问题描述
我想处理这段代码，但是InternalError让我烦恼
此数据是kaggle数据，称为“泰坦尼克号：灾难中的机器学习”
import pandas as pd
import numpy as np
import tensorflow as tf
path = '../1.데이터/'
data1 = pd.read_csv(path + "test.csv",index_col = "PassengerId")
data2 = pd.read_csv(path + "gender_submission.csv",index_col = "PassengerId")
test_data = pd.merge(data1,data2,on = "PassengerId")
test_data["Sex"] = pd.get_dummies(test_data["Sex"])
test_data["Embarked"] = pd.get_dummies(test_data["Embarked"])
inde = test_data[["Pclass","Sex","SibSp","Parch","fare","Embarked"]]
sub = test_data["Survived"]
X = tf.keras.layers.Input(shape=[6])
Y = tf.keras.layers.Dense(1,activation='softmax')(X)
model = tf.keras.models.Model(X,Y)
model.compile(loss='sparse_categorical_crossentropy',metrics=['accuracy'])
model.fit(inde,sub,epochs=1000,verbose=0)
model.fit(inde,epochs=10)
错误消息
---------------------------------------------------------------------------
InternalError Traceback (most recent call last)
<ipython-input-34-0d8442a43d4d> in <module>
----> 1 model.fit(inde,verbose=0)
2 model.fit(inde,epochs=10)
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\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_freq,max_queue_size,workers,use_multiprocessing,**kwargs)
817 max_queue_size=max_queue_size,818 workers=workers,--> 819 use_multiprocessing=use_multiprocessing)
820
821 def evaluate(self,C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in fit(self,model,**kwargs)
340 mode=ModeKeys.TRAIN,341 training_context=training_context,--> 342 total_epochs=epochs)
343 cbks.make_logs(model,epoch_logs,training_result,ModeKeys.TRAIN)
344
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in run_one_epoch(model,iterator,execution_function,dataset_size,strategy,num_samples,mode,training_context,total_epochs)
126 step=step,mode=mode,size=current_batch_size) as batch_logs:
127 try:
--> 128 batch_outs = execution_function(iterator)
129 except (stopiteration,errors.OutOfRangeError):
130 # Todo(kaftan): File bug about tf function and errors.OutOfRangeError?
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py in execution_function(input_fn)
96 # `numpy` translates Tensors to values in Eager mode.
97 return nest.map_structure(_non_none_constant_value,---> 98 distributed_function(input_fn))
99
100 return execution_function
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\def_function.py in __call__(self,*args,**kwds)
566 xla_context.Exit()
567 else:
--> 568 result = self._call(*args,**kwds)
569
570 if tracing_count == self._get_tracing_count():
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\def_function.py in _call(self,**kwds)
630 # Lifting succeeded,so variables are initialized and we can run the
631 # stateless function.
--> 632 return self._stateless_fn(*args,**kwds)
633 else:
634 canon_args,canon_kwds = \
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\function.py in __call__(self,**kwargs)
2361 with self._lock:
2362 graph_function,args,kwargs = self._maybe_define_function(args,kwargs)
-> 2363 return graph_function._filtered_call(args,kwargs) # pylint: disable=protected-access
2364
2365 @property
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\function.py in _filtered_call(self,kwargs)
1609 if isinstance(t,(ops.Tensor,1610 resource_variable_ops.BaseResourceVariable))),-> 1611 self.captured_inputs)
1612
1613 def _call_flat(self,captured_inputs,cancellation_manager=None):
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\function.py in _call_flat(self,cancellation_manager)
1690 # No tape is watching; skip to running the function.
1691 return self._build_call_outputs(self._inference_function.call(
-> 1692 ctx,cancellation_manager=cancellation_manager))
1693 forward_backward = self._select_forward_and_backward_functions(
1694 args,C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\function.py in call(self,ctx,cancellation_manager)
543 inputs=args,544 attrs=("executor_type",executor_type,"config_proto",config),--> 545 ctx=ctx)
546 else:
547 outputs = execute.execute_with_cancellation(
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\tensorflow_core\python\eager\execute.py in quick_execute(op_name,num_outputs,inputs,attrs,name)
65 else:
66 message = e.message
---> 67 six.raise_from(core._status_to_exception(e.code,message),None)
68 except TypeError as e:
69 keras_symbolic_tensors = [
C:\tools\Anaconda3\envs\tensorflow2_py37\lib\site-packages\six.py in raise_from(value,from_value)
InternalError: Blas GEMV launch Failed: m=6,n=32
[[node model_7/dense_7/MatMul (defined at <ipython-input-34-0d8442a43d4d>:1) ]] [Op:__inference_distributed_function_1008]
Function call stack:
distributed_function
这是我的环境
[name: "/device:cpu:0"
device_type: "cpu"
memory_limit: 268435456
locality {
}
incarnation: 4159448654357613034,name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 5077532672
locality {
bus_id: 1
links {
}
}
incarnation: 8467986699714318171
physical_device_desc: "device: 0,name: GeForce GTX 1060 6GB,pci bus id: 0000:01:00.0,compute capability: 6.1"
]
tensorflow 2.1.0
keras 2.2.4-tf
pandas 1.1.1
sklearn 0.23.2
scipy 1.5.2
numpy 1.19.1
matplotlib 3.3.1
h5py 2.10.0
我怎么了？有人帮助我
解决方法
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