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Working Environment MacBook Pro 14' with M2-Pro chip macOS Sonoma 14.0 Python 3.11.4 tensorflow 2.14.0, tensorflow-macos 2.14.0, tensorflow-metal 1.1.0 Issue Description Hi there! I met an issue when working around with Keras' TextVectorization preprocessing layer. text_vectorization = keras.layers.TextVectorization(output_mode="tf_idf") text_vectorization.adapt(ds.map(lambda x: x['title'])) The inputs are string contents. And here is the trackback: --------------------------------------------------------------------------- NotFoundError Traceback (most recent call last) /Users/ken/Workspaces/MLE101/tfrs101/preprocess.ipynb Cell 13 line 3 1 # with tf.device('/CPU:0'): 2 text_vectorization = keras.layers.TextVectorization(output_mode="tf_idf") ----> 3 text_vectorization.adapt(ds.map(lambda x: x['title'])) File ~/miniconda3/envs/ds-101/lib/python3.11/site-packages/keras/src/layers/preprocessing/text_vectorization.py:473, in TextVectorization.adapt(self, data, batch_size, steps) 423 def adapt(self, data, batch_size=None, steps=None): 424 """Computes a vocabulary of string terms from tokens in a dataset. 425 426 Calling `adapt()` on a `TextVectorization` layer is an alternative to (...) 471 argument is not supported with array inputs. 472 """ --> 473 super().adapt(data, batch_size=batch_size, steps=steps) File ~/miniconda3/envs/ds-101/lib/python3.11/site-packages/keras/src/engine/base_preprocessing_layer.py:258, in PreprocessingLayer.adapt(self, data, batch_size, steps) 256 with data_handler.catch_stop_iteration(): 257 for _ in data_handler.steps(): --> 258 self._adapt_function(iterator) 259 if data_handler.should_sync: 260 context.async_wait() File ~/miniconda3/envs/ds-101/lib/python3.11/site-packages/tensorflow/python/util/traceback_utils.py:153, in filter_traceback.<locals>.error_handler(*args, **kwargs) 151 except Exception as e: 152 filtered_tb = _process_traceback_frames(e.__traceback__) --> 153 raise e.with_traceback(filtered_tb) from None 154 finally: 155 del filtered_tb File ~/miniconda3/envs/ds-101/lib/python3.11/site-packages/tensorflow/python/eager/execute.py:60, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name) 53 # Convert any objects of type core_types.Tensor to Tensor. 54 inputs = [ 55 tensor_conversion_registry.convert(t) 56 if isinstance(t, core_types.Tensor) 57 else t 58 for t in inputs 59 ] ---> 60 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name, 61 inputs, attrs, num_outputs) 62 except core._NotOkStatusException as e: 63 if name is not None: NotFoundError: Graph execution error: Detected at node StringSplit/stack defined at (most recent call last): ... No registered 'ExpandDims' OpKernel for 'GPU' devices compatible with node {{node StringSplit/stack}} (OpKernel was found, but attributes didn't match) Requested Attributes: T=DT_STRING, Tdim=DT_INT32, _XlaHasReferenceVars=false, _device="/job:localhost/replica:0/task:0/device:GPU:0" . Registered: device='XLA_CPU_JIT'; Tdim in [DT_INT32, DT_INT64]; T in [DT_FLOAT, DT_DOUBLE, DT_INT32, DT_UINT8, DT_INT16, DT_INT8, DT_COMPLEX64, DT_INT64, DT_BOOL, DT_QINT8, DT_QUINT8, DT_QINT32, DT_BFLOAT16, DT_UINT16, DT_COMPLEX128, DT_HALF, DT_UINT32, DT_UINT64, DT_FLOAT8_E5M2, DT_FLOAT8_E4M3FN] device='DEFAULT'; T in [DT_HALF]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_HALF]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_BFLOAT16]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_BFLOAT16]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_FLOAT]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_FLOAT]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_DOUBLE]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_DOUBLE]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_UINT64]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_UINT64]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_INT64]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_INT64]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_UINT32]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_UINT32]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_UINT16]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_UINT16]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_INT16]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_INT16]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_UINT8]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_UINT8]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_INT8]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_INT8]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_COMPLEX64]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_COMPLEX64]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_COMPLEX128]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_COMPLEX128]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_BOOL]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_BOOL]; Tdim in [DT_INT64] device='DEFAULT'; T in [DT_INT32]; Tdim in [DT_INT32] device='DEFAULT'; T in [DT_INT32]; Tdim in [DT_INT64] device='CPU'; Tdim in [DT_INT32] device='CPU'; Tdim in [DT_INT64] [[StringSplit/stack]] [Op:__inference_adapt_step_71204] I have to explicitly specify to use CPU to make it work - with tf.device('/CPU:0'): text_vectorization = keras.layers.TextVectorization(output_mode="tf_idf") text_vectorization.adapt(ds.map(lambda x: x['title'])) I have referred to this post: https://developer.apple.com/forums/thread/700108