution error: Detected at node 'StatefulPartitionedCall_4' defined at (most recent call last): File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/runpy.py", line 86, in _run_code exec(code, run_globals) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/ipykernel_launcher.py", line 17, in app.launch_new_instance() File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/traitlets/config/application.py", line 992, in launch_instance app.start() File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/ipykernel/kernelapp.py", line 711, in start self.io_loop.start() File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/tornado/platform/asyncio.py", line 215, in start self.asyncio_loop.run_forever() File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/asyncio/base_events.py", line 603, in run_forever self._run_once() File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/asyncio/base_events.py", line 1899, in _run_once handle._run() ... File "/var/folders/f9/bp40pn0d401d974fy48dxm8h0000gn/T/ipykernel_63636/3393788193.py", line 2, in <module> history = model.fit(Xf_train, yf_train, epochs=3, batch_size=64); File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler return fn(*args, **kwargs) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/engine/training.py", line 1650, in fit tmp_logs = self.train_function(iterator) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in train_function return step_function(self, iterator) ...... File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/engine/training.py", line 1222, in run_step outputs = model.train_step(data) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/engine/training.py", line 1027, in train_step self.optimizer.minimize(loss, self.trainable_variables, tape=tape) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 527, in minimize self.apply_gradients(grads_and_vars) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1140, in apply_gradients return super().apply_gradients(grads_and_vars, name=name) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 634, in apply_gradients iteration = self._internal_apply_gradients(grads_and_vars) File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1166, in _internal_apply_gradients return tf.__internal__.distribute.interim.maybe_merge_call( File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1216, in _distributed_apply_gradients_fn distribution.extended.update( File "/opt/homebrew/Caskroom/miniforge/base/envs/tf/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1211, in apply_grad_to_update_var return self._update_step_xla(grad, var, id(self._var_key(var))) Node: 'StatefulPartitionedCall_4' could not find registered platform with id: 0x28edf1f90 [[{{node StatefulPartitionedCall_4}}]] [Op:__inference_train_function_1241]