如何修复此错误“无法将numpy数组转换为张量”

如何解决如何修复此错误“无法将numpy数组转换为张量”

我正在使用张量流（如年龄，性别等（总共6个值））制作张量流的保险费用预测器（给出单个输出，这是一个浮动）。 这是代码

import tensorflow as tf
import numpy as np
from tensorflow import keras
import pandas as pd
a=0
file=pd.read_csv(r"""C:\Users\lavni\OneDrive\Desktop\proj.csv""",sep=',',index_col=False)
Data = file[['age','sex','bmi','children','smoker','region']].to_numpy()
Charges=file[['charges']].to_numpy()
model = keras.Sequential()
model.add(keras.layers.Dense(units=6,input_shape=(6,)))
model.compile(optimizer='sgd',loss='mean_squared_error')

model.fit(Data,Charges)

运行代码时，出现以下错误：

  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\ML.py",line 14,in <module>
    model.fit(Data,Charges)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\training.py",line 108,in _method_wrapper
    return method(self,*args,**kwargs)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\training.py",line 1063,in fit
    steps_per_execution=self._steps_per_execution)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py",line 1117,in __init__
    model=model)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py",line 265,in __init__
    x,y,sample_weights = _process_tensorlike((x,sample_weights))
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py",line 1021,in _process_tensorlike
    inputs = nest.map_structure(_convert_numpy_and_scipy,inputs)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\util\nest.py",line 635,in map_structure
    structure[0],[func(*x) for x in entries],File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\util\nest.py",in <listcomp>
    structure[0],File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\keras\engine\data_adapter.py",line 1016,in _convert_numpy_and_scipy
    return ops.convert_to_tensor(x,dtype=dtype)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\ops.py",line 1499,in convert_to_tensor
    ret = conversion_func(value,dtype=dtype,name=name,as_ref=as_ref)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\tensor_conversion_registry.py",line 52,in _default_conversion_function
    return constant_op.constant(value,dtype,name=name)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\constant_op.py",line 264,in constant
    allow_broadcast=True)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\constant_op.py",line 275,in _constant_impl
    return _constant_eager_impl(ctx,value,shape,verify_shape)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\constant_op.py",line 300,in _constant_eager_impl
    t = convert_to_eager_tensor(value,ctx,dtype)
  File "C:\Users\lavni\AppData\Local\Programs\Python\python37\lib\site-packages\tensorflow\python\framework\constant_op.py",line 98,in convert_to_eager_tensor
    return ops.EagerTensor(value,ctx.device_name,dtype)
ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type int).

我们将不胜感激，谢谢您。

解决方法

Charges = np.array([file.loc[:,'charges']])

这可能解决了您的问题。首先，使用loc方法过滤数据帧。之后，将其转换为numpy数组。