刚配好autokeras环境准备跑一下mnist简单试一下,
但是在fit的时候就会报错
from keras.datasets import mnist
from autokeras import ImageClassifier
#下载数据
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train.reshape(x_train.shape + (1,))
x_test = x_test.reshape(x_test.shape + (1,))
# Initialize the ImageClassifier.
clf = ak.ImageClassifier(max_trials=3)
# Search for the best model.
clf.fit(x_train, y_train, epochs=3, time_limit=10*60)
报错信息为:
Epoch 1/3
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-10-42cb2b350dcc> in <module>
1 # Search for the best model.
----> 2 clf.fit(x_train, y_train, epochs=3)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/autokeras/tasks/image.py in fit(self, x, y, epochs, callbacks, validation_split, validation_data, **kwargs)
120 validation_split=validation_split,
121 validation_data=validation_data,
--> 122 **kwargs)
123
124
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/autokeras/auto_model.py in fit(self, x, y, batch_size, epochs, callbacks, validation_split, validation_data, **kwargs)
256 validation_data=validation_data,
257 fit_on_val_data=self._split_dataset,
--> 258 **kwargs)
259
260 def _process_x(self, x, fit):
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/autokeras/engine/tuner.py in search(self, callbacks, fit_on_val_data, **fit_kwargs)
112 new_callbacks.append(tf.keras.callbacks.EarlyStopping(patience=10))
113
--> 114 super().search(callbacks=new_callbacks, **fit_kwargs)
115
116 # Fully train the best model with original callbacks.
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/kerastuner/engine/base_tuner.py in search(self, *fit_args, **fit_kwargs)
128
129 self.on_trial_begin(trial)
--> 130 self.run_trial(trial, *fit_args, **fit_kwargs)
131 self.on_trial_end(trial)
132 self.on_search_end()
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/autokeras/engine/tuner.py in run_trial(self, trial, x, *fit_args, **fit_kwargs)
69 model = self.hypermodel.build(trial.hyperparameters)
70 utils.adapt_model(model, x)
---> 71 history = model.fit(x, *fit_args, **copied_fit_kwargs)
72 for metric, epoch_values in history.history.items():
73 if self.oracle.objective.direction == 'min':
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
64 def _method_wrapper(self, *args, **kwargs):
65 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
---> 66 return method(self, *args, **kwargs)
67
68 # Running inside `run_distribute_coordinator` already.
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
846 batch_size=batch_size):
847 callbacks.on_train_batch_begin(step)
--> 848 tmp_logs = train_function(iterator)
849 # Catch OutOfRangeError for Datasets of unknown size.
850 # This blocks until the batch has finished executing.
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
578 xla_context.Exit()
579 else:
--> 580 result = self._call(*args, **kwds)
581
582 if tracing_count == self._get_tracing_count():
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds)
625 # This is the first call of __call__, so we have to initialize.
626 initializers = []
--> 627 self._initialize(args, kwds, add_initializers_to=initializers)
628 finally:
629 # At this point we know that the initialization is complete (or less
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
504 self._concrete_stateful_fn = (
505 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
--> 506 *args, **kwds))
507
508 def invalid_creator_scope(*unused_args, **unused_kwds):
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
2444 args, kwargs = None, None
2445 with self._lock:
-> 2446 graph_function, _, _ = self._maybe_define_function(args, kwargs)
2447 return graph_function
2448
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2775
2776 self._function_cache.missed.add(call_context_key)
-> 2777 graph_function = self._create_graph_function(args, kwargs)
2778 self._function_cache.primary[cache_key] = graph_function
2779 return graph_function, args, kwargs
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
2665 arg_names=arg_names,
2666 override_flat_arg_shapes=override_flat_arg_shapes,
-> 2667 capture_by_value=self._capture_by_value),
2668 self._function_attributes,
2669 # Tell the ConcreteFunction to clean up its graph once it goes out of
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
979 _, original_func = tf_decorator.unwrap(python_func)
980
--> 981 func_outputs = python_func(*func_args, **func_kwargs)
982
983 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in wrapped_fn(*args, **kwds)
439 # __wrapped__ allows AutoGraph to swap in a converted function. We give
440 # the function a weak reference to itself to avoid a reference cycle.
--> 441 return weak_wrapped_fn().__wrapped__(*args, **kwds)
442 weak_wrapped_fn = weakref.ref(wrapped_fn)
443
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
966 except Exception as e: # pylint:disable=broad-except
967 if hasattr(e, "ag_error_metadata"):
--> 968 raise e.ag_error_metadata.to_exception(e)
969 else:
970 raise
AttributeError: in user code:
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py:571 train_function *
outputs = self.distribute_strategy.run(
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:951 run **
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:2290 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/distribute/distribute_lib.py:2649 _call_for_each_replica
return fn(*args, **kwargs)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py:543 train_step **
self.compiled_metrics.update_state(y, y_pred, sample_weight)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/compile_utils.py:391 update_state
self._build(y_pred, y_true)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/compile_utils.py:322 _build
self._metrics, y_true, y_pred)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/util/nest.py:1118 map_structure_up_to
**kwargs)
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/util/nest.py:1214 map_structure_with_tuple_paths_up_to
*flat_value_lists)]
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/util/nest.py:1213 <listcomp>
results = [func(*args, **kwargs) for args in zip(flat_path_list,
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/util/nest.py:1116 <lambda>
lambda _, *values: func(*values), # Discards the path arg.
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/compile_utils.py:421 _get_metric_objects
return [self._get_metric_object(m, y_t, y_p) for m in metrics]
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/compile_utils.py:421 <listcomp>
return [self._get_metric_object(m, y_t, y_p) for m in metrics]
/opt/anaconda3/envs/ak-env/lib/python3.6/site-packages/tensorflow/python/keras/engine/compile_utils.py:442 _get_metric_object
y_t_rank = len(y_t.shape.as_list())
AttributeError: 'tuple' object has no attribute 'shape'
在最后有说AttributeError: 'tuple' object has no attribute 'shape',但是我没有对示例代码或数据集做任何其他的修改,不懂这个错误是怎么出来的。
想过可能是keras版本过高,从2.4降到2.3还是不行。python也是autokeras唯一可用的3.6。tensorflow2.2。感觉这些应该都没问题啊?
求求大佬帮忙