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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
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