Python 凯拉斯:什么是“a”;“浅层结构”;?
使用Keras和Tensorflow 2.3.1来训练网络时,我收到以下错误消息:Python 凯拉斯:什么是“a”;“浅层结构”;?,python,tensorflow,keras,tensorflow2.0,tf.keras,Python,Tensorflow,Keras,Tensorflow2.0,Tf.keras,使用Keras和Tensorflow 2.3.1来训练网络时,我收到以下错误消息: TypeError: The two structures don't have the same sequence type. Input structure has type <class 'list'>, while shallow structure has type <class 'dict'>. 最好包含完整的回溯,而不仅仅是其中的一行。您能为任何TF数据集提供复制代码吗?@
TypeError: The two structures don't have the same sequence type. Input structure has type <class 'list'>, while shallow structure has type <class 'dict'>.
最好包含完整的回溯,而不仅仅是其中的一行。您能为任何TF数据集提供复制代码吗?@M.Innat数据集和代码都很大。输入元组绝对是这样的形式:
(输入数据,{“target1”:target1,“target1”:target2})
其中输入数据
是[None,n\u步骤,1]
,目标1
是[None,n\u输出]
,目标2
是[None,1]
。我真的希望有人能对“浅层结构”的含义有所了解,这样我就可以开始进一步挖掘了。谢谢您可以使用检查结构是否与数据相同,它检查浅层结构并返回bool。但是什么是“浅层结构”?这是我的问题。我不知道哪个实体或结构是不正确的。最好是包含完整的回溯,而不是其中的一行。你能为任何TF数据集提供复制代码吗?@M.Innat数据集和代码都很大。输入元组绝对是这样的形式:(输入数据,{“target1”:target1,“target1”:target2})
其中输入数据
是[None,n\u步骤,1]
,目标1
是[None,n\u输出]
,目标2
是[None,1]
。我真的希望有人能对“浅层结构”的含义有所了解,这样我就可以开始进一步挖掘了。谢谢您可以使用检查结构是否与数据相同,它检查浅层结构并返回bool。但是什么是“浅层结构”?这是我的问题。我不知道什么实体或结构是不正确的。
File "<ipython-input-2-0c8f2fdd652d>", line 1, in <module>
runfile('/Users/username/my_repo/my_trainer_R2.py', wdir='/Users/username/my_repo')
File "/Users/username/Library/Application Support/JetBrains/Toolbox/apps/PyCharm-P/ch-0/203.5981.165/PyCharm 2020.3 EAP.app/Contents/plugins/python/helpers/pydev/_pydev_bundle/pydev_umd.py", line 197, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "/Users/username/Library/Application Support/JetBrains/Toolbox/apps/PyCharm-P/ch-0/203.5981.165/PyCharm 2020.3 EAP.app/Contents/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/Users/username/my_repo/my_trainer_R2.py", line 131, in <module>
graph_builder.train_model(dataset_train_tuple, dataset_valid_tuple, n_epochs, n_batch_size, run_dir=run_dir, run_name=run_name, valid_dataset=pipeline_valid.get_dataset(), plotting_records=plotting_records[0])
File "/Users/username/my_repo/graph_builder_R2.py", line 401, in train_model
callbacks = [early_stopping_cb, tensorboard_cb, checkpoint_cb, general_callbacks]
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 108, in _method_wrapper
return method(self, *args, **kwargs)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1098, in fit
tmp_logs = train_function(iterator)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
result = self._call(*args, **kwds)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 823, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 697, in _initialize
*args, **kwds))
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 2855, in _get_concrete_function_internal_garbage_collected
graph_function, _, _ = self._maybe_define_function(args, kwargs)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 3213, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 3075, in _create_graph_function
capture_by_value=self._capture_by_value),
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 986, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 600, in wrapped_fn
return weak_wrapped_fn().__wrapped__(*args, **kwds)
File "/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 973, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in user code:
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:806 train_function *
return step_function(self, iterator)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:796 step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
return fn(*args, **kwargs)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:789 run_step **
outputs = model.train_step(data)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:759 train_step
self.compiled_metrics.update_state(y, y_pred, sample_weight)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/compile_utils.py:388 update_state
self.build(y_pred, y_true)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/compile_utils.py:319 build
self._metrics, y_true, y_pred)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/util/nest.py:1139 map_structure_up_to
**kwargs)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/util/nest.py:1221 map_structure_with_tuple_paths_up_to
expand_composites=expand_composites)
/Users/username/.local/lib/python3.7/site-packages/tensorflow/python/util/nest.py:825 assert_shallow_structure
shallow_type=type(shallow_tree)))
TypeError: The two structures don't have the same sequence type. Input structure has type <class 'list'>, while shallow structure has type <class 'dict'>.