86 bert_history = bert_model.fit(
87 train_ds,
88 validation_data=test_ds,
89 epochs=3,
90 verbose=1
报错:InvalidArgumentError: Graph execution error:
Detected at node 'tf_bert_for_sequence_classification/bert/embeddings/assert_less/Assert/Assert' defined at (most recent call last):
File "D:\Anaconda\envs\pytorch1\lib\runpy.py", line 192, in _run_module_as_main
return _run_code(code, main_globals, None,
File "D:\Anaconda\envs\pytorch1\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel_launcher.py", line 17, in <module>
app.launch_new_instance()
File "D:\Anaconda\envs\pytorch1\lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
app.start()
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\kernelapp.py", line 701, in start
self.io_loop.start()
File "D:\Anaconda\envs\pytorch1\lib\site-packages\tornado\platform\asyncio.py", line 205, in start
self.asyncio_loop.run_forever()
File "D:\Anaconda\envs\pytorch1\lib\asyncio\windows_events.py", line 316, in run_forever
super().run_forever()
File "D:\Anaconda\envs\pytorch1\lib\asyncio\base_events.py", line 563, in run_forever
self._run_once()
File "D:\Anaconda\envs\pytorch1\lib\asyncio\base_events.py", line 1844, in _run_once
handle._run()
File "D:\Anaconda\envs\pytorch1\lib\asyncio\events.py", line 81, in _run
self._context.run(self._callback, *self._args)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\kernelbase.py", line 534, in dispatch_queue
await self.process_one()
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\kernelbase.py", line 523, in process_one
await dispatch(*args)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\kernelbase.py", line 429, in dispatch_shell
await result
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
reply_content = await reply_content
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\ipkernel.py", line 429, in do_execute
res = shell.run_cell(
File "D:\Anaconda\envs\pytorch1\lib\site-packages\ipykernel\zmqshell.py", line 549, in run_cell
return super().run_cell(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\interactiveshell.py", line 3009, in run_cell
result = self._run_cell(
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\interactiveshell.py", line 3064, in _run_cell
result = runner(coro)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\async_helpers.py", line 129, in _pseudo_sync_runner
coro.send(None)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\interactiveshell.py", line 3269, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\interactiveshell.py", line 3448, in run_ast_nodes
if await self.run_code(code, result, async_=asy):
File "D:\Anaconda\envs\pytorch1\lib\site-packages\IPython\core\interactiveshell.py", line 3508, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "C:\Users\豆崽\AppData\Local\Temp\ipykernel_20320\247762855.py", line 86, in <module>
bert_history = bert_model.fit(
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\modeling_tf_utils.py", line 1229, in fit
return super().fit(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\training.py", line 1742, in fit
tmp_logs = self.train_function(iterator)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\training.py", line 1338, in train_function
return step_function(self, iterator)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\training.py", line 1322, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\training.py", line 1303, in run_step
outputs = model.train_step(data)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\modeling_tf_utils.py", line 1672, in train_step
y_pred = self(x, training=True)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\training.py", line 569, in __call__
return super().__call__(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\base_layer.py", line 1150, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\modeling_tf_utils.py", line 1734, in run_call_with_unpacked_inputs
if not self._using_dummy_loss and parse(tf.__version__) < parse("2.11.0"):
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\models\bert\modeling_tf_bert.py", line 1746, in call
outputs = self.bert(
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\base_layer.py", line 1150, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\modeling_tf_utils.py", line 1734, in run_call_with_unpacked_inputs
if not self._using_dummy_loss and parse(tf.__version__) < parse("2.11.0"):
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\models\bert\modeling_tf_bert.py", line 887, in call
embedding_output = self.embeddings(
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\engine\base_layer.py", line 1150, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\keras\src\utils\traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\models\bert\modeling_tf_bert.py", line 180, in call
if input_ids is not None:
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\models\bert\modeling_tf_bert.py", line 181, in call
check_embeddings_within_bounds(input_ids, self.config.vocab_size)
File "D:\Anaconda\envs\pytorch1\lib\site-packages\transformers\tf_utils.py", line 190, in check_embeddings_within_bounds
tf.debugging.assert_less(
Node: 'tf_bert_for_sequence_classification/bert/embeddings/assert_less/Assert/Assert'
assertion failed: [The maximum value of input_ids (Tensor(\"tf_bert_for_sequence_classification/bert/embeddings/Max:0\", shape=(), dtype=int32)) must be smaller than the embedding layer\'s input dimension (30522). The likely cause is some problem at tokenization time.] [Condition x < y did not hold element-wise:] [x (IteratorGetNext:1) = ] [[101 2746 14667...]...] [y (tf_bert_for_sequence_classification/bert/embeddings/Cast/x:0) = ] [30522]
[[{{node tf_bert_for_sequence_classification/bert/embeddings/assert_less/Assert/Assert}}]] [Op:__inference_train_function_73426]
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