Tornado 错误 "Global name 'memoryview' is not defined"

本文介绍如何在 Python 2.6.* 版本环境中安装指定版本的 Tornado (2.1.1)。首先使用 pip 卸载原有版本的 Tornado,然后通过 pip 安装指定版本 (2.1.1) 的 Tornado。这一过程确保了开发环境的一致性和稳定性。

说明python版本为2.6.*

使用:

pip uninstall tornado
pip install tornado==2.1.1

 

参考文献:https://github.com/nkrode/RedisLive/issues/93

转载于:https://www.cnblogs.com/jhc888007/p/7247363.html

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]
最新发布
06-24
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